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Human granulocytic anaplasmosis , a tick-borne infection caused by Anaplasma phagocytophilum , has received scant attention , while scrub typhus , a mite-transmitted disease caused by Orientia tsutsugamushi , is the most common rickettsiosis in Taiwan . The clinical presentations of both diseases are characterized by undifferentiated fever , headache and malaise . Moreover , both pathogens have been detected in small mammals that serve as hosts for chiggers and ticks in the wild . The objective of the present study was to investigate whether human granulocytic anaplasmosis occurs in Taiwan . Blood samples from 274 patients suspected of having scrub typhus in Kinmen , an offshore island of Taiwan , in 2011 and 2012 were retrospectively examined by immunofluorescence assays . IgG antibodies reactive with Anaplasma phagocytophilum was found in 31 . 8% ( 87/274 ) of the patients . Paired serology identified 3 patients with human granulocytic anaplasmosis and 8 patients with coinfection with O . tsutsugamushi and A . phagocytophilum . Laboratory tests showed that elevated serum ALT/AST , creatinine , and BUN levels were observed in patients with anaplasmosis and coinfection , but elevated serum CRP levels , thrombocytopenia , and anemia were only observed in coinfected patients . PCR detected A . phagocytophilum 16S rDNA and p44/msp2 in 2 patients . The phylogenetic analysis suggested that the replicons of the 16S rDNA shared high sequence similarity with the reference sequences in the Korea , USA , Japan , and China . The amplicons of p44/msp2 were close to those of the human variants identified in the USA and Japan . Our findings indicated that A . phagocytophilum infection was prevalent but unrecognized in Taiwan .
Human granulocytic anaplasmosis ( HGA ) is an emerging rickettsial disease caused by Anaplasma phagocytophilum . Since it was first identified in the United States , HGA has been reported across Europe and in China , Japan , and South Korea [1–12] . The disease is transmitted by Ixodes ticks , although the species varies according to the habitat , with Ixodes scapularis and Ixodes pacificus found in North America , Ixodes ricinus found in Europe , and Ixodes persulcatus found in Asia [10 , 11 , 13] . Other genera , such as Dermacentor spp . and Rhipicephalus spp . have been reported to be biological vectors , but their significance remains unknown [14 , 15] . Larval or nymphal ticks acquire the bacterium via feeding on infected small mammals before transferring it to humans or domestic animals during their subsequent life stages . Small mammals , including white-footed mice ( Peromyscus leucopus ) , woodrats , squirrels ( Sciurus spp . ) , chipmunks ( Tamias spp . ) , voles , hedgehogs , and shrews are known reservoirs for the rickettsial pathogen [16] . Anaplasma phagocytophilum is an obligate intracellular , Gram-negative bacterium which attacks granulocytes , neutrophils especially . The bacterium enters the host cell by phagocytosis via binding between the fucosylated or sialylated scaffold proteins , e . g . PSGL-1 ( CD162 ) and L-selectin , on the granulocyte surfaces and the bacterium surface protein , e . g . p44/Msp2 [17 , 18] . It has been reported that infection changes gene expressions that modify endocytic pathway and prolong the life of host granulocytes [19 , 20] . The pathogen then replicates by binary fission in an endosome , growing into a cluster called morulae until being released by exocytosis or apoptosis of the host cell . Individuals who have contracted HGA often present with fever , malaise , myalgia , and headache [21] . Although most patients recover spontaneously in a short period of time , as with other rickettsial infections , poor outcomes can occur without prompt treatment . Approximately one-third to one-half of symptomatic patients require hospitalization , and 3% to 7% develop life-threatening complications , with fatality rates less than 1% [22] . HGA can be difficult to diagnose because of the nonspecific nature of the symptoms , but antibiotic therapy needs to be administered as early as possible in the course of the illness when it is most likely to be successful . Doxycycline is the first-line treatment for anaplasmosis in adults and children . Therapy for a presumptive diagnosis should be initiated while waiting for laboratory confirmation via serologic tests , the detection of bacterial DNA by PCR , or bacterium isolation by culturing [1] . In Taiwan , human cases of granulocytic anaplasmosis have not been formally reported , but A . phagocytophilum infections have been identified in Rattus losea , Rattus norvegicus , Mus caroli , dogs , and one nymph each of Ixodes granulatus and Rhipicephalus haemaphysaloides , implying that the pathogen is being transmitted [23–27] . Scrub typhus , in contrast , is listed as a notifiable disease along with epidemic typhus and murine typhus , and it is the best recognized rickettsial disease . Transmitted by trombiculid mites , Orientia bacteria multiply in the inoculation site and disseminate into multiple organs through endothelial cells and macrophages , resulting in the development of fatal complications [28] . The incidence rate of scrub typhus was 1 . 9 per 100 , 000 person-years from 2008 to 2017 while certain offshore island such as Kinmen had an incidence rate as high as 51 . 6 per 100 , 000 person-years , but only 13 . 1–19 . 9% of the blood samples collected for laboratory diagnosis actually tested positive for Orientia infection [29] . The etiological agents of a rather large proportion of rickettsia-like fevers remained to be determined; hence , the current retrospective study was conducted to investigate whether HGA is present in Taiwan .
The use of samples and medical records was approved by the Institutional Review Board of the Taiwan Centers for Disease Control ( Taiwan CDC ) ( No . 102006 ) and the National Taiwan University Hospital Research Ethics Committee ( No . 201806011RIND ) . Blood samples from patients with suspected scrub typhus were sent to the Taiwan CDC laboratory for diagnosis as routine practice . Further application of the leftover specimens was approved by a written informed consent . The material transfer agreement for the samples was officially granted by the Taiwan CDC ( No . 1070001530 ) . All data analyzed were anonymized . Kinmen County consists of a group of offshore islands governed by Taiwan and is located approximately 2 kilometers away from mainland China . Remaining a military reserve until the mid-1990s , development on the islands has been limited . A quarter of the area of the county has been designated as a national park which is famous for migratory birds and wildlife . Human population continuously grew during the past decade , from 84 , 570 in 2008 to 137 , 456 in 2017 . It is one of the counties with the highest prevalence of scrub typhus in Taiwan . Kinmen Hospital is the only regional and referral hospital in Kinmen County . Blood samples from 274 patients presenting with clinical symptoms resembling those of scrub typhus were sent to the Taiwan CDC for laboratory diagnosis from 2011 to 2012 ( 8–72 years of age , mean 26 . 2 years ) . Orientia infection was diagnosed when one of the following criteria was met: ( 1 ) the isolation of O . tsutsugamushi from blood or eschars , ( 2 ) the detection of O . tsutsugamushi DNA , ( 3 ) total antibody titers for IgM≥1:80 and IgG≥1:320 , or ( 4 ) a ≥4-fold increase in antibody titers in paired sera . Infection of A . phagocytophilum was examined by immunofluorescence assay ( IFA ) using the Focus Anaplasma phagocytophilum ( HGA ) IFA IgG Kit ( Focus Technologies , Cypress , CA , USA ) . Patients’ serum samples were diluted from 1:64 to 1:2048 , and the reaction was read at a final magnification of 400X under a fluorescence microscope ( Leica Microsystems , Singapore ) . An IgG endpoint titer ≥1:64 was suggestive of exposure according to the manufacturer’s instructions . A ≥4-fold increase in antibody titers in paired sera indicated current or recent infection . Scrub typhus was diagnosed by an in-house IFA [30] . The serum samples were diluted from 1:40 to 1:640 and reacted with O . tsutsugamushi ( Karp + Kato + Gilliam strains ) -infected L929 cells coated on the slides . The reactive antibodies were detected with FITC-conjugated secondary antibodies , and the slides were then observed under a fluorescence microscope . The medical records of patients with HGA were reviewed retrospectively . The demographic information , clinical manifestations , the results of laboratory tests , clinical diagnoses , comorbidities , and antimicrobial treatments were recorded . The geographic distribution of the patients was mapped manually using the Microsoft Paint and a background map available on USGS LandsatLook ( https://landsatlook . usgs . gov/ ) according to their residential addresses . DNA was extracted from the blood and buffy coats using a QIAamp DNA Blood Mini Kit ( QIAGEN , Hilden , Germany ) . PCR was performed using the primers EHR16SD ( 5’-GGTACCYACAGAAGAAGTCC-3’ ) and EHR16SR ( 5’-TAGCACTCATCGTTTACAGC-3’ ) , which amplify a 345-bp fragment of the 16S rDNA of the Anaplasmataceae family [31] . The reaction was run on a Biometra TRIO thermocycler ( Analytik Jena AG , Jena , Germany ) with the following conditions: 94°C for 15 min , 35 cycles of 94°C for 30 s , 53°C for 30 s , and 72°C for 1 min , followed by termination at 72°C for 10 min . Infection with A . phagocytophilum was further assessed by nested PCR targeting the multiple-copy p44/msp2 gene as previously described [10] . The set of external primers p3726 ( 5’-GCTAAGGAGTTAGCTTATGA-3’ ) and p4257 ( 5'-AAGAAGATCATAACAAGCATT-3’ ) and the set of internal primers p3761 ( 5’-CTGCTCTKGCCAARACCTC-3’ ) and p4183 ( 5’-CAATAGTYTTAGCTAGTAACC-3’ ) were used for amplification . The reaction conditions were 94°C for 15 min , 35 cycles of 94°C for 30 s , 52°C for 30 s , and 72°C for 1 min , followed by 72°C for 10 min . For all reactions , negative water controls were included during each run . The p44/msp2 amplicons from positive samples were then cloned into a pCR2 . 1 vector with the TA Cloning Kit ( Life Technologies , Grand Island , NY , USA ) . For scrub typhus , real-time PCR was also used to detect the 56-kDa type-specific antigen ( TSA ) gene [32] . The reaction was run on an iQ5 iCycler ( BioRad Laboratories , Hercules , CA , USA ) using the KAPA SYBR FAST Universal Kit ( Sigma-Aldrich Corporation , St . Louis , MO , USA ) following the manufacturer’s instructions . Samples were considered positive if they had a cycle threshold value <50 and characteristic amplification plots . The PCR products generated in the study were sent for sequencing in both the forward and reverse directions ( Mission Biotech , Taipei , Taiwan ) . Sequences were aligned using SeqMan Pro ( Lasergene , Madison , USA ) and evaluated for homology with previously reported sequences by a BLAST search of the GenBank database ( http://blast . ncbi . nlm . nih . gov/Blast . cgi ) . A phylogenetic tree was constructed based on the alignment and the most closely related paralogs , followed by the application of Maximum Likelihood method or Neighbor-Joining method ( 1 , 000 bootstrap ) using MEGA7 software [33] . All statistical analyses were performed with SAS v9 . 1 . 3 ( SAS Institute , Cary , NC ) . Categorical variables were compared with Chi-square tests , and continuous variables were analyzed with t-tests; p≤0 . 05 was considered statistically significant . Sequences generated in the study have been uploaded to GenBank . Anaplasma phagocytophilum 16S rDNA: MH260385 , MH260386 , MH260387 , MH260388 , MH260389 , MH260390 , MH260391 , MH260392 . Anaplasma phagocytophilum p44/msp2: MH260370 , MH260371 , MH260372 , MH260373 , MH260374 , MH260375 .
Of the 274 patients suspected of having scrub typhus , 129 cases ( 129/274; 47 . 1% ) were confirmed by the Taiwan CDC laboratory . Moreover , 87 were positive for A . phagocytophilum-specific IgG ( 87/274; 31 . 8% ) ( Table 1 ) . There were no significant differences in positivity rates according to gender , occupation , or age group . Four-fold increases in A . phagocytophilum IgG titers were observed in 11 paired serum samples ( patients A-K ) ( Table 2 ) . While 3 of those patients appeared to have only HGA ( patients A-C ) , 8 of the patients also showed seroconversion against O . tsutsugamushi , suggesting coinfection ( patients D-K ) . The complete medical records of 9 HGA patients ( patients A , B , D-G , I-K ) were retrieved from Kinmen Hospital and carefully reviewed . These patients lived in different villages on the island ( Fig 1 ) , and the infections mostly occurred in June ( n = 6 ) and July ( n = 3 ) when scrub typhus peaked in the years ( S1 Fig ) . The symptoms were summarized in Table 3 . All patients developed fever ( 9/9 ) , while eschars at a variety of sites ( knee , axillary area , back and inguinal area ) were only found in patients coinfected with O . tsutsugamushi . Laboratory tests showed that elevated serum ALT/AST , creatinine , and BUN levels were observed in patients with A . phagocytophilum infection , but elevated serum CRP levels , thrombocytopenia , and anemia were only observed in patients with concurrent scrub typhus and HGA . HGA/scrub typhus coinfection did not seem to negatively impact on the clinical outcomes of patients . All patients recovered after treatment with minocycline or doxycycline ( oral or intravenous administration ) . With regard to the patients’ contact and travel histories , one of the HGA patients ( patient B ) returned from a trip to Guangxi Province in China a week before the onset of symptoms; one patient ( patient A ) had traveled to Taiwu mountain , and another patient ( patient I ) had a history of contact with cattle . However , all patients denied having experienced a recent tick bite ( S1 Table ) . Of the 11 patients who tested positive for HGA serologically , 2 patients were confirmed by molecular diagnosis with evidence that both 16S rDNA and p44/msp2 were successfully amplified . The evolutionary relationships was further inferred by molecular phylogenetic analysis for the 16S rDNA ( Fig 2A , S2 Fig ) and p44/msp2 ( Fig 2B , S3 Fig ) . Anaplasma phagocytophilum 16S rDNA was detected in 8 patients ( patients A-H ) ( Table 2 ) . The resulting sequences that differed from each other by at least in 1 base , were submitted to GenBank ( accession nos . MH260385-MH260392 ) ( S2 Table ) . While two of the amplified fragments ( from patients C and F ) were identical to the reference sequence from Korea ( accession no . MK271308 . 1 ) , the others showed the highest degree of similarity to the sequences from Korea , the USA , Japan , and China ( Fig 2A ) . The p44/msp2 multigene was amplified in 2 patients ( patients D and E ) . Subsequent cloning identified 4 different sequences from 85 clones from patient D ( patient D-36 , 41 , 113 , 134 ) and 2 sequences from 21 clones from patient E ( patient E-16 and 17 ) . All sequences were deposited in GenBank ( accession nos . MH260370-MH260375 ) ( S3 Table ) . Phylogenetic analysis revealed that the amplicons from the same patients clustered together , and the sequences were close to those of the variants identified in the USA and Japan ( Fig 2B ) . A 56-kDa TSA gene was detected in 4 patients ( patients D-G ) . Further sequencing of the 56-kDa TSA gene showed that the PCR products in the study were identical to those of the isolates previously reported in Kinmen in 2006 ( KM0606a , accession no . GQ332760; KM0605a , accession no . GQ332742; KM0607h , accession no . GQ332746 ) [34] . Patient D was infected with the Kawasaki strain of O . tsutsugamushi while the others were infected with the Karp strain . These strains of O . tsutsugamushi have continued to circulate in Kinmen County , where the habitat is favorable for chiggers and small mammals .
In this study , we reported granulocytic anaplasmosis in humans in Taiwan for the first time . Current or recent infection was suggested by seroconversion in paired serum samples from 11 patients . Molecular analysis confirmed A . phagocytophilum in 2 patients , and the amplified fragments shared high sequence similarity to the isolates from Korea , the USA , Japan , and China . Combined with the findings of previous studies that detected A . phagocytophilum DNA in small mammals and ticks , the transmission of the pathogen was further verified [23 , 27] . Moreover , patients with concurrent HGA and scrub typhus were identified despite differences in Acari vectors , reflecting the unique ecosystem in Kinmen in which multiple pathogenic rickettsiae circulate . The Kinmen archipelago is nearly 200 km from the main island of Taiwan . With A . phagocytophilum DNA has been detected in animals on the main island of Taiwan , the scope of human infections requires further investigation [25 , 26] . Although animal hosts and ticks have been reported to be infected by A . phagocytophilum worldwide , reports of infections in humans are less frequent , probably due to misdiagnosis owing to nonspecific clinical signs . Seroprevalence studies have shown that 14 . 9% of the residents in northwest Wisconsin , 17% of Slovenians , 2 . 6% of US military personnel , 16 . 2% of adults from western Norway , and 7 . 6% of adults in Yunnan Province in China have antibodies against A . phagocytophilum without a history suggestive of HGA [35–39] . This could imply the occurrence of subclinical infections . Nevertheless , a recent survey of hunters in eastern Poland detected seropositivity in 30% of the surveyed subjects , and more exposure was noted among those who handle animals than among blood donors from the general population in Belgium , suggesting that environment and animal contact history could be risk factors for infection [40 , 41] . Serological evidence indicated that as many as 87 of the 274 subjects in this study had been exposed at some point to A . phagocytophilum , but no association was found between seropositivity and gender , occupation , or age . Because all participants presented with rickettsia-like fever upon enrollment , the at-risk population needs to be clarified by further reviewing the extent of A . phagocytophilum infection among all age groups of the general population . None of the HGA patients recalled having recently experienced tick bites in the study . Similar findings have been observed , with at least 25% of patients with proven HGA failing to report exposure to ticks [1] . In addition , changes in the hematological and chemical blood tests of patients with HGA were nonspecific , in contrast with previous studies which showed that leukopenia , thrombocytopenia , and liver dysfunction were common in most HGA patients [21] . Nonetheless , serial measurements indicated that these abnormalities soon recovered after the first week of illness [42] . To further confirm A . phagocytophilum infection , PCR was performed with acute phase blood , and the 16S rDNA and p44/msp2 were detected in 8 and 2 patients , respectively . Traditionally being used for screening tests , the 16S rDNA showed higher sensitivity in our findings despite its single copy in the pathogen perhaps due to the design of primers , shorter amplified fragments , specimen preservation or other reasons affecting PCR analysis and cloning . Specimens yielded positive results by both PCR were considered positive for molecular detection in current study . The resulting partial sequences of 16S rDNA were 99–100% identical to the reference sequence from Korea ( accession no . MK271308 . 1 ) while the amplicons of p44/msp2 were 92 . 5–100% identical to an isolate from the USA ( accession no . CP006618 . 1 ) . The conserved nature of the 16S rDNA and the more variable similarity of p44/msp2 were in agreement with other report [43] . Kinmen has been recognized for its idyllic scenery and untouched ecology . During the Cold War era , the islands stood as the military frontier between the People’s Republic of China and Taiwan . The development of Kinmen was strictly focused on the ability to survive a long blockade . Drought-resistant sorghum was introduced for the production of liquor ( kaoliang wine ) as the major source of income . Agricultural and pastoral ways of life remained predominant on the islands until 1992 , when tensions between mainland China and Taiwan gradually eased , and tourists began to visit across the strait . Today , the economy of Kinmen is mainly based on tourism . Investment and infrastructure projects have been undertaken , including the construction of houses , hotels , and businesses , in expectation of economic gains , but these changes also threaten characteristic local industries and traditional agricultural practices . An increase in the number of abandoned farms may have adverse consequences on the risk of disease and expose the residents not only to mite-borne scrub typhus but also tick-borne HGA [44] . Twenty-nine species of ticks belonging to the genera Amblyomma , Aponomma , Boophilus , Dermacentor , Haemaphysalis , Ixodes , and Rhipicephalus in the family Ixodidae have been documented in Taiwan [45] . Recent reports further recorded Haemaphysalis lagrangei parasitizing dogs and Haemaphysalis wellingtoni , Ixodes columnae , and Ixodes turdus parasitizing birds [46 , 47] . While I . persulcatus , an important vector in northeast China , Russia , Japan , and Korea [10 , 11 , 48 , 49] , has not been encountered since 2000 , studies from other countries demonstrated that A . phagocytophilum can infect the tick species that occur in Taiwan . The 16S rDNA from A . phagocytophilum has been detected in snake ticks ( Amblyomma helvolum and Aponomma varanense ) in Malaysia [50] , Amblyomma testudinarium in Thailand and Japan [10 , 51] , Rhipicephalus ( Boophilus ) microplus in China [52] , Haemaphysalis formosensis in Japan [10] , Ixodes nipponensis in Korea [53] , Ixodes ovatus in Japan [54] , and Ixodes simplex in Hungary and Romania [55] . Ixodes granulatus and R . haemaphysaloides are the most common ticks collected from some small mammals captured in Kinmen County [56] , and their infection with A . phagocytophilum has also been reported [23 , 27] , although the transmission cycle of A . phagocytophilum remains to be determined . Anaplasma phagocytophilum infection can also be acquired via exposure to contaminated blood . Nosocomial infections have been reported in Anhui Province in China , suggesting that HGA can be acquired by contact with patient blood or respiratory secretions [57] . Similarly , infections have been reported in butchers exposed to infected deer blood [58] . Perinatal transmission was documented in 1 neonate [59] . A recent case of death from transfusion-transmitted anaplasmosis highlighted a new risk , as blood products are not currently screened for A . phagocytophilum infection [60] . In addition , A . phagocytophilum DNA was found in Tabanid flies , which could be potential vectors for transmission [61] . Whether these alternative routes play any roles in the presence of HGA in Taiwan should be explored . Sequential or simultaneous infections of A . phagocytophilum with tick-borne pathogens such as Borrelia burgdorferi , Babesia microti , and Rickettsia japonica frequently occur after one or multiple tick bites [1 , 10] , but coinfection with mite-borne O . tsutsugamushi was never confirmed despite previous attempts in Korea [62 , 63] . On the other hand , relatively high prevalence of O . tsutsugamushi infections in wild rodents , ranging from 69 . 1% to over 90% , as well as a high chigger infestation rate ( 100% , mostly Leptotrombidium deliense ) and a high chigger O . tsutsugamushi PCR positivity rate ( 96% ) , have been found on the offshore islands and the main island of Taiwan [64–66] . Given that 15 . 8% to 17 . 2% of R . losea , the most abundant species in arable lands or abandoned fields in Kinmen , was infected by A . phagocytophilum and 19% parasitized by ticks [23 , 25] , coinfection is very likely to occur . The study employed IFA to detect antibodies of HGA and scrub typhus . Cross-reactive antibodies have been noted between A . phagocytophilum and E . chaffeensis , but cross-reactions between A . phagocytophilum and B . burgdorferi or O . tsutsugamushi were not significant in the previous studies [62 , 67] . In our findings , concurrent positive reactions were observed in 8 among 129 patients with scrub typhus , and 4 of them had molecular evidence to support the diagnosis . Therefore , we concluded that the cross-reactions were not significant in the study and that patients simultaneously infected with O . tsutsugamushi and A . phagocytophilum were identified . In view of the similarity in the clinical presentations , infection or coinfection with other tick-borne pathogens , for example , A . phagocytophilum , should be considered for patients suspected of having scrub typhus in the future .
We retrospectively examined blood samples from 274 patients with suspected diagnoses of scrub typhus in Kinmen in 2011 and 2012 . IFA results showed that 87 patients ( 87/274; 31 . 8% ) were seropositive for A . phagocytophilum , and 11 patients had evidence of seroconversion; that is , a 4-fold increase in the titer between acute and convalescent sera . Despite nonspecific clinical signs , active infection of A . phagocytophilum was confirmed by molecular diagnosis . Both of the 16S rDNA and p44/msp2 gene were successfully amplified in 2 patients . Phylogenetic analysis revealed that the resulting sequences exhibited high similarity with the variants in Korea , the USA , Japan , and China . Our findings suggested HGA was present on the offshore island of Taiwan , and moreover , cases with concurrent HGA and scrub typhus were identified . Anaplasma phagocytophilum infection should be considered by the physicians for the purpose of early diagnosis and differential diagnosis in the area .
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Human granulocytic anaplasmosis is a tick-borne rickettsial infection caused by Anaplasma phagocytophilum . Although most cases resolve readily , life-threatening complications can occur without prompt antibiotic treatment . The major difficulty in diagnosing human granulocytic anaplasmosis is due to the nonspecific nature of the symptoms . Given that scrub typhus is the most frequently reported rickettsial disease in Taiwan and shares similar early clinical signs with anaplasmosis , we retrospectively examined blood samples from patients with suspected diagnoses of scrub typhus in 2011 and 2012 . While serological evidence of potential past exposure was found in as many as 31 . 8% ( 87/274 ) of the patients , current or recent anaplasmosis was supported by seroconversion in 11 patients , including 8 patients coinfected with scrub typhus . Anaplasma phagocytophilum DNA was detected in acute phase samples , and the amplified fragments were phylogenetically close to those of variants in the Korea , the USA , Japan , and China . Herein , for the first time , we confirmed the presence of human granulocytic anaplasmosis in Taiwan . By reporting coinfections with anaplasmosis and scrub typhus , the study further highlighted the health risk of increasing contact with wild rodents .
|
[
"Abstract",
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2019
|
Human granulocytic anaplasmosis in Kinmen, an offshore island of Taiwan
|
Although retinoic acid ( RA ) teratogenicity has been investigated for decades , the mechanisms underlying RA-induced outflow tract ( OFT ) malformations are not understood . Here , we show zebrafish embryos deficient for Cyp26a1 and Cyp26c1 enzymes , which promote RA degradation , have OFT defects resulting from two mechanisms: first , a failure of second heart field ( SHF ) progenitors to join the OFT , instead contributing to the pharyngeal arch arteries ( PAAs ) , and second , a loss of first heart field ( FHF ) ventricular cardiomyocytes due to disrupted cell polarity and extrusion from the heart tube . Molecularly , excess RA signaling negatively regulates fibroblast growth factor 8a ( fgf8a ) expression and positively regulates matrix metalloproteinase 9 ( mmp9 ) expression . Although restoring Fibroblast growth factor ( FGF ) signaling can partially rescue SHF addition in Cyp26 deficient embryos , attenuating matrix metalloproteinase ( MMP ) function can rescue both ventricular SHF addition and FHF integrity . These novel findings indicate a primary effect of RA-induced OFT defects is disruption of the extracellular environment , which compromises both SHF recruitment and FHF ventricular integrity .
The heart is the first organ to develop and function in all vertebrates . Improper heart development can lead to congenital heart defects ( CHDs ) , which impinge on normal embryogenesis and can result in embryonic or neonatal lethality [1 , 2] . Construction of a functional vertebrate heart requires the precisely coordinated development of two sources of cardiomyocyte progenitors [3] . Progenitors within the anterior lateral plate mesoderm give rise to early-differentiating cardiomyocytes of the first heart field ( FHF ) , which generate the initial heart tube [3 , 4] . Progenitors within the adjacent , medial pharyngeal mesoderm give rise to later-differentiating cardiomyocytes of the second heart field ( SHF ) , which augments the heart through accretion to both the arterial and venous poles [3 , 4] . There has been considerable effort in elucidating the mechanisms of vertebrate SHF development . Numerous studies examining mouse and zebrafish embryos have demonstrated defects in SHF development that result in outflow tract ( OFT ) defects [5–8] . Furthermore , there is a significant need to understand the mechanisms underlying OFT development , because , in humans , OFT defects comprise almost 30% of CHDs , which are the most common class of developmental malformations [2] . Despite advances in understanding many of the intricate signaling mechanisms that direct appropriate SHF development in vertebrates , the molecular etiologies underlying OFT defects still remain poorly understood . It has long been established that proper levels of retinoic acid ( RA ) , a metabolic product of vitamin A , are required for proper OFT development [9] . In particular , it is critical to limit embryonic RA levels , as excess RA is a potent teratogen [9–11] . The most common consequences of RA embryopathies are conotruncal and aortic arch malformations of the OFT [9 , 10] . The major mechanism limiting RA levels within vertebrate embryos are the Cyp26 enzymes ( Cyp26a1 , Cyp26b1 , and Cyp26c1 ) , which facilitate RA degradation [12 , 13] . Cyp26 enzyme deficiency occurs in several human developmental syndromes with OFT malformations , including DiGeorge Syndrome and Antley–Bixler Syndrome [14 , 15] . Previous studies in mice and zebrafish have shown loss of Cyp26a1 or both Cyp26a1 and Cyp26c1 results in heart malformations [16–19] . Although studies using exogenous RA treatment have indicated RA-induced OFT defects are in part due to the failure of cardiac neural crest addition to the arterial pole [20] , excess RA from exogenous or endogenous sources likely also affects ventricular cardiomyocyte development in the OFT . Early exposure to high teratogenic levels of RA , which can inhibit ventricular progenitor specification during early patterning [21–23] , may explain some ventricular OFT defects of the conus . However , the extraordinary sensitivity of ventricular OFT development to increased embryonic RA levels suggests more modest increases in RA levels at stages after early patterning may also produce OFT defects through unexplored mechanisms . We recently demonstrated that Cyp26a1 and Cyp26c1 depletion ( hereafter referred to as Cyp26 deficiency ) causes an expansion of atrial progenitors at the expense of adjacent anterior vascular progenitors during early somitogenesis [16] . Despite these early patterning defects , development of the ventricular FHF within the nascent heart tube was not affected in Cyp26-deficient embryos [16] . Here , we show that Cyp26-deficient zebrafish embryos lack ventricular OFT development after the initial heart tube has formed . Interestingly , the ventricular OFT defects in Cyp26-deficient embryos are derived from two mechanisms: first , there is a failure of SHF progenitors to add to the nascent OFT , which instead contribute to the anterior PAAs , and second , there is a loss of cardiomyocyte polarity and extrusion of differentiated ventricular cardiomyocytes from the heart tube . Although FGF signaling is lost in Cyp26-deficient embryos , a lack of FGF signaling only partially accounts for the ventricular defects . Instead , we find that ventricular OFT defects in Cyp26-deficient embryos are predominantly caused by a parallel increase in matrix metalloproteinase 9 ( mmp9 ) expression . Thus , our data reveal a novel paradigm whereby the primary cause of ventricular OFT defects in Cyp26-deficient embryos is through matrix metalloproteinase ( MMP ) -induced disruption of the extracellular environment that impedes both SHF recruitment and the maintenance of FHF ventricular integrity .
Using previously validated morpholinos ( MOs ) [16 , 24] , we found that Cyp26-deficient embryos display normal overt heart morphology and ventricular cardiomyocyte number at 36 hours post fertilization ( [hpf] , Fig 1A , 1D and 1G ) , confirming our previous observations [16] . However , after initial heart tube formation , Cyp26a1 and Cyp26c1 are both expressed in the pharyngeal arches adjacent to the OFT [25 , 26] . Additionally , analysis of cyp26a1 expression , which is a well-characterized direct RA signaling target gene [27–31] , and a transgenic RA sensor line [32] indicates Cyp26-deficient embryos have increased RA signaling at these later stages in the cardio-pharyngeal region ( S1A–S1F Fig ) , suggesting that Cyp26 enzymes may also be required for proper heart development at later embryonic stages . Consistent with this hypothesis , examining Cyp26-deficient embryos at 48 and 72 hpf revealed hearts that become progressively more dysmorphic , correlating with a significant reduction of both ventricular cardiomyocyte number as well as expression of cardiac differentiation markers myl7 ( pan-cardiac ) and vmhc ( ventricular ) using real-time quantitative polymerase chain reaction ( RT-qPCR ) ( Fig 1B , 1C and 1E–1H ) . Giraffe ( gir ) mutants , which have a nonsense mutation in cyp26a1 leading to a truncation prior to the catalytic domain [25] , have more modest but similar aberrant heart morphology and loss of ventricular cardiomyocytes , a phenotype that is exacerbated when Cyp26c1 is concurrently depleted ( referred to as gir+c1 ) ( S2A–S2Q Fig ) . Treatment with the pan cytochrome P450 ( Cyp ) inhibitor Ketoconazole ( Sigma ) from the two-cell stage or exogenous RA from 24 hpf also produced hearts with similar morphology and reduction of ventricular cardiomyocyte number ( S3A–S3F Fig ) . Additionally , treatment of Cyp26-deficient embryos with DEAB , an inhibitor of RA synthesis , or co-injection of cyp26a1 mRNA with the cyp26 MOs can restore heart morphology and cardiomyocyte number ( S3G–S3P Fig ) . Importantly , the decrease in ventricular cells is not from an increased production of atrial cells . Gir mutants and embryos with Cyp26 knockdown using lower doses of MOs than were used to produce overt early patterning defects have a reduction in ventricular cardiomyocytes independent of any change in atrial cardiomyocyte number ( S2R and S2S Fig ) or the atrial differentiation marker atrial myosin heavy chain ( amhc ) ( Fig 1H ) . Therefore , Cyp26 deficiency causes a specific loss of ventricular cardiomyocytes after the formation of the FHF-derived heart tube . A significant accretion of SHF-derived ventricular cardiomyocytes is observed in the hearts of control embryos after the generation of the predominantly FHF-derived heart tube between 36 and 48 hpf [5 , 33] , which is not observed in Cyp26-deficient embryos ( Fig 1G ) . To explicitly determine if SHF-derived ventricular cardiomyocytes fail to add in Cyp26-deficient embryos , we used the Tg ( myl7:Kaede ) line that facilitates analysis of cardiomyocyte addition through photoconversion of Kaede from green to red in differentiated cardiomyocytes [33] . Embryos were photoconverted just prior to 36 hpf and then imaged at 48 hpf , followed by quantification of ventricular addition ( green only cells ) using ImageJ software . We found that Cyp26-deficient , gir , and gir+c1 embryos all have a significant decrease in the addition of later-differentiating ventricular cardiomyocytes to the OFT compared to control siblings ( Fig 1I–1K and S2T–S2X Fig ) , confirming that SHF-derived ventricular cardiomyocyte addition is disrupted . To determine if other SHF derivatives are also lost , we examined elastin b ( elnb ) , which marks the SHF-derived smooth muscle of the bulbous arteriosus [34] , using in situ hybridization ( ISH ) . In Cyp26-deficient , gir , and gir+c1 embryos , elnb expression was significantly diminished or abolished ( S4A–S4D , S4E and S4G Fig ) . Together , these data confirm there is a failure of later-differentiating SHF derivatives to add to the OFT in Cyp26-deficient embryos . We reasoned that the failure to add SHF-derived ventricular cardiomyocytes to the OFT in Cyp26-deficient embryos could be from either lack of SHF progenitor specification or an inability of SHF progenitors to properly join the extending heart tube . Because our previous work found that patterning of the anterior lateral plate mesoderm can be disrupted in Cyp26-deficient embryos [16] , we first examined SHF progenitor specification . Using ISH and RT-qPCR , we did not find a loss in expression of the SHF progenitor markers mef2cb and ltbp3 , or nkx2 . 5 , which is expressed in cardiomyocyte and pharyngeal arch artery ( PAA ) progenitors [35] , in Cyp26-deficient embryos compared to control siblings ( S5A–S5K Fig ) . Counting nkx2 . 5+ cells lateral to the cardiac cone in the cardio-pharyngeal region at 24 hpf also revealed that there is not a significant change in their number ( S5L Fig ) . Thus , the loss of SHF-derived ventricular cardiomyocytes in Cyp26-deficient embryos is not due to early patterning defects that eliminate SHF progenitor specification . To examine SHF progenitors at time points relevant to the observed SHF ventricular defects , we performed two-color ISH for myl7 to mark the differentiated cardiomyocytes and zsyellow to track nkx2 . 5+ undifferentiated SHF progenitors proximal to the heart tube using Tg ( nkx2 . 5:ZsYellow ) embryos . Cyp26-deficient embryos had an increase in nkx2 . 5:zsyellow expression lateral to the heart at stages from 24 through 36 hpf compared to control embryos ( Fig 2A–2C and 2E–2G ) . After 36 hpf , we found that nkx2 . 5:ZsYellow+ progenitors accumulated outside of the heart tube in Cyp26-deficient embryos ( Fig 2G and 2H ) , suggesting a failure to add differentiated ventricular cardiomyocytes may be due to improper progenitor migration . To specifically test the ability of SHF progenitors to migrate and join the arterial pole of the heart , we used the Tg ( nkx2 . 5:Kaede ) line . Small clusters of nkx2 . 5:Kaede+ cells located adjacent to the forming heart tube or more laterally were photoconverted at 24 hpf ( Fig 2I , 2I’ , 2K and 2K’ ) . The location of the photoconverted red cells with respect to the heart tube was then recorded at 48 hpf ( Fig 2J–2J” , 2L–2L” , 2M and 2N ) . Nkx2 . 5:Kaede+ cells photoconverted adjacent to the nascent heart tube joined the heart tube in both control and Cyp26-deficient embryos at 48 hpf , although the frequency was reduced in Cyp26-deficient embryos ( Fig 2N ) . However , photoconverted nkx2 . 5:Kaede+ cells of the lateral populations , which have previously been shown to also give rise to the PAAs [35] , ingressed into the heart significantly less frequently and more frequently contributed to the third and fourth PAAs of the branchia in Cyp26-deficient embryos ( Fig 2I–2N ) . To determine if there is an increase in endothelial cells that contributed to these arch arteries , we crossed the Tg ( nkx2 . 5:Kaede ) and Tg ( kdrl:nlsEGFP ) lines to facilitate counting of the nkx2 . 5+ endothelial cells via their nuclei . We found that Cyp26-deficient embryos had an increase in the number of endothelial cells in the third and fourth arch arteries ( Fig 2O–2Q ) , suggesting that some SHF progenitors may differentiate as arch artery endothelial cells at the expense of becoming ventricular cells in Cyp26-deficient embryos . Therefore , SHF progenitors fail to migrate and add appropriately to the extending OFT of the heart tube and more frequently contribute to the anterior PAAs in Cyp26-deficient embryos . Although a failure of SHF addition can partially account for the ventricular cardiomyocyte OFT defects in Cyp26-deficient embryos , the cardiomyocyte counts indicate that cells from the mainly FHF-derived heart tube may also be lost , as we observe fewer ventricular cardiomyocytes at 48 and 72 hpf compared to 36 hpf in Cyp26-deficient embryos ( Fig 1G ) . Immunohistochemistry ( IHC ) for activated Caspase 3 ( aCasp3 ) indicated there is not a significant increase in apoptosis within the heart tube of Cyp26-deficient embryos compared to control embryos ( S6A and S6B Fig ) . Thus , cell death within the heart tube does not explain the loss of ventricular cardiomyocytes . However , quite surprisingly , we noticed cardiomyocytes outside the heart tube in ~50% ( 28/61 ) of Cyp26-deficient Tg ( myl7:EGFP ) embryos ( S6B and S6B” Fig ) , as well as in Tg ( myl7:Kaede ) embryos ( Fig 1J ) . In contrast , cardiomyocytes were never observed outside of the heart in control embryos . Furthermore , ectopic myl7:EGFP+ cardiomyocytes were also observed in gir and gir+c1 embryos ( S2K , S2L and S2P Fig ) as well as RA-treated embryos ( S3E Fig ) . Importantly , during the myl7:Kaede assays to address cardiomyocyte addition , we found that the ectopic cardiomyocytes in Cyp26-deficient embryos fluoresced red ( Fig 1J ) , indicating that these cardiomyocytes were differentiated prior to 36 hpf and likely predominantly derived from the FHF . To determine if the ectopic cardiomyocytes are exiting the heart tube , we performed time-lapse imaging from 40 hpf to 52 hpf with confocal microscopy using Tg ( myl7:EGFP ) embryos . This analysis revealed that ventricular cardiomyocytes can be extruded from the differentiated heart tube into the pericardial space in Cyp26-deficient embryos , a phenomenon never observed in control siblings ( Fig 3A and 3B; S1 and S2 Movies ) . Although the aCasp3 IHC did not label cells within the heart tube , we found that the ectopic cardiomyocytes within the pericardial space were co-labeled for aCasp3 and myl7:EGFP+ ( S6A–S6B” Fig ) , suggesting cardiomyocytes that exit the heart undergo apoptosis . Therefore , the loss of ventricular cardiomyocytes in Cyp26-deficient embryos is , at least in part , due to differentiated FHF cardiomyocytes exiting the heart and dying . To begin to understand the cellular mechanisms underlying the ectopic cardiomyocytes in Cyp26 deficient embryos , we examined sectioned hearts with hematoxylin–eosin ( HE ) staining and confocal sections of Tg ( myl7:EGFP; kdrl:mCherry ) hearts . At 48 hpf , both assays revealed an uneven ventricular myocardium with an increased separation between the endocardium and myocardium in Cyp26-deficient embryos ( Fig 3C–3G ) , suggesting adhesion between the myocardial and endocardial cell layers is disrupted . To further investigate ventricular cardiomyocyte adhesion and polarity , we performed IHC with ZO1 and β-catenin in Tg ( myl7:EGFP ) embryos . In Cyp26-deficient and gir+c1 embryos , the ventricular cardiomyocytes of the heart tube were more round ( Fig 3K and S7F Fig ) and separated from each other , with some cardiomyocytes extruded from the single cell layer in the pericardial space ( Fig 3I and 3I” and S7D Fig ) . The ventricular cardiomyocytes also had punctate ZO1 expression ( Fig 3H–3J and S7A–S7E Fig ) and more broadly expressed , mislocalized β-catenin in Cyp26-deficient embryos compared to control siblings ( Fig 3L–3M”‘ ) . Altogether , these data indicate that disruption of myocardial cell polarity and shape may facilitate ventricular cardiomyocyte extrusion from the heart tube in Cyp26-deficient embryos . Next , we sought to identify molecular mechanisms underlying the ventricular OFT defects in Cyp26-deficient embryos . We first examined fibroblast growth factor 8a ( fgf8a ) , because previous studies have shown that RA and FGF exhibit a mutually antagonistic relationship in the heart [36 , 37] , and FGF is required in vertebrates for SHF development through promoting proper proliferation and migration [38–41] . Indeed , fgf8a expression was significantly decreased in Cyp26-deficient embryos and their isolated hearts at 48 hpf ( Fig 4A and 4B ) . Furthermore , within the lateral nkx2 . 5+ cell population , which encompasses the SHF progenitors , proliferation is decreased , consistent with previous findings on loss of FGF signaling ( S5M Fig ) [38–40] . Restoring FGF signaling in Cyp26-deficient embryos at 24 hpf through heat-shock–induced expression of a constitutively active FGF receptor using the transgenic line Tg ( hsp70:ca-fgfr1 ) can restore ventricular addition ( Fig 4C and 4E–4H ) and ventricular cardiomyocyte number at 48 hpf ( Fig 4D and 4I–4L ) . Therefore , these data suggest that the loss of FGF signaling contributes to the ventricular OFT defects in Cyp26-deficient embryos . Despite the ability of induced FGF signaling to rescue some aspects of OFT addition in Cyp26-deficient embryos , heart morphology and the appearance of ectopic cardiomyocytes was not significantly restored ( Fig 4I–4L; S8A and S8B Fig ) . Furthermore , there was still a significant decrease in ventricular cardiomyocyte number ( Fig 4D ) and loss of elnb expression at 72 hpf in FGF-restored Cyp26-deficient embryos ( S4E–S4H Fig ) . An additional induction of FGF signaling at 48 hpf also did not restore ventricular cardiomyocyte number ( S8C Fig ) . Together , these results suggest that loss of FGF signaling can only partially explain ventricular OFT defects and that additional effectors must contribute to the OFT defects in Cyp26-deficient embryos . Because a loss of fgf8a expression cannot completely account for the OFT defects in Cyp26-deficient embryos , we next wanted to identify candidate effectors downstream of RA signaling that could explain the ventricular cardiomyocyte polarity and heart tube integrity defects . We examined matrix metalloproteinase 9 ( mmp9 ) expression , a gelatinase that breaks down collagen in the extracellular matrix [42] , because previous studies have shown that RA signaling can induce its expression in several disease contexts [43–46] . Furthermore , reminiscent of our observations of ventricular cells in Cyp26-deficient embryos , excess MMP9 disrupts the structural integrity of the vasculature [47] and lung epithelium [48] . Using RT-qPCR and ISH , we found MMP9 expression was significantly increased in Cyp26-deficient whole embryos and their isolated hearts ( Fig 5A and 5B; S9A and S9B Fig ) . Gir mutants and gir+c1 embryos also had increased mmp9 expression ( S9C Fig ) . Furthermore , the increased mmp9 expression in Cyp26-deficient embryos is not due to an increase in macrophages or neutrophils ( S9D–S9I Fig ) , which are known to secrete MMP9 [49] . To determine if attenuating MMP function can rescue SHF addition , embryos were treated with a 25-μM concentration of the MMP inhibitor GM6001 [50] beginning at 6 hpf and assayed for ventricular cardiomyocyte addition and number . We found that attenuating MMP function restored SHF addition ( Fig 5C and 5E–5H ) and ventricular cardiomyocyte number at 48 hpf ( Fig 5D ) . In contrast to induction of FGF signaling , heart morphology was markedly improved ( Fig 5I–5L ) , ectopic cardiomyocytes were less frequently observed ( Fig 5M and 5N ) , and ventricular cardiomyocyte polarity and shape were restored ( S10A–S10F Fig ) in GM6001-treated Cyp26-deficient embryos compared to DMSO-treated siblings . Moreover , ventricular cardiomyocyte number was better maintained ( Fig 5D ) , and bulbous arteriosus formation was restored in GM6001-treated Cyp26-deficient embryos through 72 hpf ( S4I–S4L Fig ) . To further test the sufficiency of increased MMP to cause OFT defects , we injected activated human MMP9 protein into the pericardial space of 24 hpf Tg ( myl7:EGFP; kdrl:mCherry ) embryos . A small but significant percentage of MMP9-injected embryos had heart defects similar to Cyp26-deficient embryos that included more linear heart morphology , separation of the endocardium from the myocardium , and ectopic cardiomyocytes ( Fig 5O–5R ) . Altogether , these data suggest that increased MMP activity in Cyp26-deficient embryos likely disrupts the extracellular environment , which impairs SHF addition and ventricular integrity in Cyp26-deficient embryos . Finally , we wanted to determine the hierarchical relationship of these perturbed molecular signals downstream of RA signaling . In Cyp26-deficient embryos , excess MMP9 appeared to underlie both the RA-induced ventricular OFT addition and integrity loss , whereas loss of Fgf8a was only partially responsible for the ventricular addition defects . Thus , because excess MMP9 can account for more of the RA-induced OFT defects than loss of Fgf signaling , we postulated that increased MMP9 may be upstream and contribute to the loss of fgf8a expression in Cyp26-deficient embryos . In contrast to this hypothesis , attenuating MMP function did not restore fgf8a expression in Cyp26-deficient embryos ( Fig 5S ) , and , conversely , restoring FGF signaling did not affect mmp9 expression ( Fig 5T ) . Therefore , our data support a model in which fgf8a and mmp9 act in parallel downstream of RA signaling in Cyp26-deficient embryos ( Fig 5U ) .
Our studies have provided insight into previously unappreciated cellular and molecular mechanisms of RA-induced OFT defects . We find that excess embryonic RA levels from endogenous sources due to Cyp26 deficiency inhibit ventricular OFT development after initial heart tube formation . The loss of proper ventricular OFT development in Cyp26-deficient embryos is due to both a failure of ventricular SHF progenitor addition and loss of differentiated FHF-derived ventricular cells from the initial heart tube . Furthermore , SHF progenitors more frequently contribute to and differentiate as third and fourth PAA cells in Cyp26-deficient embryos , which has not been described previously . Although loss of FGF signaling plays a role downstream of excess RA in the generation of OFT defects , we identified that excess MMP9 is a primary effector of ventricular OFT defects in Cyp26-deficient embryos . Thus , our studies support the hypothesis that disruption of the extracellular environment is a key cause of RA-induced ventricular OFT defects after the initial stages of heart development . In many developmental contexts , RA signaling has an antagonistic relationship with FGF signaling . During patterning of the cardiac progenitor field , previous studies have shown that RA signaling establishes the posterior boundary of the SHF in mice and zebrafish [37 , 51 , 52] . At slightly later stages , FGF signaling is required to promote SHF progenitor proliferation and deployment [39 , 40 , 53] . Our studies indicate that it is critical to limit RA signaling after the initial patterning of FHF progenitors to promote FGF signaling that directs SHF progenitor development , providing another developmental context for the antagonistic relationship between these essential pathways . Consistent with previous analysis of FGF signaling in SHF development [39 , 53] , we found that there is decreased proliferation in SHF progenitors . However , in comparing the ventricular OFT defects in Cyp26- and FGF signaling–deficient embryos , it is noteworthy that the loss of ventricular cardiomyocytes in Cyp26-deficient embryos is much greater than the loss of ventricular cardiomyocytes previously reported for FGF signaling deficient embryos ( >50% loss in Cyp26-deficient versus ~20% loss in FGF signaling–deficient embryos ) [54] . Importantly , restoration of FGF signaling in Cyp26-deficient embryos only partially restored ventricular cardiomyocyte number and did not restore ventricular integrity . Thus , our interpretation is that decreased FGF signaling in SHF progenitors is only one mechanism that contributes to RA-induced OFT defects in vertebrates . A key finding of our study is that perturbation of the extracellular environment , which we posit in turn adversely affects ventricular cardiomyocyte polarity , is one of the main factors contributing to OFT defects from surplus RA signaling . Previous studies of fibronectin levels in zebrafish have shown that a proper extracellular matrix environment is required for FHF progenitor migration to the midline during somitogenesis [55 , 56] . In mice , fibronectin is required for SHF development , with loss of fibronectin resulting in shortened OFTs [57] . Interestingly , previous studies also found that excess RA signaling can disrupt the extracellular matrix in the endocardial cushions , leading to transposition of the great arch arteries [58 , 59] . However , the mechanisms underlying extracellular matrix disruption in this context are not understood . Our data implicate a necessity to limit MMP9 levels within the heart tube and surrounding environment . Although our study is the first to our knowledge to designate misregulation of MMP9 as a crucial effector of RA-induced OFT defects , exogenous RA signaling promotes MMP9 expression in several other developmental and disease contexts , including dendritic cell migration [60] , neuroblastoma [43 , 44] , and glomerulosclerosis [45] . Although there are multiple conserved RA response elements in the promoter of MMP9 [61] , future experiments will be necessary to determine if RA signaling directly promotes MMP9 expression within the pharyngeal tissues and heart . Interestingly , recent studies of Ezh2 , a component of the Polycomb repressive complex 2 ( PRC2 ) , have indicated a necessity to limit MMP9 expression in vascular development , as excess MMP9 can result in loss of vascular integrity [47] . Tie2-mediated conditional knockdown of Ezh2 in endothelial cells results in a separation of the endocardium from the myocardium observed at E11 . 0 [47] , similar to what we observe in Cyp26-deficient embryos . Additionally , direct application of MMP9 to the lung epithelium causes loss of tight junctions and cell extrusion [48] , which is highly reminiscent of the ventricular cardiomyocyte polarity and integrity defects we observe in Cyp26-deficient embryos . Although we do not find a direct transcriptional relationship between fgf8a and mmp9 , it is interesting that a recent study found that Cadm4 , which is involved in cell adhesion , is a downstream effector of FGF signaling in OFT development [38] , suggesting FGF signaling may promote critical interactions with the extracellular environment . Future experiments will determine if RA-induced MMP9 expression directly perturbs signals known to promote proper SHF development , including FGF , Tgf-β ligands and their receptors , and cell adhesion molecules . RA signaling has been shown to function in a regulatory loop with Tbx1 and FGF signaling . Disruption of this regulatory network is thought to underlie malformations in DiGeorge Syndrome , at least in the posterior pharyngeal mesoderm [62] . Additionally , cell polarity and tight junction defects have recently been described in SHF progenitors of Tbx1 null mice [63] . Although previous studies have found RA signaling negatively regulates tbx1 expression during early somitogenesis [64 , 65] , via RT-qPCR and ISH , we found that tbx1 expression is not reduced or significantly altered in Cyp26-deficient embryos at these later stages ( S5N–S5R Fig ) . Therefore , we have identified unanticipated temporal sensitivity to the canonical Tbx1-RA signaling regulatory loop [15 , 65–67] , suggesting that transcriptional repression of tbx1 due to excess RA signaling cannot explain the later ventricular cardiomyocyte OFT defects in Cyp26-deficient embryos presented here . Moreover , previous genetic interactions between RA signaling and Tbx1 have been shown to affect the most posterior pharyngeal arteries through affecting the neural crest in mice [67–71] . Thus , our data are the first to indicate that excess RA signaling can promote a surplus of endothelial cells in the more anterior arch arteries , potentially at the expense of ventricular SHF progenitors and independent of the canonical Tbx1-RA regulatory mechanism . Altogether , our study provides critical insight into the sensitivity of OFT development to excess embryonic RA levels , which can occur from genetic loss of Cyp26 enzymes or exogenous RA treatment . Furthermore , we found that excess RA signaling at later stages of development than previously appreciated can disrupt ventricular cells derived from both the FHF and SHF . Importantly , our study is also the first , to our knowledge , to implicate excess MMP9 and consequently disruption of the extracellular environment as primary effectors of RA-induced CHDs . The function of Cyp26 enzymes and the necessity to limit RA signaling is a highly conserved aspect of vertebrate heart development . Therefore , our findings significantly enhance understanding of the molecular and cellular etiologies of developmental syndromes with RA-induced OFT defects .
All zebrafish husbandry and experiments were performed under conditions outlined in protocols approved by IACUC and Cincinnati Children’s Hospital Medical Center . Adult zebrafish were grown and maintained under standard laboratory conditions [72] . Transgenic lines used were: Tg ( β-actin:VPBD-RLBD;UAS:EGFP ) [32] , Tg ( –5 . 1myl7:DsRed2-NLS ) f2 [73] , Tg ( −6 . 5kdrl:mCherry ) ci5 [74] , Tg ( myl7:Kaede ) sd22 [33] , TgBAC ( −36nkx2 . 5:ZsYellow ) fb7 [7] , Tg ( nkx2 . 5:Kaede ) fb9 [75] , Tg ( kdrl:nlsEGFP ) [76] , Tg ( myl7:EGFP ) twu [77] , and Tg ( hsp70:ca-fgfr1 ) pd3 [54] . The giraffe/cyp26a1 mutant line [25] was used . MO injections were performed at the one-cell stage as described previously [16] . MO sequences for cyp26a1 and cyp26c1 were previously published [24 , 78] . Knockdown of cyp26a1 and cyp26c1 together was attained using a cocktail of 1 . 5 ng cyp26a1 MO1 , 0 . 75 ng cyp26a1 MO2 , and 4 ng cyp26c1 . For experiments using the gir mutant embryos , heterozygous carriers were in-crossed , and the resulting embryos were either injected using 4 ng cyp26c1 MO or kept as uninjected controls . Nonspecific MO-induced cell death was counteracted with 2 ng p53 MO for all injections . The cyp26a1 mRNA was injected at 500 pg as previously described [79 , 80] . IHC and cardiomyocyte counts were performed using Tg ( myl7:DsRed-NLS ) embryos as described previously [22] . For cell counts and cell polarity markers , embryos were fixed with 1% Formaldehyde in 1X PBS for 1 h then washed with 0 . 2% Saponin in 1X PBS for 3X at 5 min . Embryos were blocked with Saponin Blocking solution ( 1X PBS , 10% sheep serum , 2 mg/ml BSA and 0 . 2% Saponin ) for 1 h then incubated with primary antibody at 4°C overnight . Embryos were washed with 0 . 2% Saponin in PBS 3X at 5 min then incubated with secondary antibodies in Saponin Blocking solution for 2 h at room temperature . Embryos were washed with 0 . 2% Saponin in 1X PBS 3X at 5 min then imaged or stored at 4°C for up to 1 wk . Primary antibodies used were anti-DsRed2 1:1000 ( 632496 , Clontech ) , anti-sarcomeric myosin ( MHC ) /MF20 1:10 ( gift of D . Yelon ) , anti-atrial myosin heavy chain ( AMHC ) /S46 1:10 ( University of Iowa Hybridoma Bank ) , anti-GFP chick 1:250 ( ab13970 , Abcam ) , anti-ZO1/TJP11:250 ( 33–9100 , Life Technologies ) , and anti-β-catenin 1:100 ( C7207-100UL , Sigma ) . Secondary antibodies for goat anti-chicken IgG-FITC ( 6100–02 , Southern Biotech ) , Goat anti-mouse IgG1 TRITC ( 1070–02 , Southern Biotech ) , Goat anti-mouse IgG1 FITC ( 1070–02 , Southern Biotech ) , goat anti-rabbit IgG-TRITC ( 4050–02 , Southern Biotech ) and Goat anti-mouse IgG2b TRITC ( 1090–03 , Southern Biotech ) were all used at 1:100 . For detection of aCasp3 and phospho-Histone H3 ( pHH3 ) staining , embryos were fixed in 4% paraformaldehyde at 4°C overnight then dehydrated with a methanol series to 100% methanol and left in the -20°C freezer for at least 2 h . Embryos were rehydrated using PBST ( PBS with 1% tween ) then permeabilized using PDT ( PBST with 1% DMSO ) supplemented with 0 . 3% Triton-X for 20 min at room temperature . Embryos were then blocked with 1xPBS/0 . 1%Tween20/10% sheep serum ( 013-000-121 Jackson Immunoresearch ) for 30 min followed by incubation in primary antibodies overnight at 4°C . Embryos were rinsed 3X for 20 min with PDT then reblocked for 30 min and incubated in secondary antibodies for 2 h at room temperature . Embryos were washed 3X for 5 min with PDT then imaged or stored at 4°C for up to 1 mo . Primary antibodies used were rabbit anti-active Caspase-3 1:250 ( 559565 , BD Biosciences Pharmigen ) and anti-histone H3 1:750 ( ab14955 , Abcam ) . Secondary antibody used was goat anti-rabbit IgG-TRITC ( 4050–02 , Southern Biotech ) at 1:100 dilution . For both methods , embryos were imaged using either a Zeiss M2BioV12 fluorescent stereomicroscope or Nikon A1 confocal microscope . To count nkx2 . 5+ cells in the cardio-pharyngeal region and pHH3+ cells , the IHC was performed as described above . Embryos were oriented dorsal side down in a small well created by using a capillary tube to punch a hole in a layer of 2% agarose within a μ-Slide 2-well ( Ibidi ) followed by imaging with a Nikon A1 confocal microscope . Images were analyzed using Imaris software ( Bitplane ) . Despite the absence of a nuclear tag nkx2 . 5:ZsYellow the individual nuclei of cells were still clearly visible , which facilitated the creating of spots in Imaris and cell counting . Stocks of 10 mM Ketoconazole ( BP2734-50 , Fisher ) , 100 mM RA , and 1 mM DEAB ( 4-diethylaminobenzaldehyde; Sigma ) were dissolved in DMSO ( Sigma ) . Embryos were treated at a final concentration of 25 μM Ketoconazole in embryo water starting at two-cell stage . Embryos were treated with a final concentration of 2 μM RA in embryo water starting at 24 hpf . Embryos were treated with a final concentration of 25 nM DEAB in embryo water starting at 50% epiboly . GM6001 ( CC1010 , Millipore ) was purchased in a 2 . 5 mM stock in DMSO . Embryos were treated with 25 μM GM6001 in embryo water starting at 50% epiboly . cDNA preparation and RT-qPCR was performed as previously described [16 , 78] . Briefly , embryos were lysed in Trizol then RNA was isolated using the PureLink RNA Micro Kit ( Invitrogen ) . cDNA was obtained using the Thermoscript RT-PCR System ( Invitrogen ) . RT-qPCR was performed under standard conditions using SYBR green PCR master mix ( Applied Biosystems ) in a Bio-Rad CFX PCR machine . Expression levels of myl7 , vmhc , mef2cb , ltbp3 , nkx2 . 5 , fgf8a , and mmp9 were standardized to β-actin . Data were analyzed using 2−ΔΔCT Livak Method and Student's t test . Primer sequences for myl7 , vmhc , nkx2 . 5 , and β-actin were previously reported [16] . Primer sequences for ltbp3 were previously reported [7] . Primer sequences for fgf8a , mef2cb , mmp9 , and tbx1 are as follows: fgf8a F-aatccggacctaccagcttt and R-atcagtttccccctcctgtt , mef2cb F-ctatggaaaccaccgcaact and R-tgcgcagactgagagttgtt , mmp9 F-caaatctgtgttcgtgacgttt and R-tccgtcgaatgtcttgtagttg , and tbx1 F-tattccggatccaactcagc and R-taatctgccattgggtccat . Whole mount ISH was performed as previously described [81] . Probes for mef2cb ( ZDB-GENE-040901-7 ) , ltbp3 ( ZDB-GENE-060526-130 ) , zsyellow ( accession number: Q9U6Y4 ) , nkx2 . 5 ( ZDB-GENE-980526 ) , myl7 ( formerly cmlc2; ZDB-GENE-991019 ) , mfap4 ( ZDB-GENE-040426-2246 ) , and mpx ( ZDB-GENE-030131-9460 ) were previously reported . The elnb probe was cloned from cDNA using primers F′-cagaggcaaaagctgcaaaatatg and R′-atccttgaccaaatcctccagcgg and placed into the pGemT-easy vector ( Promega ) . The mmp9 probe was cloned from cDNA using primers F′-tgacgggaacagcaatgaagc and R′-tggagaaggtttcgttggcac and placed into pGemT-easy vector ( Promega ) . Probe was synthesized using standard methods . Two-color ISHs were performed as described previously [82] using INT-BCIP ( Roche ) . Embryos were de-yolked , flatmounted , and imaged using a Zeis M2BioV12 stereomicroscope . Fixed embryos were embedded in paraffin and sectioned at 7-μ thickness . HE was performed using the HE stain kit ( American Master Tech ) as directed by kit protocol . Heart isolations were performed as described previously [83] . Heat-shock experiments were performed using hemizygous Tg ( hsp70:ca-fgfr1 ) carriers crossed to either Tg ( myl7:Kaede ) or Tg ( –5 . 1myl7:DsRed-NLS ) adult fish . Resulting embryos were raised at 28 . 5°C until 24 hpf then they were heat-shocked at 37°C for 30 min in a BioRad Thermal Cycler . Carriers of the Tg ( hsp70:ca-fgfr1 ) transgene were identified by crystalline-RFP in the lens and sorted from non-carriers at 48 hpf using Nikon A1 confocal or at 72 hpf using a Zeiss M2BioV12 fluorescent stereomicroscope . Embryos were then used for either Kaede-addition experiments or cell counts . Photoconversion of Kaede from Tg ( myl7:Kaede ) embryos was achieved by exposing the embryos to fluorescent light from a DAPI filter on a Zeiss M2BioV12 fluorescent stereomicroscope until all green fluorescence was gone ( approximately 15 min ) . At 48 hpf , embryos were anesthetized with Tricaine , gently compressed under a coverslip , and imaged using a Nikon A1 confocal microscope . Cardiomyocyte addition to the heart was analyzed using ImageJ to measure the area of green-only OFT . Photoconversion of Kaede in specific groups of cells in Tg ( nkx2 . 5:Kaede ) embryos was performed by orienting embryos dorsal side up in a small well created by using a capillary tube to punch a hole in a layer of 2% agarose within a μ-Slide 2-well ( Ibidi ) . Kaede+ cells from embryos were first imaged using the 20X objective on a Nikon A1 confocal microscope . Then , a specific cluster of Kaede+ cells was photoconverted using a 10X zoom of the 20X objective and the DAPI filter . Conversion of Kaede+ cells took approximately 30 s . The Kaede+ green and red cells from the embryos were then imaged again . Imaged embryos were maintained at 28 . 5°C until 48 hpf when they were scored for contribution to cardiomyocytes and imaged using a Nikon A1 confocal microscope . Counting of endothelial cells in the third and fourth PAAs was performed in hemizygous Tg ( nkx2 . 5:Kaede; kdrl:nlsEGFP ) embryos . Kaede was photoconverted to red , as described above , in nkx2 . 5+ cells just prior to imaging . Embryos were then mounted laterally on a footed coverslip , and confocal images were taken at 1 . 5-μm intervals to generate 10–25 μm Z-stacks of the arches using a Nikon A1 confocal microscope . Reconstructions of the pharyngeal arches were created using NIS Elements . EGFP-expressing endothelial cells in the third and fourth PAAs were then manually counted . Images for time-lapse movies were taken with a Nikon A1 confocal microscope . Embryos were mounted in a μ-Slide 2-well ( Ibidi ) with 0 . 6% low melt agar and oriented to provide a frontal view of the heart . Using NIS Elements software , a time-lapse program was set up where the Z-stacks were taken spanning 150 μm at 3 μm per step . Hearts were imaged every 15 or 30 min . After imaging , the Z-stacks were reconstructed into hearts , cropped , and depth coded using NIS Elements software . Tg ( myl7:EGFP; kdrl:mCherry ) embryos were raised to 24 hpf then mounted laterally in 0 . 6% low melt agar . Embryos were injected into the pericardial space with either Cascade blue-dextran tracer ( D-1976 , Invitrogen ) alone or along with 12 pg activated MMP9 protein ( ab168863 , Abcam ) . Embryos were left to recover for 15 min then removed from the low melt agar and transferred to fresh embryo water . Embryos were analyzed , fixed with 4% Formaldehyde in PBS , and imaged using a Nikon A1 confocal microscope at 48 hpf . All RT-qPCR was analyzed using 2−ΔΔCT Livak Method and Student's t test . Circularity measurements were performed by measuring area and perimeter in ImageJ then calculating circularity as 4piArea/perimeter^2 and analyzed using Student's t test . Cell counts were analyzed using Student's t test . Contribution of nkx2 . 5:Kaede cells to the heart and arches was analyzed using a Chi Squared test .
|
Retinoic acid ( RA ) is the most active metabolic product of vitamin A . The embryonic heart is particularly sensitive to inappropriate RA levels , with cardiac outflow tract ( OFT ) defects among the most common RA-induced malformations . However , the mechanisms underlying these RA-induced defects are not understood . Cyp26 enzymes facilitate degradation of RA and thus are required to limit RA levels in early development . Here , we present evidence that loss of Cyp26 enzymes induces cardiac OFT defects through two mechanisms . First , we find that Cyp26-deficient zebrafish embryos fail to add later-differentiating ventricular cardiac progenitors to the OFT , with some of these progenitors instead contributing to the nearby arch arteries . Second , Cyp26-deficient embryos cannot maintain the integrity of the nascent heart tube , with ventricular cells within the heart tube losing their polarity and being extruded . Our data indicate that excess expression of matrix metalloproteinase 9 , an enzyme that degrades the extracellular matrix , underlies both the cardiac progenitor addition and heart tube integrity defects seen in Cyp26-deficient embryos . Our findings highlight perturbation of the extracellular matrix as a major cause of RA-induced cardiac OFT defects that specifically disrupt ventricular development at later stages than previously appreciated .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"physiology",
"medicine",
"and",
"health",
"sciences",
"cardiovascular",
"anatomy",
"vertebrates",
"animals",
"endocrine",
"physiology",
"cell",
"polarity",
"animal",
"models",
"organisms",
"developmental",
"biology",
"osteichthyes",
"model",
"organisms",
"developmental",
"signaling",
"arteries",
"growth",
"factors",
"embryos",
"cellular",
"structures",
"and",
"organelles",
"fibroblast",
"growth",
"factor",
"research",
"and",
"analysis",
"methods",
"embryology",
"fishes",
"blood",
"vessels",
"extracellular",
"matrix",
"endocrinology",
"signal",
"transduction",
"zebrafish",
"anatomy",
"cell",
"biology",
"physiology",
"biology",
"and",
"life",
"sciences",
"cell",
"signaling",
"heart"
] |
2016
|
Cyp26 Enzymes Facilitate Second Heart Field Progenitor Addition and Maintenance of Ventricular Integrity
|
Nondisjunction of chromosome 21 is the leading cause of Down syndrome . Two risk factors for maternal nondisjunction of chromosome 21 are increased maternal age and altered recombination . In order to provide further insight on mechanisms underlying nondisjunction , we examined the association between these two well established risk factors for chromosome 21 nondisjunction . In our approach , short tandem repeat markers along chromosome 21 were genotyped in DNA collected from individuals with free trisomy 21 and their parents . This information was used to determine the origin of the nondisjunction error and the maternal recombination profile . We analyzed 615 maternal meiosis I and 253 maternal meiosis II cases stratified by maternal age . The examination of meiosis II errors , the first of its type , suggests that the presence of a single exchange within the pericentromeric region of 21q interacts with maternal age-related risk factors . This observation could be explained in two general ways: 1 ) a pericentromeric exchange initiates or exacerbates the susceptibility to maternal age risk factors or 2 ) a pericentromeric exchange protects the bivalent against age-related risk factors allowing proper segregation of homologues at meiosis I , but not segregation of sisters at meiosis II . In contrast , analysis of maternal meiosis I errors indicates that a single telomeric exchange imposes the same risk for nondisjunction , irrespective of the age of the oocyte . Our results emphasize the fact that human nondisjunction is a multifactorial trait that must be dissected into its component parts to identify specific associated risk factors .
The overwhelming majority of trisomy 21 , or Down syndrome , is caused by the failure of chromosomes to separate properly during meiosis , also known as chromosome nondisjunction . As nondisjunction is the leading cause of pregnancy loss , mental retardation and birth defects , it is imperative that we understand the biology underlying this phenomenon . Characteristics of chromosome 21 nondisjunction are typical of many of the other human autosomes . That is , the overwhelming majority are due to errors during oogenesis: at least 90% of cases of chromosome 21 nondisjunction are due to maternal meiotic errors [1] , [2] . In addition , among these maternal errors , the majority occur during meiosis I ( MI ) [3] , [4] . It has been well established that increased maternal age , the most significant risk factor for nondisjunction , is associated specifically with errors occurring during oogenesis . Interestingly , for chromosome 21 nondisjunction , advanced maternal age is associated with both maternal MI and meiosis II ( MII ) errors [5] . The timing of meiosis in the human female suggests risk factors that may be involved in chromosome nondisjunction . Meiosis is initiated at about 11–12 weeks of gestation and , after pairing , synapsis and recombination , arrests in prophase I until just prior to ovulation . At that time , the oocyte completes MI and progresses to metaphase II where it remains until it is fertilized and the meiotic process is completed . Thus , homologous chromosomes are arrested in prophase I for 10 to 50 years . In contrast , spermatogenesis in the human male begins at puberty and cells entering meiosis move from one stage to the other with no delay . This extended state of arrest in oocyte formation is hypothesized to be associated with the increased prevalence of maternal nondisjunction . Chiasmata function to stabilize paired homologous chromosomes ( tetrads ) during MI along with sister chromatid and centromere cohesion . They also help to properly orient homologous chromosomes on the meiotic spindle [5] . A proportion of nondisjunction is associated with failure of homologues to pair or to recombine , leading to an increased risk for homologue malsegregation during MI [6]–[9] . In our previous work [10] , it was estimated that 45% of maternal MI cases of trisomy 21 did not have an exchange along chromosome 21 . We also found that the location of the exchange was associated with nondisjunction: a single exchange near the telomere of 21q increased the risk of maternal MI nondisjunction and the presence of an exchange near the centromere increased the risk for so called MII nondisjunction . This association of a MI event ( i . e . , recombination ) with a MII error in chromosome segregation led us to suggest that MII nondisjoining errors are initiated during MI . To represent this finding , we will refer to MII errors in quotes . Most recently , we have explored the relationship between maternal age and recombination to gain further insight into potential mechanisms of abnormal chromosome segregation [11] . We compared the frequency and the location of exchanges along 21q between women ( or “oocytes” ) of various maternal ages who had an infant with Down syndrome due to a maternal MI error . While there was no significant association between maternal age and the overall frequency of exchange , the placement of meiotic exchange differed significantly by maternal age . In particular , single telomeric recombinant events were present in the highest proportion among the youngest age group ( 80% ) , while the proportions in the oldest group of women with nondisjoined chromosomes 21 and in women with normally disjoining meiotic events were almost equal ( 14% and 10% , respectively ) . We speculated that for young women then , the most frequent risk factor for MI nondisjunction is the presence of a telomeric exchange . As a woman ages , her meiotic machinery is exposed to an accumulation of age-related insults , becoming less efficient/more error-prone . The susceptible telomeric exchange pattern still increases susceptibility to nondisjunction , but now even homologous chromosomes with optimally placed exchanges are at risk . Over time , the proportion of nondisjunction due to normal exchange configurations increases as age-dependent risk factors exert their influence . As a result , the most prevalent exchange profile of nondisjoined oocytes shifts from susceptible to non-susceptible patterns with increasing age of the oocyte . As mentioned above , our studies also identified an association between the presence of a meiotic exchange within the pericentromeric region of 21q and “MII” nondisjunction [10] , but further studies were not possible due to limited sample size . We have now increased our sample size and , for the first time , have been able to investigate the relationship of exchange patterns stratified by maternal age for maternal “MII” cases of trisomy 21 . This increase in sample size has also allowed us to refine our analysis of recombination in maternal MI cases by maternal age . These analyses have provided further insight into the complex pathways leading to nondisjunction among oocytes .
Among normal disjoining maternal meiotic events , exchanges most often occur in the center of 21q [11] . This observation suggests that the presence of a single medially placed exchange is important for normal segregation of homologous chromosomes 21 . This pattern is in striking contrast to the chromosomes 21 that have undergone maternal MI or “MII” nondisjunction , where either no exchange occurs or single exchanges occur at the very ends of 21q [8] , [10] . In order to better understand the factors that play a role in these recombination-related disjoined events , we have examined both the number and location of recombination along nondisjoined chromosomes 21 stratified by maternal age . In these analyses , maternal age served as a proxy for the age of the oocyte . First , among normally disjoining chromosomes 21 in oocytes , there was no obvious association between maternal age and the frequency of exchange or the location of exchange along chromosome 21 . We did not expect to observe a maternal age association , as our comparison group , taken from the CEPH families , was relatively small compared to Kong et al . [9] , the only study that has noted such an association . In that study , it took over 14 , 000 maternal meiotic events in order to identify that the frequency of exchanges increased with maternal age: an additional two recombinants genome-wide were estimated over a 25 year age span . Thus , the magnitude of the observed association is not on the same scale as that observed for nondisjoined meiotic events . Irrespective , we still must be cautious with our results and emphasize that the sample sizes of meiotic events , particularly those in the older age groups were small ( Table S1 ) and thus limited our ability to detect maternal age associations with recombination . Whereas there was no obvious maternal age association with recombination patterns among normally disjoining chromosomes 21 , there was a significant one among maternal MI and “MII” errors . One set of observations provides evidence for specific recombination patterns being the proximal cause of nondisjunction , while the others suggest an interaction between specific recombination patterns and maternal age-related risk factors . Figure 1 provides an overall summary of our findings related to the spatial distribution of exchanges for MI and “MII” nondisjunction events ( using the data from Table 2 ) . In Figure 2 , we interpret these findings , as well as those associated with the frequency of exchanges ( Table 1 ) within the context of the overall rate of trisomy 21 among women of the three age groups ( see Materials and Methods for calculations ) . In this figure , the overall rate of trisomy 21 among births by maternal age group is represented by the height of each bar and is estimated from Hecht and Hook [14] . Within each bar , the proportion of those rates that are estimated to have a specific origin and recombination pattern is denoted by color . Here , we have focused on meiosis occurring in the aging oocyte . Several meiotic proteins that function to promote proper chromosome segregation have been shown to degrade with increasing age [15] , [16] . This degradation is assumed to lead to increased frequency of nondisjunction; thus , more maternal-age related risk factors for nondisjunction exist among older women compared to younger women . In the analyses presented here , we have compared the pre-disposing recombination patterns among the oocytes with nondisjoined events by maternal age ( Figure 1 ) . Our expectation is that some recombination patterns will lead to susceptibility irrespective of other maternal age factors and these will predominate the youngest age group , or that group with no other risk factors . We found that single telomeric exchanges follow this pattern ( Figure 2 , “MI: E1 int 6” ) , as reported previously [11] . This type of error represents less than 8% of each maternal age group . This same risk factor has been established in model organisms as well [17]–[19] . Most likely , susceptibility is related to the minimal amount of the sister chromatid cohesion complex remaining distal to the exchange event [20] . Specifically , when the exchange is too far from the kinetechore , this could prevent the biorientation of homologues on the meiotic spindle [18] , [21]–[23] . Alternatively , the integrity of the chiasma may be compromised when a minimal amount of cohesin remains to hold homologues together . Thus , bivalents may act as a pair of functional univalents during MI , as has been observed in human oocytes [24] , [25] . The results related to lack of exchange are intriguing , although difficult to interpret at this time . We did find that the proportion of E0s was the highest among the youngest group compared with the other two age groups , indicating a maternal-age independent mechanism . However , the proportions did not decrease linearly with age ( Table 1 ) . Conservatively , we can state that E0s lead to susceptibility irrespective of the age of the oocyte . However , the non-significant increase in E0 in the older age group causes us to speculate further . As noted in Figure 2 ( “MI: E0” ) , the lack of a linear decrease by age group suggests that a greater proportion of older oocytes at risk for trisomy 21 will have E0 tetrads compared with the other two age groups . Perhaps these results provide preliminary evidence for a secondary mechanism that is age-dependent . In model systems , there are known mutations that lead to increased nondisjunction of E0s . For example , Drosophila with mutations in the gene nod ( no distributive disjunction ) , show increased nondisjunction of non-exchange chromosomes [26] . This observation was the first to suggest a mechanism that functions to ensure the proper segregation of non-exchange homologues . Studies in yeast also provide evidence for such a mechanism [27] . Interestingly , proteins in humans that may have a similar function to those that play a role in the proper segregation of non-exchange homologues in yeast have been shown to be down regulated with increasing ovarian age [15] , [16] . Thus , the age-dependent down-regulation of these essential proteins , or others , may lead to the decreased ability to properly segregate non-exchange chromosomes in aging oocytes . However , this is only speculation at this point . More data are needed to determine significance of our preliminary finding . Interestingly , the analysis of the normally disjoining meiotic events from the CEPH data indicates a large proportion of E0s , 20% . These data are based on genotyping a high density of chromosome 21-specific SNPs among 152 maternal meiotic events [28] . Other studies have used the CEPH families and have obtained similar frequencies of observed recombinants and estimates of E0 frequencies [29] , [30] . These data suggest a higher frequency of E0s compared with other studies that have used techniques that examine tetrads more directly , such as chiasma counts or MLH1 counts . For example , Tease et al . [31] identified three E0 chromosome 21 bivalents out of a total of 86 counted . However , all 86 oocytes analyzed came from only one ovary . As variation in recombination rates among women is well established [28] , [32] , we need to be careful in drawing conclusions about the difference in estimates of E0 using MLH1 counts versus linkage studies . Nevertheless , future studies are required to determine if the frequency of E0s is significantly different from zero for chromosomes 21 in oocytes ( e . g . , using MLH1 counts ) and in transmissions to births ( e . g . , linkage studies ) , each representing a different time point in oocyte development . These studies will complement those among nondisjoined events to determine if a distributive pairing system similar to those in model systems exists in humans . The other established susceptibility pattern that is associated with an increased risk for “MII” nondisjunction is the presence of a single exchange within the most proximal 5 . 2 Mb of 21q . When we compared such events among age groups , we observed an enrichment of pericentromeric exchanges in the oldest age group of “MII” nondisjoined chromosomes 21 as summarized in Figure 1 . This leads to a greater proportion of trisomy 21 cases among older women being related to pericentromeric exchanges ( Figure 2 , “MII: E1 int 1” ) . This pattern can be explained in two different ways: 1 ) a pericentromeric exchange sets up a suboptimal confirmation that exacerbates the effect of maternal age-related risk factors or 2 ) a pericentromeric exchange protects the bivalent from maternal-age related risk factors allowing the proper segregation of homologues , but not sister chromatids . An example of the former would be that a pericentromeric exchange compromises proteins involved in centromeric cohesion , exacerbating the normal degradation of this important complex with age . Shugoshin , a protein important in protecting centromere cohesin during MI , would be an obvious target . For example , in yeast cells that were shugoshin deficient , Marston et al . [33]showed that homologous chromosomes segregated to opposite poles in MI , but sister chromatids prematurely separated prior to anaphase II and segregated randomly , sometimes leading to MII nondisjunction . Interestingly , BubR1 , the protein required for the localization of shugoshin to the centromere , has been shown to have decreased expression with increasing maternal age in the human female [15] , [16] . Perhaps the presence of a pericentromeric exchange exacerbates the degradation of this complex . Alternatively , a pericentromeric exchange may protect the bivalent from maternal-age related risk factors . The effect of degradation of centromere or sister chromatid cohesin complexes or of spindle proteins with age of the oocyte may lead to premature sister chromatid separation . Perhaps a pericentromeric exchange helps to stabilize the compromised tetrad through MI . This would lead to an enrichment of MII errors among the older oocytes . Although there is no specific model system that points to this mechanism , findings can be interpreted with this mechanism in mind . For example , the effects of a hypomorph of bubR1 were examined in female meiosis in Drosophila [34] . In mutant females , most chiasmate X chromosome failed to segregate properly at MII , most likely due to premature sister chromatid separation in late MI anaphase or MII . Interestingly , a subtle but repeatable increase in pericentromeric exchanges was identified along such chromosomes . Lastly , we examined the hypothesis that the number of exchanges may be protective against maternal age-related risk factors . This was first suggested by Robinson et al . [35] , who found that among maternal MI chromosome 15 nondisjunction errors , the age of the mother was significantly increased among cases with multiple recombinants compared with those having zero or only one observed recombinant . From this , the authors suggested that cases with multiple recombinants might be more resistant to nondisjunction because of increased stability of the tetrad over time . Similarly , an analysis of maternal nondisjunction of the X chromosome showed that the mean maternal age of cases with recombination was significantly older than that of cases with no recombination [36] . This same pattern was observed for trisomy 18 , although the difference was not statistically significant [37] . For chromosome 21 MI errors , we do not see this pattern . Among the young , middle and older age groups , the observed data infer 40% , 23% and 33% of tetrads have multiple exchanges among our young , middle and old groups respectively ( Table 1 ) . Among chromosome 21 “MII” errors , we observe a very different pattern: 78% , 49% and 44% of tetrads have multiple exchanges , respectively . This pattern is opposite of that expected if multiple exchanges were protective . Again , we need to be cautious in our interpretation for the following reason . We have assumed that “MII” cases with no recombination are due to post-zygotic , mitotic events . As shown in Figure 2 , these appear to be age-independent events . However , some proportion may be true MII errors with no recombination and we do not have a method to distinguish these alternatives . We have not discussed our observations related to the placement of multiple recombinants along the nondisjoined chromosomes 21 and the potential effects of altered interference . This is due to the obvious fact that chromosome 21 is small , leading to only a few meiotic events on which we could derive exchange patterns . There were approximately 20 meiotic events in each age category of MI and MII errors . Thus , this type of investigation awaits a larger sample size , or , perhaps , should be based on larger nondisjoined chromosomes ( e . g . , chromosome 15 or the X chromosome ) . The importance of understanding the causes of nondisjunction and the maternal age effect cannot be over-stated . Many women are electing to delay childbearing until their mid-thirties or later , the time at which nondisjunction rates dramatically increase . Irrespective of the exact mechanisms of nondisjunction , our findings indicate that nondisjunction is a complex trait and that there are different risk factors that play a role in age-independent and dependent nondisjunction . The study design for identification of such environmental and genetic risk factors can be guided by our findings . Clearly , examination of nondisjunction events stratified by maternal age , type of error and recombination pattern should increase the power to identify important factors that play a role in chromosome mal-segregation .
Families with an infant with full trisomy 21 were recruited through a multisite study of risk factors associated with chromosome nondisjunction [2] , [8] , [10] . Parents and the infant donated a biological sample ( either blood or buccal ) from which DNA was extracted . All recruitment sites obtained the necessary Institutional Review Board approvals from their institutions . Only families in which DNA was available from both parents and the child with trisomy 21 were included in the present analysis . A subset of families in the current analysis with maternal MI errors were also included in a previous study [6] . Samples were genotyped for a minimum of 21 short tandem repeat ( STR ) markers specific to the long arm of chromosome 21 ( Figure 3 ) . The most centromeric STR was D21S369 and the most telomeric was D21S1446 . Our analysis of the number and location of recombination was restricted to 21q . The long arm of chromosome 21 was divided into six relatively equal physical intervals with interval 1 comprising the most centromeric region of 21q and interval 6 comprising the most telomeric region ( Figure 3 ) . The presence of a recombinant event was identified by changes in the status of adjacent informative markers from “reduced” to “nonreduced” ( or vice versa ) . In most cases , the location of recombination was scored as belonging to one of six distinct intervals along 21q . When one of the six intervals was uninformative , but markers defining the two flanking intervals were informative , we included the family . Those with two or more adjacent uninformative intervals were excluded from our analysis . In some instances , the recombinant event could not be located to one specific interval , but instead to one of two adjacent intervals ( e . g . , interval 1 or interval 2 ) . The location of such events was treated as occurring at the midpoint of the two intervals ( e . g . , represented as interval 1 . 5 ) in most of our analyses ( see Statistical Analysis below ) . Our final analysis included a total of 615 maternal MI cases and 253 maternal “MII” cases of trisomy 21 . In order to determine the location of recombination along 21q in women who exhibited normal segregation of chromosome 21 , the transmission of maternal grandparental SNP genotypes to the maternal offspring was analyzed . A maternal recombinant event was noted when the sharing of SNPs identical by descent switched from one maternal grandparent to the other . Our final analysis included 152 informative maternal meioses .
|
Nondisjunction occurs when chromosomes fail to segregate during meiosis; when this happens , gametes with an abnormal number of chromosomes are produced . The clinical significance is high: nondisjunction is the leading cause of pregnancy loss and birth defects . We have studied trisomy 21 using DNA from individuals with Down syndrome and their parents to identify mechanisms underlying nondisjunction . The results from these studies show that altered patterns of recombination , e . g . , no exchange , a single telomeric exchange and a single pericentromeric exchange , were associated with nondisjunction of chromosome 21 within the oocyte . In this report , we stratified maternal cases of trisomy 21 by the type of nondisjunction error ( meiosis I or meiosis II ) and by maternal age ( ages <29 , 29–34 and >34 years ) and examined both the number and location of recombination by age group . Our results suggest that the risk imposed by the absence of exchange or by a single telomeric exchange is the same , irrespective of the age of the oocyte . In contrast , the risk imposed by a single pericentromeric exchange increases with increasing maternal age . These findings , put into the context of proteins involved in the meiotic process , have enabled us to further understand mechanisms underlying nondisjunction .
|
[
"Abstract",
"Introduction",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"molecular",
"biology/recombination",
"genetics",
"and",
"genomics/chromosome",
"biology"
] |
2008
|
New Insights into Human Nondisjunction of Chromosome 21 in Oocytes
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Many organisms have a mechanism for down regulating the expression of non-synapsed chromosomes and chromosomal regions during meiosis . This phenomenon is thought to function in genome defense . During early meiosis in Caenorhabditis elegans , unpaired chromosomes ( e . g . , the male X chromosome ) become enriched for a modification associated with heterochromatin and transcriptional repression , dimethylation of histone H3 on lysine 9 ( H3K9me2 ) . This enrichment requires activity of the cellular RNA-directed RNA polymerase , EGO-1 . Here we use genetic mutation , RNA interference , immunofluorescence microscopy , fluorescence in situ hybridization , and molecular cloning methods to identify and analyze three additional regulators of meiotic H3K9me2 distribution: CSR-1 ( a Piwi/PAZ/Argonaute protein ) , EKL-1 ( a Tudor domain protein ) , and DRH-3 ( a DEAH/D-box helicase ) . In csr-1 , ekl-1 , and drh-3 mutant males , we observed a reduction in H3K9me2 accumulation on the unpaired X chromosome and an increase in H3K9me2 accumulation on paired autosomes relative to controls . We observed a similar shift in H3K9me2 pattern in hermaphrodites that carry unpaired chromosomes . Based on several assays , we conclude that ectopic H3K9me2 accumulates on paired and synapsed chromosomes in these mutants . We propose alternative models for how a small RNA-mediated pathway may regulate H3K9me2 accumulation during meiosis . We also describe the germline phenotypes of csr-1 , ekl-1 , and drh-3 mutants . Our genetic data suggest that these factors , together with EGO-1 , participate in a regulatory network to promote diverse aspects of development .
During sexual reproduction , mutations existing in the gametes will be inherited by the offspring . Therefore , it is essential that gametes contain accurate copies of the genetic information . Through evolution , multiple mechanisms have been developed to safeguard gamete quality . One such mechanism may be a process referred to as meiotic silencing of unpaired chromatin ( MSUC ) whereby genes located on unpaired chromatin are silenced during first meiotic prophase . This is a widespread phenomenon that has been described in fungi , nematodes , and mammals ( for reviews , see [1]–[3] ) . While it naturally involves sex chromosomes in the heterogametic sex , meiotic silencing also targets unsynapsed regions that may be present due to mutation or chromosome rearrangement [4]–[6] . MSUC may function as a surveillance mechanism to protect against detrimental conditions such as aneuploidy or expression of genetic parasites ( e . g . , transposable elements ) that are inserted in one homolog and would not properly align during meiosis [1] , [7] . MSUC may also function in the segregation of non-homologous chromosomes , e . g . , the mammalian X and Y chromosome [3] . Distinct mechanisms of MSUC appear to function in different species , although some common components and features are involved . MSUC in nematodes and mammals occurs at the transcriptional level . In C . elegans , regions of unpaired chromatin , e . g . the male X chromosome , accumulate a histone modification associated with transcriptional silencing , H3K9me2 [4] . High levels of H3K9me2 also accumulate on free chromosomal duplications and chromosomes that fail to synapse due to mutations in both the XX and XO germ line [4] . Few X-linked genes are expressed in the male germ line , therefore it is difficult to correlate H3K9me2 accumulation with repression of gene expression in males . However , transcription of X-linked oogenesis-specific genes decreases dramatically in sexually transformed XO hermaphrodites , suggesting that the H3K9me2 marks indeed correlate with gene silencing [8] . The C . elegans meiotic silencing machinery may involve small RNA , e . g . , small interfering ( si ) RNA , as activity of the RNA-directed RNA polymerase ( RdRP ) , EGO-1 , is required for H3K9me2 enrichment on unpaired regions [9] . In mouse , as in C . elegans , histone modifications associated with gene silencing accumulate on regions of unpaired chromatin , e . g . the male X and Y chromosomes and chromosomal translocations in both XX and XO germ lines . These regions also accumulate histone variants , e . g . , macroH2A1 . 2 and γH2AX [5] , [10]–[13 , ] ( see also [3] ) . Mammalian meiotic silencing is known to require machinery closely related to the DNA repair pathways ( see [1] ) . In the filamentus fungus , Neurospora crassa , MSUC ( also called meiotic silencing by unpaired DNA , MSUD ) requires the activity of: an RNA-directed RNA polymerase ( RdRP ) , SAD-1 [14]; a member of the Argonaute family of RNA binding proteins , SMS-2 [15]; and a Dicer endonuclease-like protein , DCL-1 [16] . N . crassa meiotic silencing appears to occur at a post-transcriptional level via a mechanism related to RNA interference ( RNAi ) ( for a review of the core RNAi machinery , see [17] ) . For example , meiotic silencing elicited by a chromosomal deletion will target paired copies of the deleted region ( present as transgenes ) that are located at a distinct site [14] . This behavior is not observed in C . elegans , e . g . , the presence of a chromosomal duplication does not lead to H3K9me2 accumulation on paired copies of the intact chromosome [4] , [8] . Small RNA has been implicated in heterochromatin assembly in a number of systems ( for reviews , see [18]–[20] ) . Mechanistic details appear to vary from one system to another , as the mechanisms involve different constellations of proteins . The best-studied case , heterochromatin assembly at centromeric repeats in the yeast , Schizosaccharomyces pombe , requires Dicer , RdRP , and Argonaute ( Ago ) activity [21]–[25] . Here , Ago and endogenous siRNAs participate in an RNA-induced transcriptional silencing ( RITS ) complex whose chromatin association is sufficient for directing H3K9me2 accumulation [18] , [19] , [25] . Dicer and Argonaute activity have also been shown to promote centromeric heterochromatin assembly in Drosophila melanogaster , an organism that apparently lacks cellular RdRP [26] , [27] . Similarly , Dicer , Argonaute , and RNA helicase activities are linked to heterochromatin formation and the subsequent elimination of repeated DNA sequences in the micronuclei of Tetrahymena thermophila [28] , [29] ( for a review , see [30] ) . In mammals , as well , a growing body of evidence suggests that promoter transcripts and an Argonaute protein may participate in transcriptional regulation [31]–[33] . In general , these transcriptional silencing mechanism ( s ) are poorly understood , and the identified RNAi factors might act indirectly , e . g . , as participants in the post-transcriptional regulation of genes whose products function directly in chromatin regulation . Interestingly , Dicer activity does not appear to be required for meiotic H3K9me2 enrichment on unpaired chromatin in C . elegans , suggesting that microRNAs and other Dicer-dependent RNA products do not participate in the regulatory process [9] . To identify additional components of the MSUC machinery in C . elegans , we surveyed candidate genes to identify those whose loss of function altered the pattern of H3K9me2 accumulation during meiosis . Here , we report the identification of CSR-1 , EKL-1 , and DRH-3 as additional regulators of meiotic H3K9me2 accumulation . These proteins function in RNAi , and DRH-3 ( like EGO-1 ) is implicated in the biogenesis of endogenous siRNAs [34] , [35] . Here , we provide evidence that H3K9me2 does not accumulate properly on unpaired chromatin in csr-1 , ekl-1 , and drh-3 mutants and is mis-targeted to correctly paired and synapsed chromatin . Moreover , the germline phenotypes of csr-1 , ekl-1 , and drh-3 mutants are complex and share some features with the ego-1 phenotype . As previously shown for ego-1 [36] , [37] , csr-1 , ekl-1 , and drh-3 interact genetically with glp-1 , which encodes the germline Notch-type receptor required for germ cell proliferation . We discuss alternative models for how these factors may participate in the regulation of meiotic chromatin .
We used two approaches to identify candidate genes whose products might participate in meiotic silencing: ( i ) we compiled a list of factors that had been implicated in small RNA-mediated processes , including Argonaute proteins and putative chromatin-associated proteins [38]–[52] ( Table 1 ) ; and ( ii ) we surveyed a set of ego mutants , previously isolated in our screens for genetic enhancers of glp-1 ( ego mutations ) , whose phenotypes resemble that of ego-1 [36] ( J . Spoerke and E . Maine , unpublished data ) . ego-1 mutants have a specific developmental phenotype that is not commonly observed , but is characteristic of some other mutants isolated in our ego screens . We subjected these candidates to two tests . First , we used indirect immunofluorescence to evaluate the meiotic H3K9me2 staining pattern in available mutants or after depletion via RNAi ( see Materials and Methods ) . Our RNAi assays were performed using him-8 mutants , as the hermaphrodite X chromosomes remain unpaired/unsynapsed and therefore become enriched for H3K9me2 . Second , we tested type ( i ) candidates genes for an Ego phenotype using RNAi-mediated knockdown in animals with a weak glp-1 loss of function mutation , glp-1 ( bn18ts ) at 20°C ( see Materials and Methods ) . We identified four genes from the candidate gene list whose activities influenced meiotic H3K9me2 distribution: csr-1 , ekl-1 , drh-3 , and sin-3 ( Table 1 ) . Three of these genes were also identified as Ego: csr-1 , ekl-1 , and drh-3 ( Table 1 ) . We also identified three ego mutants with altered H3K9me2 distribution , ego ( om55 ) , ego ( om56 ) , and ego ( om83 ) . The three ego mutations mapped close to ekl-1 and drh-3 ( see Materials and Methods ) ; we cloned them in order to determine whether they represented alleles of ekl-1 , drh-3 , and/or other genes whose products function in meiotic chromatin regulation . Our data indicate that ego ( om56 ) and ego ( om83 ) are alleles of ekl-1 , and ego ( om55 ) is an allele of drh-3 ( Figure 1 ) ( see Materials and Methods ) . Intriguingly , CSR-1 ( an Argonaute protein ) , DRH-3 ( a Dicer-related DEAH/D-box helicase ) , and EKL-1 ( a Tudor domain protein ) all , like EGO-1 , promote RNAi ( Table 1 ) . Hence , we hypothesize that these factors may work together to regulate meiotic H3K9me2 accumulation via a mechanism that involves small RNA , e . g . , endogenous siRNA . We will focus this report on the role of CSR-1 , EKL-1 , and DRH-3 in meiotic silencing and will discuss SIN-3 in a future report . In wild type males , the X chromosome preferentially becomes enriched for H3K9me2 during early pachytene stage and maintains this enrichment until germ cells become primary spermatocytes [4] ( Figure 2A ) . Other chromosomes exhibit a relatively low level of H3K9me2 . In ego-1 null mutant males ( hereafter designated ego-1 males ) , X chromosome enrichment fails to occur , and all chromosomes accumulate a variable and low level of H3K9me2 [9] ( Figure 2C ) . In csr-1 ( tm892 ) , ekl-1 ( om83 ) , and drh-3 ( tm1217 ) males , H3K9me2 was distributed more broadly across the chromosomes than in controls , and a single focus was rarely observed ( Figure 2B , 2D , 2E ) . Several foci were visible in some nuclei , which also tended to have a higher overall level of the mark . We quantified the relative proportion of nuclei with each labeling pattern , and the proportion of nuclei with normal meiotic versus abnormal chromosomal morphology ( Table 2 ) . It was difficult to quantify the H3K9me2 level since the labeling intensity varied even among control preparations . However , we obtained a general measure of labeling intensity by comparing images captured at equivalent exposures . The majority of nuclei with normal pachytene morphology lacked a strong focus of H3K9me2 labeling when compared with wild type ( ranging from 57% of pachytene nuclei in csr-1 males to 83% of pachytene nuclei in ekl-1 males ) ( Figure 3 ) . A smaller proportion of the nuclei with normal morphology had multiple bright H3K9me2 foci and/or a higher overall level of H3K9me2 ( ranging from 14% in ekl-1 to 34% in csr-1 males ) ( Figure 2B , Figure 3 ) . In such nuclei , one of the foci may correspond to the X chromosome . The H3K9me2 distribution appeared essentially normal in a small proportion of nuclei ( ranging from 3% in ekl-1 to 9% in csr-1 males ) , particularly nuclei located in the proximal region of the gonad arm . Among morphologically abnormal nuclei , the most striking ones were large and had diffuse chromosome morphology; these nuclei , which may have been polyploid , tended to have multiple H3K9me2 foci and a high overall level of H3K9me2 ( Figure 2B , Table 2 ) . To identify the X chromosome , we co-labeled H3K9me2 and a histone “activating” mark that is present on autosomes but absent from the X chromosomes in germ cells , H3K4me2 [4] , [53] . We consistently observed a chromosome without H3K4me2 , which presumably corresponds to the X chromosome ( Figure 3 ) . We observed a variable level of H3K9me2 associated with this chromosome; in many nuclei , the level was substantially reduced compared with controls . We also observed frequent H3K9me2 enrichment co-localizing with H3K4me2 ( Figure 3 ) . We interpreted this phenotype to reflect enrichment for H3K9me2 on autosomal sites in the absence of CSR-1 , EKL-1 , or DRH-3 activity . In contrast to the male ( XO ) germ line , we observed no obvious defect in H3K9me2 accumulation in mutant hermaphrodite ( XX ) germ lines ( data not shown ) . We considered two possibilities for why this might be the case: CSR-1 , EKL-1 , and DRH-3 function might affect chromatin assembly only in male germ cells or , alternatively , only in germ cells with significant unpaired chromatin ( e . g . , unpaired chromosomes or a chromosomal duplication ) . To distinguish between these hypotheses , we examined H3K9me2 accumulation in mutant hermaphrodites where the X chromosomes did not pair or synapse ( genotype ekl-1 ( om83 ) ; him-8 and drh-3 ( tm1276 ) ; him-8 ) and in hermaphrodites carrying a free chromosomal duplication ( genotype sDp3;csr-1 ( tm892 ) , ekl-1;sDp3 , and drh-3;sDp3 ) . In these five strains , H3K9me2 foci were reduced in intensity relative to controls , and there appeared to be a mild increase in H3K9me2 levels on other chromatin ( Figure 4 ) . To distinguish between autosomes and X chromosomes in drh-3;him-8 and ekl-1;him-8 hermaphrodites , we co-labeled H3K4me2 and H3K9me2 marks . In both control and experimental animals , we consistently identified chromosomal regions that failed to accumulate H3K4me2 and were presumably the X chromosomes ( Figure S1 ) . Consistent with the data presented in Figure 4 , these H3K4me2-negative regions were highly enriched for H3K9me2 in him-8 controls , but much less so in the mutants . These results suggest that unpaired regions are not as highly targeted for H3K9me2 in csr-1 , ekl-1 , and drh-3 hermaphrodites as they are in wildtype hermaphrodites . We compared the developmental phenotypes of ego-1 , csr-1 , ekl-1 and drh-3 mutants in order to address further the functional relationship among the four gene products ( see Materials and Methods ) . As discussed above , loss-of-function mutations in each gene enhanced a mild GLP-1/Notch defect in the germ line . We observed additional germline defects in young adult hermaphrodites and males of each genotype , as follows: a moderately reduced number of germ cells; a larger than normal proportion of leptotene-zygotene nuclei; a smaller than normal proportion of pachytene nuclei; a delay in the sperm-oocyte switch; and abnormal oogenesis ( Figure 5D , 5G , 5H , Table 3 , data not shown ) . ekl-1 , csr-1 , and drh-3 germ lines contained some large nuclei with a diffuse chromosomal morphology quite distinct from pachytene and diplotene nuclei; we previously observed morphologically similar nuclei in ego-1 mutants [35] , [54] ( see Figures 2 and 3 , Table 2 ) . 100% of hermaphrodites produced abnormal , small oocytes and 100% of their progeny died as embryos . As adults aged , oocytes tended to back up around the loop and there was a reduction in the proportion of the germ line in mitosis and first meiotic prophase . These observations are consistent with previous reports of sterility in csr-1 mutants [40] , [42] , and ekl-1 mutants [40] and an oogenesis defect in drh-3 mutants [34] , [56] . Wild type oocytes arrest at diakinesis with six pairs of bivalents visible per nucleus ( Figure 5A ) . In csr-1 , ekl-1 and drh-3 mutants , a subset of oocyte nuclei appeared to contain unpaired homologous chromosomes ( univalents ) , as previously observed for ego-1 ( Figure 5H , and data not shown ) [37] . The penetrance of this phenotype was variable with respect to the number of univalents per nucleus and the proportion of diakinesis nuclei with this abnormal morphology . The phenotype was more penetrant in ekl-1 mutants ( 50% of gonad arms contained at least one oocyte with univalents ) than in ego-1 , csr-1 , or drh-3 mutants ( ≤18% of gonad arms contained oocytes with univalents ) ( Table 3 ) [37] . The presence of univalents was rarely fully penetrant within any single oocyte; instead , for individual mutants , the number of abnormal chromosome figures ranged from 7 ( ego-1 , csr-1 , drh-3 ) to 11 ( drh-3 ) ( Table 3 ) indicating asynapsis or desynapsis of 1–5 chromosome pairs . The presence of both a protracted leptotene-zygotene region and univalent chromosomes at diakinesis , could indicate pairing , synapsis , and/or recombination defects in these mutants [57] . Spermatogenesis in 100% of ekl-1 and drh-3 mutants ( males and hermaphrodites ) was visibly abnormal in a manner that we did not observe in ego-1 or csr-1 mutants ( Figure 5D and 5I versus Figure 5B and 5G , Table 3 ) . ekl-1 and drh-3 sperm nuclei were abnormally large and variably sized , as if chromatin condensation or chromosome segregation was impaired . In addition , male sperm did not become tightly packed in the vas deferens ( as they do in wild type ) . Analysis of double mutant phenotypes suggested a complex relationship among ego-1 , csr-1 , ekl-1 , and drh-3 with respect to germline development . ( See Materials and Methods for generation of double mutants . ) Several aspects of the phenotype were more severe in at least a subset of double mutants . For example , the frequency of animals with univalents at diakinesis was higher among ekl-1 drh-3 , ego-1 drh-3 , and ekl-1 ego-1 double mutants than in ekl-1 , ego-1 , and drh-3 single mutants reflecting either a synergistic or additive effect ( Table 3 ) . Interestingly , although the frequency of animals showing the phenotype increased , the degree of asynapsis in individual nuclei was not significantly higher in double mutants compared with single mutants ( Table 3 ) . In contrast , the univalent frequency in ego-1;csr-1 double mutants was similar to that observed in csr-1 and ego-1 single mutants ( Table 3 ) . We observed the sperm condensation defect in ekl-1 ego-1 and ego-1 drh-3 double mutants , indicating it is epistatic to the more normal sperm morphology present in ego-1 single mutants ( Figure 5E and 5F' ) . Interestingly , we observed a similar , although less severe , condensation defect in a subset of ego-1;csr-1 double mutants ( Table 3 ) . The implications of these double mutant phenotypes are considered in the Discussion . In situ hybridization data compiled by the Nematode Expression Pattern Database ( NEXTDB , http://nematode . lab . nig . ac . jp ) are consistent with our phenotypic observations . The highest concentrations of csr-1 , ekl-1 , and drh-3 transcripts were detected in the gonad and in early embryos , suggesting major functions in the germ line and early embryo . Similarly , ego-1 mRNA is highly enriched in the germ line [37] and the NEXTDB observed ego-1 transcripts in the gonad and early embryo . The severity of the oogenesis defect in these mutants precludes our analysis of embryonic phenotypes . However , RNAi-based surveys of gene function have reported embryonic defects associated with weak knockdown of all four genes [55]–[56] , [58]–[63] . The presence of univalent chromosomes in csr-1 , ekl-1 , and drh-3 diakinesis nuclei was particularly relevant to the H3K9me2 defect . In C . elegans , univalents can result from defective homolog pairing , synapsis , and/or double-strand break ( DSB ) formation [64] , [65] . Both pairing and synapsis have been implicated as important in the process by which meiotic silencing is triggered , whereas DSB formation/repair has not: H3K9me2 enrichment is observed on autosomes in XO mutants with pairing and/or synapsis defects , but not in mutants defective only in double-strand break formation ( A . Fedotov and W . Kelly , manuscript in preparation ) . Therefore , we considered that autosomal H3K9me2 levels might be elevated in csr-1 , ekl-1 , and drh-3 mutants due to ( i ) mis-targeting of the chromatin-modifying machinery to inappropriate sites or ( ii ) appropriate targeting to autosomal regions due to a meiotic pairing and/or synapsis defect . Consequently , we decided to evaluate pairing and synapsis in these mutants . We evaluated homolog pairing using fluorescent in situ hybridization ( FISH ) to visualize the 5S ribosomal RNA gene cluster located on LGV ( see Materials and Methods ) . We detected a minor pairing defect in drh-3 and ekl-1 mutants ( Text S1 , Table S1 , Table S2 , Table S3 ) . However , the frequency of nuclei where chromosome V was unpaired was much lower than the frequency of nuclei with ectopic H3K9me2 ( Text S1 , Table S1 , Table S2 , Table S3 ) . We concluded that H3K9me2 must have accumulated on paired chromosomes in these mutants . We investigated synaptonemal complex integrity by co-labeling two proteins involved in synapsis , HIM-3 and SYP-1 [66]–[68] ( see Materials and Methods ) . Our data did not reveal a defect in synapsis in mutant males ( Figure S2 ) or hermaphrodites ( Figure S3 , Figure S4 ) . See Text S1 for further details . To better address the relationship between pairing and H3K9me2 accumulation , we performed simultaneous LGV FISH and H3K9me2 immunolabeling on drh-3 males . drh-3 was chosen because it has the strongest pairing defect of the three mutants examined ( Table S1 , Table S2 ) . We observed nuclei where elevated H3K9me2 and a single LGV FISH signal coincided , consistent with elevated H3K9me2 on the paired LGVs ( Figure 6A , 6C ) . We also observed nuclei where H3K9me2 accumulated at sites distinct from one or both of two FISH signals , consistent with low H3K9me2 on unpaired chromosome Vs ( Figure 6B ) . Given these results and the data presented in Table 2 , Table S1 , and Text S1 , we conclude that the H3K9me2 distribution in drh-3 , ekl-1 , and csr-1 pachytene nuclei is likely to be independent of the ( mild ) pairing defect in these mutants . We also evaluated whether H3K9me2 accumulates at synapsed chromatin in csr-1 , ekl-1 , and drh-3 mutant males . To do so , we co-labeled H3K9me2 and SYP-1 ( see Materials and Methods ) . In wild type males , we consistently observed a single chromosomal region that failed to accumulate SYP-1 and was highly enriched for H3K9me2 ( Figure 7 ) . In csr-1 , ekl-1 , and drh-3 mutant males , we typically observed a single SYP-1 ( - ) region that accumulated a variable level of H3K9me2 . In addition , we observed H3K9me2 at other chromosomal regions that contained SYP-1 ( Figure 7 ) . At the limit of sensitivity of our data , these results are consistent with the hypothesis that elevated H3K9me2 accumulation occurs at synapsed regions in these germ cells . Our previous work indicated that the loss of EGO-1 activity prevents H3K9me2 accumulation on unpaired chromatin [9] . Here , we tested whether EGO-1 activity is required for ectopic H3K9me2 accumulation by determining the H3K9me2 distribution in ego-1;csr-1 , ego-1 drh-3 , and ekl-1 ego-1 double mutant males . The H3K9me2 distribution in all three double mutants resembled the distribution we had observed in csr-1 , ekl-1 , and drh-3 single mutant males ( Figure 2F , 2G , 2H ) . Therefore , EGO-1 activity is not necessary for ectopic H3K9me2 to accumulate on autosomes . Moreover , since EGO-1 is required for the H3K9me2 accumulation diagnostic of meiotic silencing , this result strengthens our conclusion that the autosomal H3K9me2 in csr-1 , ekl-1 , and drh-3 males is mis-targeted to paired chromatin . We also note that , in double mutants such as ekl-1 drh-3 , the H3K9me2 distribution resembled that observed in the two corresponding single mutants ( Figure 2I , and data not shown ) . We sought to determine whether the pattern of elevated autosomal H3K9me2 in csr-1 , ekl-1 , and drh-3 mutants depended on HIM-17 activity . HIM-17 is a chromatin-associated protein reported to be required for normal accumulation of H3K9me2 per se in both XX and XO germ lines [69] . We constructed him-17;csr-1 , ekl-1;him-17 , and drh-3;him-17 double mutants and found that they have severe germline defects similar to those previously described for ego-1;him-17 double mutants [9] ( data not shown ) . Unfortunately , nuclear morphology was abnormal throughout the severely impaired germ line , prohibiting meaningful interpretation of the H3K9me2 labeling pattern .
Biochemical analysis of CSR-1 and DRH-3 has provided direct insight into their functions . AGO proteins are known to localize to target RNAs via interaction with a siRNA “guide” molecule [38] . Using in vitro assays , Aoki et al . [46] demonstrated that CSR-1 has Slicer endonuclease activity and binds to secondary ( 2° ) siRNAs that are produced as a consequence of RdRP activity on target mRNA during the RNAi process . DRH-3 activity promotes the formation of diverse classes of small RNAs [34] , [35] . In vitro , DRH-3 interacts physically with the somatic RdRP , RRF-1 , and is required for 2° siRNA production [46] . By analogy , we hypothesize that DRH-3 may promote EGO-1 activity in the germ line . Although little is known about the biochemical function of EKL-1 , we hypothesize that it may bind methylated proteins via its Tudor domains [70] . Tudor domains from several mammalian proteins have been shown to bind methylated peptides in vitro , specifically peptides corresponding to histone H3 tails methylated at either lysine 4 or 9 and histone H4 tail methylated at lysine 20 [71] . Similarly , the DNA repair function of Saccharomyces cerevisiae RAD9 apparently requires binding to methylated H3 lysine 79 via its Tudor domain [72] . We consider two general models for how an EGO-1/CSR-1/EKL-1/DRH-3 pathway might function in meiotic chromatin regulation . One model is that these factors directly target the chromatin-modifying machinery to unpaired regions , perhaps via a mechanism similar to that which directs H3K9me2 to centromeric repeats in S . pombe . There is increasing evidence that siRNAs and other small RNAs participate in transcriptional silencing in many organisms , although thus far the mechanisms are poorly understood [19] . Ultimately , this pathway may establish a self-amplifying loop to attract histone methyltransferase ( HMTase ) to unpaired chromatin and/or exclude HMTase activity from paired chromatin . We speculate that chromatin-associated RNA pol II transcripts [73]–[76] act as templates for EGO-1 RdRP activity and are essential for establishment of the self-amplifying loop . One possible scenario is that all or a subset of these proteins are initially recruited to unpaired chromatin via interaction with a factor that is lost or masked by successful pairing and/or synapsis . As an amplification loop is established , the HMTase is preferentially recruited to unpaired regions . In the absence of EGO-1 activity , the HMTase may be recruited to specific sites but be unable to methylate chromatin effectively . In the absence of CSR-1 , EKL-1 , or DRH-3 activity , the HMTase may not be properly recruited or retained and therefore be free to modify chromatin in an unregulated manner , perhaps through enhanced interaction with another competing complex . As an alternative model , EGO-1 , CSR-1 , EKL-1 , and DRH-3 may influence H3K9me2 by participating in post-transcriptional and/or transcriptional silencing mechanisms that ultimately regulate the expression of genes whose products discriminate between paired and unpaired chromatin . This model is complicated by the fact that we would expect direct targets of such a hypothetical silencing mechanism to be up-regulated upon loss of silencing activity . Therefore , we propose that loss of silencing activity would indirectly down-regulate the discriminatory factors , perhaps by allowing over-expression of a negative regulator . EGO-1 might regulate a different constellation of genes than do CSR-1 , EKL-1 , and DRH-3 , resulting in the different H3K9me2 patterns in ego-1 versus csr-1 , drh-3 , and ekl-1 mutants . Identification of specific sites on unpaired chromatin that are targeted for H3K9me2 accumulation , and investigation of whether EGO-1 , CSR-1 , EKL-1 , and/or DRH-3 associate with those sites will help to distinguish between these alternative models . Our phenotypic analysis of CSR-1 , EKL-1 , and DRH-3 suggests that they participate in a complex regulatory network to promote development of the germ line . Their activity is critical for maintenance of germline proliferation , meiotic progression , spermatogenesis , and oogenesis . Previous reports in the literature have indicated that EGO-1 , EKL-1 , DRH-3 , and CSR-1 may promote other aspects of development , including embryonic viability and proper chromosome segregation [34] , [42] , [58] . Most strikingly , Rocheleau et al . [63] demonstrated that reduction in function of each of these four genes enhanced the lethality of a weak ksr-1 ( kinase suppressor of ras ) mutation . ksr-1 lethality results from a defect in excretory duct formation due to impaired Ras signaling [77] . Rocheleau et al . proposed that EGO-1 , CSR-1 , DRH-3 , and EKL-1 may affect the development of the excretory duct cell by promoting the biogenesis/activity of a set of germline small RNAs whose activity ultimately regulates expression of factors important for the KSR-1/KSR-2 Ras-ERK signaling pathway . We have now demonstrated the importance of this non-coding RNA pathway in meiotic chromatin regulation and other aspects of germline development . Our genetic data suggest that EGO-1 , CSR-1 , EKL-1 , and DRH-3 participate in a complex regulatory network . Based on strict epistasis criteria , EGO-1 and CSR-1 act in a common genetic pathway to promote bivalent stability at diakinesis , and this pathway works in parallel with DRH-3 and EKL-1 pathways . Given what is known about the biochemical functions of these proteins , perhaps the simplest way to think about these genetic pathways is that they may involve distinct classes of small RNAs ( e . g . , [35] , [45] , [78] ) . The EGO-1/CSR-1/EKL-1/DRH-3 pathway may be responsible for biogenesis/function of one class of small RNA , while other classes of small RNA may require EKl-1 and/or DRH-3 , but rely on a different RdRP and/or AGO protein in place of EGO-1 and CSR-1 . Indeed , DRH-3 is required for production of many classes of small RNAs , while individual RdRPs function in biogenesis of a subset of such RNAs [34] , [35] . Analysis of sperm nuclear morphological detects also suggested a complex pattern of regulation by multiple small RNA-mediated pathways . In this case , the most important pathway ( s ) require ( s ) DRH-3 and EKL-1 activity while EGO-1 and CSR-1 activity appear to play only a minor role in this process . Hence , analysis of mutant phenotypes can provide insight into the relationships among different small RNA-mediated pathways .
C . elegans strains were cultured using standard methods as described [79] . C . elegans var Bristol ( N2 ) is the wild type parent strain of all the mutants used in this study . The following mutations , chromosomal deficiencies , duplications , and reciprocal translocations were used: LG ( linkage group ) I: C04F12 . 1 tm1637 , drh-3 ( tm1217 ) , drh-3 ( om55 ) ( this report ) , ego-1 ( om84 ) , ekl-1 ( om56 , om83 ) ( this report ) , F55A12 . 1 ok1078 , R06C7 . 1 ok1074 , ppw-1 ( pk1425 ) , ppw-2 ( tm1120 ) , prg-1 ( tm872 ) , sago-2 ( tm894 ) , sin-3 ( tm1276 ) , T23D8 . 7 tm1163 , unc-13 ( e51 ) , unc-15 ( e73 ) , unc-55 ( e402 ) , ozDf5 , nDf25; LG II: alg-2 ( ok304 ) , C06A1 . 4 tm887 , F58G1 . 1 tm1019 , Y49F6A . 1 tm1127 , ZK1248 . 7 tm1135; LG III: C16C10 . 3 tm1200 , tag-76 ( ok1041 ) , unc-32 ( e189 ) , zfp-1 ( ok554 ) , sDf121 , sDp3 ( III;f ) , hT2[bli-4 ( e937 ) let- ? ( q782 ) qIs48] ( I , III ) ; LG IV: csr-1 ( tm892 ) , drh-1 ( tm1329 ) , drh-2 ( tm728 ) , gfl-1 ( gk321 ) , him-8 ( e1489 ) , him-17 ( e2806 , ok424 ) , M03D4 . 6 tm1144 , prg-2 ( tm1094 ) , T22B3 . 2 tm1155 , nT1[qIs51] ( IV , V ) ; LG V: ergo-1 ( tm1860 ) , sago-1 ( tm1195 ) , T22H9 . 3 tm1186 , ZK218 . 8 tm1324; LG X: R04A9 . 2 tm1116 . The tm , ok , and gk alleles are deletions and therefore likely to be null or extreme loss-of-function . ego-1 ( om84 ) is a protein null [54] . ekl-1 ( om83 ) is a deletion allele ( this report ) . An integrated transgenic array , ccIs4251[myo-3::Ngfp-lacZ+myo-3::Mtgfp] , was used as an LGI marker . Information on specific genes and alleles can be found at Wormbase ( http://www . wormbase . org ) unless otherwise noted . Multiple mutant strains were generated using standard genetic strategies . PCR analysis was routinely used to confirm the presence of deletion mutations . The following strategy was used to build cis-doubles . To generate ego-1 ( om84 ) drh-3 ( tm1217 ) double mutants , we generated an ego-1 ( om84 ) unc-55 ( e402 ) /unc-13 ( e51 ) drh-3 ( tm1217 ) male/hermaphrodite strain and mated non-Unc males with unc-13 ( e51 ) unc-55 ( e402 ) hermaphrodites . Non-Unc-13 , non-Unc-55 progeny were recovered; PCR analysis was used to identify the lines carrying both ego-1 ( om84 ) and drh-3 ( tm1217 ) deletions ( i . e . , ego-1 drh-3/unc13 unc-55 ) . The ego-1 ( om84 ) drh-3 ( tm1217 ) chromosome was then balanced with hT2[bli-4 ( e937 ) let- ? ( q782 ) qIs48] . ekl-1 ( om83 ) ego-1 ( om84 ) and ekl-1 ( om83 ) drh-3 ( tm1217 ) double mutants were constructed by the same general strategy ( using different marker mutations in one case ) . RNAi was done by the feeding method as described [80] except that double strand RNA production was sometimes induced by 0 . 2% lactose rather than 1 mM IPTG . Multiple L4 N2 and glp-1 ( bn18 ) hermaphrodites were placed onto each bacterial “feeding” strain at 25°C and 20°C , respectively . Adult F1 progeny were scored for sterility using a dissecting microscope . Steriles were examined at high magnification as described [81] to determine whether they had a Glp-1 sterile phenotype ( premature meiotic entry of all germ cells ) . ego mutations om55 , om56 , and om83 were recovered in genetic screens for enhancers of glp-1 ( bn18ts ) as previously described [36] using either ethylmethane sulfonate ( EMS ) ( om55 , om56 ) or trimethylpsoralen/UV irradiation ( om83 ) as the mutagen . Three-factor and deletion mapping placed the three mutations on the right arm of LGI . Based on complementation tests , om56 and om83 comprise a single complementation group while om55 comprises another . Three-factor mapping placed om56 and om83 between dpy-5 and unc-13 . We subsequently mapped om56 relative to single nucleotide polymorphisms ( SNPs ) , ultimately localizing it between SNPs at nucleotide position ∼7050 K and 7120 K . This interval was predicted to encode 19 genes , including ekl-1 ( see www . wormbase . org ) . DNA from the ekl-1 gene region was amplified from ego ( om83 ) and ego ( om56 ) mutants and sequenced . In ego ( om83 ) animals , the ekl-1 open reading frame ( ORF ) contained a 110 nucleotide deletion and concomitant single nucleotide insertion ( at the deletion site ) ; the net 109 nucleotide deletion is predicted to shift the ORF , resulting in production of a truncated product comprising 314 amino acids ( Figure 1A ) . In ego ( om56 ) mutants , the ekl-1 ORF contained a single nucleotide substitution , inserting a stop codon for tryptophan 319 ( Figure 1A ) . Primers used to sequence the ekl-1 region were ( 5′→3′ ) : ekl1-1r cgattgcgcgacgaatctgatc; ekl1-2f ggaagttgttctctccactg; ekl1-2r ccgaataagcagtaaactaagg; ekll-3f cactggagagtggcaaagag; ekl1-3r ctccgcacacttgcattgc; ekl1-0r cctgaatagcttgccacgg; ekl1-4f cgttcatttccaacagattg . Three-factor mapping placed om55 within an ∼244 kb region between gld-1 and unc-55 that includes drh-3 . om55 failed to complement drh-3 ( tm1217 ) for fertility . DNA from the drh-3 region was amplified from om55 animals and sequenced using standard methods . A single substitution was detected in the drh-3 open reading frame ( ORF ) ; this change is predicted to replace glycine with glutamic acid at residue 133 , leading to production of truncated product ( Figure 1B ) . We conclude that om55 is an allele of drh-3 . Primers used to sequence the drh-3 region were: OM5501F gcattgagatcgaaaggcag; OM5501R catgttgttcaaactggcgc; drh3s1 . 1f cagagaagattctcggaatg; drh3s1 . 1r catcacttcgtcagcaattc; drh3s1 . 2f ggtcgaagatttgctaaccg; drh3s1 . 2r cggttagcaaatcttcgacc; drh3s2 . 1f cgaacatcccaaggaaagcc; drh3s2 . 1r ccaacatgctcattgagctc; drh3s2 . 2f cgcattgatcaacgctccac; drh3s2 . 2r caagcatagttcgacagctg; drh3s2 . 3f ggtctgacagcttcattgag; drh3s3 . 1f ggtctcgatgttactgcatg; drh3s3 . 1r gcggcaaataggttcctctg; drh3s3 . 2f catggtgttcgatccaagtg; drh-3s3 . 2r gatcgaatgaaaattgctcgg . H3K9me2 single labeling was carried out as described [9] using polyclonal anti-H3K9me2 ( gift of C . D . Allis ) at 1/500 dilution and Alexa488-labeled secondary antibody ( Invitrogen ) at 1∶200 dilution . H3K9me2/SYP-1 double labeling was performed as follows . Gonads were dissected in 8 µL of 0 . 25 mM levamisole/PBS on a poly-lysine treated slide . 8 µL of 6% paraformaldehyde ( PFA ) /2X EGG buffer were added to the dissected tissue and a Super-Frost slide ( Fisher ) immediately placed on top . The slide sandwich was placed on dry ice for 15 minutes , cracked open , and immediately washed with PBST . After a total of 3X 5 min washes in PBST ( 1X PBS/0 . 1% Tween-20 ) , the sample was blocked for 30 minutes in 30% goat serum ( GS ) /PBST . Monoclonal anti-H3K9me2 ( 1∶200 dilution , Abcam1220 ) and polyclonal anti-SYP-1 ( 1∶200 dilution , STD143 gift of A . Villeneuve ) were added . Tissue was incubated at 4°C overnight and then washed 3X 10 min in PBST . Tissue was incubated with Alexa488-conjugated goat anti-rabbit ( 1∶200 dilution , Invitrogen ) and Alexa568-conjugated goat anti-mouse ( 1∶400 dilution , Invitrogen ) secondary antibodies for 2 hours at room temperature and then washed 1X in PBST , 2X in PBS . DAPI was added to the first PBS wash . Images were captured on a Zeiss Axioscope and , in some cases , on a Zeiss LSM 710 Confocal microscope . H3K4me2 and H3K9me2 co-labeling was performed using rabbit anti-H3K4me ( gift of C . D . Allis ) and mouse anti-H3K9me2 ( Abcam 1220 ) . Dissected tissue was fixed for 5 min in 2 . 5% PFA , washed 3X in PBST , blocked >30 min in PBST/GS , and incubated overnight at room temp in primary antibody diluted 1∶200 ( anti-H3K9me2 ) or 1∶250 ( anti-H3K4me2 ) in PBST/GS . Washes and secondary antibody staining was carried out as described above . HIM-3 and SYP-1 co-labeling was performed using a similar protocol , except that dissected gonads were fixed for 5 min in 1% PFA and post-fixed for 1 min with −20°C methanol prior to PBST washes . Rabbit anti-HIM-3 ( gift of M . Zetka ) and guinea pig anti-SYP-1 ( STD 165 , gift of A . Villeneuve ) were each diluted 1/200 . Alexa488-conjugated goat anti-guinea pig ( Invitrogen ) was diluted 1/200 . The 5S rDNA probe was generated by amplification of a 1 kb region of the 5S rDNA locus using published primers [82] . The probe was labeled with DIG-11-dUTP using the DIG-Nick Translation Kit ( Roche Applied Science ) . FISH was carried out as described [8] . A 1∶200 dilution of anti-Digoxigenin-Fluorescein antibody ( Roche Applied Science ) was used for probe detection . Samples were examined using a DRMXA fluorescent microscope ( Leica ) ; the images were acquired using a CCD camera ( Q Imaging ) and processed using SimplePCI ( Hamamutsu Corporation ) software . DAPI staining was used to characterize the germline developmental phenotypes . To avoid variations in germline morphology caused by aging , animals were harvested at a consistent developmental stage ( 24 hours post-L4 stage at 20°C ) . Animals were then dissected to expose the gonad . Fixation and staining were performed as described [83] . Nuclei in mitosis and different stages of meiosis were identified based on nuclear morphology as described [37] , [83] .
|
DNA within a cell's nucleus is packaged together with proteins into a higher order structure called chromatin . In its simplest form , chromatin consists of DNA and a set of proteins called histones , arranged so that the DNA strand is wrapped around histone protein clusters . This basic chromatin structure can be modified in various ways to regulate access to the genetic information encoded in the DNA . Such regulation is critical for cellular function and development of the organism . As cells form gametes , they undergo a specialized type of cell division called meiosis . During meiosis , chromatin is regulated in specific ways to ensure proper development of the embryo . During meiosis in the nematode C . elegans , the chromatin structure of the single male X chromosome depends on an RNA-directed RNA polymerase called EGO-1 . Here , we identify three more regulators of meiotic chromatin , the proteins CSR-1 , EKL-1 , and DRH-3 . Our data suggest that these proteins collaborate with EGO-1 to ensure that paired chromosomes ( autosomes and hermaphrodite X chromosomes ) are regulated correctly and in a manner distinct from the male X chromosome . Our findings suggest that these four proteins participate in a mechanism to ensure proper gene expression for gamete formation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology/germ",
"cells",
"molecular",
"biology/chromatin",
"structure",
"molecular",
"biology/histone",
"modification",
"developmental",
"biology/stem",
"cells",
"genetics",
"and",
"genomics/chromosome",
"biology",
"genetics",
"and",
"genomics/epigenetics",
"developmental",
"biology/developmental",
"molecular",
"mechanisms",
"cell",
"biology/gene",
"expression"
] |
2009
|
Regulation of Heterochromatin Assembly on Unpaired Chromosomes during Caenorhabditis elegans Meiosis by Components of a Small RNA-Mediated Pathway
|
Albendazole ( ABZ ) , a benzimidazole ( BZ ) anthelmintic ( AH ) , is commonly used for treatment of soil-transmitted helminths ( STHs ) . Its regular use increases the possibility that BZ resistance may develop , which , in veterinary nematodes is caused by single nucleotide polymorphisms ( SNPs ) in the β-tubulin gene at positions 200 , 167 or 198 . The relative importance of these SNPs varies among the different parasitic nematodes of animals studied to date , and it is currently unknown whether any of these are influencing BZ efficacy against STHs in humans . We assessed ABZ efficacy and SNP frequencies before and after treatment of Ascaris lumbricoides , Trichuris trichiura and hookworm infections . Studies were performed in Haiti , Kenya , and Panama . Stool samples were examined prior to ABZ treatment and two weeks ( Haiti ) , one week ( Kenya ) and three weeks ( Panama ) after treatment to determine egg reduction rate ( ERR ) . Eggs were genotyped and frequencies of each SNP assessed . In T . trichiura , polymorphism was detected at codon 200 . Following treatment , there was a significant increase , from 3 . 1% to 55 . 3% , of homozygous resistance-type in Haiti , and from 51 . 3% to 67 . 8% in Kenya ( ERRs were 49 . 7% and 10 . 1% , respectively ) . In A . lumbricoides , a SNP at position 167 was identified at high frequency , both before and after treatment , but ABZ efficacy remained high . In hookworms from Kenya we identified the resistance-associated SNP at position 200 at low frequency before and after treatment while ERR values indicated good drug efficacy . Albendazole was effective for A . lumbricoides and hookworms . However , ABZ exerts a selection pressure on the β-tubulin gene at position 200 in T . trichiura , possibly explaining only moderate ABZ efficacy against this parasite . In A . lumbricoides , the codon 167 polymorphism seemed not to affect drug efficacy whilst the polymorphism at codon 200 in hookworms was at such low frequency that conclusions cannot be drawn .
Ascaris lumbricoides ( roundworm ) , Trichuris trichiura ( whipworm ) and Necator americanus/Ancylostoma duodenale ( hookworms ) are the most common species of soil-transmitted helminths infecting humans worldwide . More than a billion people are infected with at least one species and 300 million are estimated to have severe infections with more than one of these parasites [1] . These infections are endemic in tropical and sub-tropical regions of the developing world and are associated with poverty , lack of clean water , and poor sanitation [2] . School-age children are the most at risk of infection with STHs and early childhood infections contribute significantly to debilitation [3] . Infected children can be malnourished and experience stunting growth and intellectual retardation , with cognitive and educational deficits [1] . Because of all these characteristics and according to estimates by the World Health Organization ( WHO ) [4] , STHs are included in the group of the so-called neglected tropical diseases ( NTDs ) . The main intervention to control STH infections at a community level is based on periodic mass drug administration ( MDA ) of the benzimidazole ( BZ ) anthelmintic ( AH ) drugs , albendazole ( ABZ ) or mebendazole ( MBZ ) [5] , that reduce the prevalence and intensity of infections [6] . However large-scale chemotherapy programmes with these drugs have the potential to exert selection pressures on the causing parasites , which may favour the development of drug resistance . Recently , expansion of MDA programmes for STHs have highlighted the need to monitor for the possibility that resistance may develop [7] , [8] . This development would have important adverse consequences on the benefits provided by deworming programmes [9] , [10] . BZ resistance in other parasitic nematodes is caused by a single nucleotide polymorphism ( SNP ) in the β-tubulin gene at codon positions 200 ( T→A ) , 167 ( T→A ) , or 198 ( A→C ) [11]–[13] . The frequency and relative importance of these different SNPs varies among the nematode species studied to date [13]–[15] . Molecular markers have been developed to identify SNPs in A . lumbricoides , T . trichiura and hookworms and wild-type and mutant-type control plasmids have been constructed to obtain the genotype profiles of “susceptible-type” parasites ( which do not have mutations at position 200 , 167 and 198 ) and “mutant-type” parasites ( that contain mutations in one of these three positions ) [16] . The codon 200 polymorphism has been identified in T . trichiura populations collected from untreated subjects in Kenya and from treated subjects in Panama [17] , and in hookworms collected in Haiti in an area periodically treated with ABZ [16] . In the present report , our aim was to investigate the field efficacy of ABZ against STH infections in countries where polymorphism in β-tubulin had previously been identified , and to assess the frequency of each SNP prior to , and after ABZ treatment within each country and for each of the three main nematode species .
Three cross-sectional studies were carried out between 2008 and 2010 in three countries located in different geographical areas , including Haiti in the Caribbean , Kenya in East Africa and Panama in Central America . These studies were integrated into the following control and evaluation programmes of ABZ use: a national health programme to fight lymphatic filariasis ( LF ) and intestinal worms in Haiti ( in collaboration with the Hôpital Ste . Croix and the Centers for Disease Control ( CDC ) ) ; school health and nutrition programmes in Kenya , and health and nutrition programmes in Panama . Thus , each study included a treatment with ABZ , stool examinations , and genotyping of the β-tubulin gene in eggs collected before and after ABZ treatment to assess the drug efficacy against STHs and to examine at each time point the frequency of possible SNPs associated with ABZ resistance in nematodes of veterinary importance . The study designs in Kenya , Panama and Haiti ( Figure 1 ) were different because each study was part of a separate national and local MDA programme . Thus , different protocols were applied rather than a purposely designed multi-study site single protocol . The study in Haiti included stool collections prior to , and after a drug treatment given in 2009 . In Haiti , the study sites were located in the West and Southeast Haitian departments known to be naive for MDA with ABZ . Individuals from five endemic communities who reached the inclusion criterion ( older than two years old ) were randomly selected . All potential participants were informed by a trained community leader of the purpose and methods of the study and gave their oral consent ( in the case of children , consent was obtained from a parent ) . A total of 353 stool samples were collected and analyzed prior to ABZ treatment . Treatment was then distributed to all people of each community ( 400 mg ABZ and 6 mg/kg diethylcarbamazine ( DEC ) ) . ABZ was supplied as a donation from GlaxoSmithKline ( GSK ) . Participants in the study were not observed during the treatment administration . However , the compliance to treatment was evaluated post-treatment by a questionnaire and relied on self-reported information of each participant , and on pre and post-treatment egg counts . Samples from participants who were not treated with ABZ were not included in the analysis . Follow-up faecal samples ( n = 317 ) were collected two weeks after the drug treatment . School-aged children from two schools located in Kwale District were enrolled in the study . Although the schools were selected because at the time of the study they were not involved in any other STH deworming programmes , pupils had received ABZ and DEC six month prior to our study for LF treatment . Stool samples were collected prior to ABZ treatment in both schools ( n = 128 ) and then all children received 400 mg ABZ under the supervision of the school teachers . The drug was provided by the Kenyan Ministry of Health and was manufactured by GSK . Seven days later , a follow-up collection was undertaken ( n = 92 ) . In one of the schools , the stool collections before and after ABZ treatment were done over two consecutive days and the results averaged . The field study was conducted in the region of Comarca Ngäbe-Buglé [18] . Stool samples were collected from pre-school children at different time points over a period of 16 months from July 2008 to October 2009 . Two treatments with ABZ , as a suspension ( 200 mg: one to two years of age; 400 mg: three to five years of age ) were distributed , once in 2008 and the second . nine months later in 2009 [19] . The drug was provided by the Panamanian Ministry of Health . In the present study , we only analyzed the faecal samples collected prior to treatment and three weeks after treatment in 2009 since the baseline prevalence for STHs was very low in the 2008 samples . Prior to this second ABZ treatment , stool samples were collected from 270 pre-school aged children and follow-up samples were available from 222 children . Children were observed while received the ABZ treatment , and only samples from treated children were included in the analysis . In the three studies , all instances of consent were informed . Ethical approval for Haiti was obtained from the Institutional Review Board of the Centers for Diseases Control and Prevention , Atlanta , Georgia , US ( Dr . Patrick Lammie ) , and the Ethics Committee of the Hôpital Ste Croix , Haiti and included the collection of stool samples , examination of stool samples for helminth eggs and DNA analysis of helminth eggs . Informed consent was obtained from all adult participants and from parents or legal guardians of all minors . A parent or legal guardian gave consent in every case of child participation . Based on past experience , it was likely that some people in the communities would not be able to read . A waiver of written informed consent on the basis that the research presented no more than minimal risk of harm to the subjects and involved no procedures for which written consent is normally required outside the research context in this setting , was requested and approved . The use of oral consent was previously approved by the IRB . Subjects were offered a written copy of the IRB approved consent form . The contents of the approved consent form were explained to each household , following which verbal consent was obtained . The reader of the consent form and a witness signed a copy of the form to indicate the subject's agreement . The study in Kenya was approved by the Kenya Medical Research Institute ( KEMRI ) Ethical Review Committee . The informed consent process , which was approved by the KEMRI IRB specifically stated that the study was included in the national programme on surveillance of disease control and followed established government procedure . The school heads organized meetings with their parent teacher association to obtain agreement for the project . An information sheet was provided . It was emphasized that the participation in the study by children was voluntary and that they may refuse to participate . All children were treated with ABZ and praziquantel in the study . Finally , all samples were anonymised . As part of a national control programme , informed consent was not documented for each individual . The content of the study was verbally explained in detail to parents/guardians , teachers and children from each school . It was done orally as it was necessary to have this explained in local languages . The use of oral consent was previously approved by the IRB . A parent or legal guardian gave oral informed consent in every case of child participation . The study in Panama was approved by the McGill University Review Board in Canada , the Instituto Conmemorativo de Gorgas and local indigenous leaders in Panama . Written informed consent was obtained from primary caregivers for their own participation as well as that of their children . They were provided with an explanation of the study , its significance , and of participant requirements and rights . They were given an opportunity to ask questions in Spanish and in the local language . A parent or legal guardian gave consent in every case of child participation . In all studies and for each intervention ( before and after ABZ treatment ) , labelled containers were distributed to each participant and collected the following morning from the community leader in Haiti , schools in Kenya , and each participant's home in Panama . Three diagnostic techniques: McMaster , Kato-Katz , and FLOTAC were used to identify STH eggs and determine the number of egg per gram ( epg ) in the faecal material collected before and after ABZ treatment . In Haiti we used a modified McMaster technique on each collected sample . One gram of faeces was suspended with water and the solution was stirred until it was completely broken apart . The mixture was poured through surgical gauze into a centrifuge tube . After centrifugation for 10 min at 15 , 000 rpm , the supernatant was poured off and the tube containing the sediment was filled with saturated sucrose solution and then gently stirred . After 10 min , an aliquot of the flotation fluid from the upper surface of the solution was transferred into each compartment of a McMaster chamber . The eggs were counted in both chambers using a low power objective ( ×10 ) . The number of epg of faeces was obtained by multiplying the total number of eggs counted in the two chambers by 50 [20] . In Kenya , the McMaster ( as described above ) and Kato-Katz techniques [21] were used on samples from one school and Kato-Katz alone was used in the other school . For Kato-Katz , the number of eggs counted was multiplied by 24 to obtain the epg [21] . In Panama , the identification of eggs and the assessment of epg were performed using Kato-Katz [21] and FLOTAC [22] , [23] , as previously described [19] . One of the primary objectives of the study was to assess the frequency of SNPs associated with resistance to ABZ ( seen in the veterinary nematode Haemonchus contortus ) in the β-tubulin gene of STHs collected from untreated and treated subjects . Thus , from the three studies , eggs from positive subjects were recovered using a saturated sucrose solution with centrifugation , and recovered eggs were preserved in 70% alcohol until use for molecular analysis . The treatment efficacy on A . lumbricoides , T . trichiura and hookworms was evaluated by the egg reduction rate ( ERR ) for each diagnostic method applied in each country: McMaster ( in Haiti , and Kenya ) , Kato-Katz ( In Kenya and Panama ) and FLOTAC ( in Panama ) . The ERR was calculated , at the group level , as the ratio of the difference between the arithmetic mean of the pre- and post-treatment faecal egg count ( FEC ) to the pre-treatment arithmetic mean , expressed as a percentage , i . e . ignoring individual variability [25] . The negative individuals at baseline were still sampled at the post-treatment collection and the resulting data were included for the calculation of ERR . Uninfected subjects were included in the mean of the FEC . Confidence intervals of each ERR estimate were determined using a bootstrap resampling method ( with replacement ) over 10 , 000 replicates in R ( version 2 . 15 . 0 , Vienna Austria , http://www . R-project . org ) . Genotype frequencies of SNPs at positions 167 , 198 and 200 in A . lumbricoides , T . trichiura and hookworms obtained at the pre-treatment collections were compared with the genotype frequencies of the same SNPs obtained at the post-treatment collections using Fisher's exact test within GraphPad Prism ( GraphPad software , San Diego , CA , USA ) . Deviation from Hardy-Weinberg equilibrium ( HWE ) was analyzed for the β-tubulin gene at position 200 in T . trichiura using Arlequin version 3 . 1 software [26] , where the p-value was calculated based on the Markov-chain method [27] . Deviations from the HWE were not determined for A . lumbricoides or hookworm for reasons explained below . When a departure from HWE was observed in T . trichiura , we estimated the maximum likelihood frequency of a null allele at position 200 . This estimate was calculated using an Expectation-Maximization Algorithm of Dempster and colleagues [28] ( EM Algorithm , http://132 . 206 . 161 . 123/em . html ) .
In T . trichiura , the three codon positions 167 , 198 , and 200 were found to be polymorphic in samples collected from untreated and treated subjects in Haiti , Kenya , and Panama . In Haiti we analyzed 65 individual T . trichiura eggs from 30 untreated subjects and 38 from 14 treated subjects . We recorded 11% and 47% experimental failure ( includes DNA extraction , PCR amplification and Pyrosequencing ) in pre- and post-treatment samples , respectively . Before treatment the T→A SNP at codon position 200 ( SNP200 ) was identified at low frequency; 3 . 1% of individual eggs genotyped were homozygous resistance-type ( AA ) and 23 . 1% were heterozygous ( TA ) . After treatment , there was a significant increase in the frequency of the homozygous resistance-type , from 3 . 1% to 55 . 3% ( p<0 . 001 ) , and a statistically significant decrease of the homozygous susceptible-type , from 75 . 4% to 21 . 1% ( p<0 . 0001 ) ( Figure 2A ) . The A→C SNP at codon position 198 was also found and showed a statistically significant change in frequency following treatment . However , the changes at codon 198 were less pronounced than at codon 200 . After treatment , there was a significant increase of homozygous resistant-type from 3 . 1% to 13 . 2% ( p<0 . 001 ) , and a significant decrease of homozygous susceptible-type from 73 . 8% to 63 . 2% ( Figure 3 ) . In Kenya , 40 individual T . trichiura eggs from 20 untreated subjects and 90 eggs from 31 treated subjects were genotyped . We recorded 30% and 5% experimental failure in pre- and post-treatment samples , respectively . Only the codon 200 SNP was polymorphic . The same trend observed in Haiti was seen with a statistically significant increase , from 51 . 3% to 68 . 5% ( p = 0 . 019 ) of homozygous resistance-type , and a significant decrease , from 48 . 6% to 21 . 4% ( p = 0 . 019 ) of homozygous susceptible-type after treatment ( Figure 2B ) . In Panama we genotyped 19 “pre-treatment” T . trichiura eggs from 10 subjects , which were collected 9 months after an earlier treatment , and 49 post-treatment eggs from 21 subjects collected 3 weeks after this second ABZ treatment . We observed homozygous resistance-type ( 78 . 9% ) and homozygous susceptible-type ( 21 . 1% ) , at codon 167 , in the pre-treatment collection . For codons 198 and 200 , 84% of the pre-treatment T . trichiura egg samples failed the PCR amplification and therefore it was not possible to assess the genotype frequencies for these positions . At the post-treatment collection , the codon 167 polymorphism was still present in the treatment survivors as homozygote resistance-type in 16 . 3% of individual eggs genotyped . For codons 198 and 200 , we observed a predominance of homozygous susceptible-type genotypes , 97 . 6% and 88 . 1% respectively; and a low frequency of heterozygous , 2 . 4% ( for each position ) and homozygous resistance-type , 9 . 5% ( for codon 200 ) . In A . lumbricoides , the codon position 167 of the β-tubulin gene was polymorphic in parasites collected from untreated and treated subjects in Haiti , Kenya and Panama , whereas the codon positions 198 and 200 were monomorphic . The SNP at position 167 identified was confirmed by conventional Sanger sequencing and real time PCR ( data not shown ) . In Haiti , we genotyped 37 individual A . lumbricoides eggs from 13 untreated subjects and five eggs from three treated subjects . We recorded 49% and 28% experimental failure in pre- and post-treatment samples . Prior to treatment , homozygous resistance-type ( 40% ) and heterozygous ( 60% ) , at codon 167 , were present in the population; however , only heterozygotes were detected after treatment . In Kenya , 22 individual A . lumbricoides eggs from 6 untreated subjects and 19 eggs from 4 treated subjects were genotyped . We recorded 15% and 17% experimental failure in pre- and post-treatment samples , respectively . The predominant genotype frequency identified was the homozygous resistance-type ( 72 . 7% ) at codon 167 . After treatment , there was no significant difference in the homozygous resistance-type frequency; however , as observed in A . lumbricoides collected in Haiti , at codon 167 there was a statistically significant increase of heterozygotes from 4 . 5% to 21 . 1% ( p<0 . 001 ) , and also a significant decrease of homozygous susceptible-type from 22 . 7% to 5 . 3% ( p<0 . 001 ) . In Panama , 53 individual eggs were genotyped from 28 untreated subjects and 70 eggs from 20 treated subjects . We recorded 57% of experimental failure only in pre-treatment samples . As seen previously in Haiti and Kenya , the most abundant genotype at codon 167 was homozygous resistance-type ( 97 . 7% ) . In this population the lowest genotype frequency was identified as homozygous susceptible-type ( 2 . 3% ) . After treatment , the percentage of both genotypes did not change significantly ( 96 . 7% and 3 . 2% , respectively ) ( Table 1 ) . In hookworms , the codons 167 and 198 of the β-tubulin gene were monomorphic in all samples genotyped from Haiti , Kenya and Panama . Codon 200 polymorphism ( TAC ) was detected in 2 eggs collected in Kenya . In Kenya , 86 individual eggs from 28 untreated subjects and 127 eggs from 34 treated subjects were genotyped . We recorded 19% and 4% experimental failure in pre- and post-treatment samples , respectively . In the pre-treatment collection we identified homozygous resistance-type at low frequency ( 2 . 3% ) and a predominance of homozygous susceptible-type ( 97 . 7% ) . After treatment the frequencies did not change significantly . In Haiti , we examined 84 hookworm eggs from 31 untreated subjects and 14 from five treated subjects and we did not identify any polymorphism at the SNP sites of interest . We recorded 19% and 63% of experimental failure for the samples from the pre- and post-treatment , respectively . In Panama , all 23 eggs analyzed from nine untreated subjects and 59 from 29 treated subjects were homozygous susceptible-type for all three positions . We recorded 71% and 24% of experimental failure for the samples from the pre- and post-treatment , respectively . The arithmetic means of the faecal egg count ( FEC ) per gram are presented in Table 2 . The standard error of the mean obtained shows a high variability of the FEC in the treated and untreated populations . The ERR estimates calculated for A . lumbricoides , T . trichiura and hookworms for each diagnostic test applied in Haiti , Kenya and Panama are summarized in Table 2 . The ERR from the same country estimated using two different diagnostic methods are not directly comparable as the number of samples tested ( and therefore the hosts making up the ERR ) were different . A direct comparison of the different diagnostic methods per se is beyond the scope of this paper and has been previously discussed elsewhere [29] , [30] . In Haiti where only McMaster was applied , the ERR for A . lumbricoides was the highest ( 99 . 9% ( 95% CI 99 . 5–100 . 0 ) ) followed by hookworms ( 98 . 6% ( 95% CI 96 . 1–99 . 7 ) ) and T . trichiura ( 49 . 7% ( 95% CI 0 . 0–88 . 4 ) ) . In Kenya the ERR estimates differed between the Kato-Katz and McMaster methods . The highest ERR was obtained for hookworms , with Kato-Katz at 89 . 95% ( 95% CI , 0 . 0–96 . 1% ) and McMaster at 96 . 8% ( 95% CI , 92 . 5–99 . 2% ) . This was followed by A . lumbricoides with 97 . 3% ( 95% CI , 0 . 0–100 . 0% ) and 80 . 3% ( 95% CI , 0 . 0–100 . 0% ) , respectively , and finally by T . trichiura with 86 . 8% ( 95% CI , 0 . 0–98 . 7% ) and 10 . 1% ( 95% CI , 0 . 0–78% ) . The ERR estimate based on Kato-Katz was the one considered as the sample sizes available were much higher ( n = 104 and n = 92 at pre- and post-treatment , respectively ) than those for McMaster ( n = 24 and n = 42 at pre- and post-treatment , respectively ) . In Panama , the ERR estimates for FLOTAC were the ones considered as the number of samples analyzed was greater than those counted by Kato-Katz [19] . In Panama , the highest ERR estimate was for A . lumbricoides , at 89 . 8% ( 95% CI , 75 . 8–97 . 3% ) , followed by T . trichiura with 65 . 1% ( 95% CI , 0–89 . 1% ) , and finally by hookworms with 47 . 8% ( 95% CI , 0–89 . 9% ) . Guo's Exact Hardy-Weinberg test [27] showed that there was a significant departure from Hardy-Weinberg expectations recorded in T . trichiura collected in Haiti ( p = 0 . 0366 ) after treatment , and in Kenya before and after treatment ( p<0 . 0001 ) for position 200 of the β-tubulin . This disequilibrium was characterized by a deficiency in the number of heterozygotes ( Table 3 ) . The estimated frequency of a null allele at position 200 showed no evidence ( χ2 = 3 . 69 ) that a null allele was responsible of the paucity of heterozygotes . For positions , 167 and 198 , respectively , polymorphism was either not found , or the differences between the frequencies of heterozygotes pre- and post-treatment were not significant .
Comparable data on pre- and post-treatment SNP frequencies were obtained at the different study sites , despite differences in the study designs between sites . However , in the context of monitoring and surveillance of STH control programmes , it will be important to conduct multiple studies according to standardized multi-centre protocols in order to allow drug efficacies to be compared .
|
The soil-transmitted helminths ( STH ) Ascaris lumbricoides , Trichuris trichiura and the hookworms Ancylostoma duodenale and Necator americanus are endemic in many tropical countries . Regular treatment with albendazole or mebendazole is the major means for controlling STHs . However , repeated treatment with the same class of benzimidazole anthelmintics has caused resistance in veterinary parasites , characterized by mutations at either codon 200 , 167 or 198 in the β-tubulin gene . There is a concern that resistance may develop in human STH . Drug efficacy and mutation frequencies were assessed in T . trichiura , A . lumbricoides and hookworms collected in Haiti , Kenya and Panama prior to and after albendazole treatment . In T . trichiura from Haiti and Kenya , a significant increase of the frequency of the mutation at codon 200 was identified after treatment and drug efficacy was mediocre . Against A . lumbricoides , albendazole efficacy was good , even though the frequency of a mutation at codon 167 was relatively high , suggesting that , in this nematode , the codon 167 polymorphism does not impact efficacy . In hookworms , the mutation at codon 200 was identified , but at low frequencies and the response to albendazole was good . We conclude that monitoring for possible resistance in control programmes should be undertaken .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"soil-transmitted",
"helminths",
"trichuriasis",
"hookworm",
"infection",
"neglected",
"tropical",
"diseases",
"infectious",
"disease",
"control",
"ascariasis",
"parasitic",
"diseases",
"helminth",
"infection"
] |
2013
|
Association between Response to Albendazole Treatment and β-Tubulin Genotype Frequencies in Soil-transmitted Helminths
|
Heterochromatin is the gene-poor , satellite-rich eukaryotic genome compartment that supports many essential cellular processes . The functional diversity of proteins that bind and often epigenetically define heterochromatic DNA sequence reflects the diverse functions supported by this enigmatic genome compartment . Moreover , heterogeneous signatures of selection at chromosomal proteins often mirror the heterogeneity of evolutionary forces that act on heterochromatic DNA . To identify new such surrogates for dissecting heterochromatin function and evolution , we conducted a comprehensive phylogenomic analysis of the Heterochromatin Protein 1 gene family across 40 million years of Drosophila evolution . Our study expands this gene family from 5 genes to at least 26 genes , including several uncharacterized genes in Drosophila melanogaster . The 21 newly defined HP1s introduce unprecedented structural diversity , lineage-restriction , and germline-biased expression patterns into the HP1 family . We find little evidence of positive selection at these HP1 genes in both population genetic and molecular evolution analyses . Instead , we find that dynamic evolution occurs via prolific gene gains and losses . Despite this dynamic gene turnover , the number of HP1 genes is relatively constant across species . We propose that karyotype evolution drives at least some HP1 gene turnover . For example , the loss of the male germline-restricted HP1E in the obscura group coincides with one episode of dramatic karyotypic evolution , including the gain of a neo-Y in this lineage . This expanded compendium of ovary- and testis-restricted HP1 genes revealed by our study , together with correlated gain/loss dynamics and chromosome fission/fusion events , will guide functional analyses of novel roles supported by germline chromatin .
Comparative genomics has revolutionized analysis of eukaryotic genome structure , function , and evolution . Genome sequencing efforts that encompass both closely and distantly related species have led to the identification of protein- and RNA-coding genes as well as noncoding regulatory sequence on an unprecedented scale [1] , [2] . This rapid progress , however , has been restricted largely to the gene-rich euchromatic genome compartment . Heterochromatin—the gene-poor , repeat-rich region found mostly near eukaryotic telomeres and centromeres—has been largely excluded from these efforts despite constituting 20–30% of human and fly genomes [3] and up to 85% of others [4] . This omission is primarily due to the highly repetitive nature of heterochromatic DNA sequence , which renders it recalcitrant to sequence assembly on which structural , functional , and evolutionary insights depend . Heterochromatin research instead relies heavily on the analysis of the non-histone chromosomal “surrogate” proteins ( reviewed in [5] ) that localize to this genome compartment . This approach has illuminated roles of heterochromatin in many basic cellular and evolutionary processes such as gene regulation [6] , telomere maintenance [7] , [8] , genome defense [9] , and speciation [10] , [11] . The Heterochromatin Protein 1 ( HP1 ) gene family encodes arguably the best-known surrogate proteins for heterochromatin function . Mutant alleles of Drosophila HP1A , for example , first illuminated the essential role of heterochromatin in mitotic chromosome segregation [12] . Functional heterogeneity among HP1 paralogs also mirrors the functional heterogeneity of heterochromatic DNA . The recent identification of a female germline-specific HP1 ( HP1D/Rhino ) in Drosophila [13] , together with its non-overlapping cytological distribution with HP1A [14] , highlighted a distinct , functionally important heterochromatic compartment that encodes clusters of Piwi-bound RNAs ( piRNAs ) required for transposable element suppression [9] . All previously characterized HP1s localize to chromatin and , with the exception of HP1C , virtually all localize predominantly to heterochromatin [14]–[16] . We reasoned that new HP1 gene discovery via BLAST followed by a phylogenomic analysis ( i . e . , the prediction of gene function based on its evolutionary history in a phylogenetic tree [17] ) would provide novel surrogates for exploring new heterochromatin functions . Because all annotated heterochromatin proteins are encoded in the euchromatin , our surrogate approach enables us to harness the power of euchromatic comparative genomics to illuminate diverse heterochromatin functions and evolutionary signatures . We therefore conducted a comprehensive BLAST and phylogenomic analysis of the Heterochromatin Protein 1 gene family . Using the 12 sequenced Drosophila genomes spanning 40 million years of gene family evolution ( Figure 1A , [2] ) , we find unexpectedly high HP1 gene numbers and structural diversity . Our analysis increases this gene family from 5 to 26 genes , including several currently uncharacterized genes in the model genetic organism , Drosophila melanogaster . Many of these HP1s occur in “partial” form , having lost canonical HP1 domains; nevertheless , their open reading frames have been preserved for millions of years . Unlike the three original members of the HP1 gene family , all of the newly annotated HP1s are highly species-specific and almost exclusively germline-restricted . Similar to the original members , however , we find little evidence of positive selection driving the evolution of HP1 genes using both population genetic and molecular evolution analyses . In some instances HP1 gene presence/absence correlates with karyotype evolution across this 40 million year snapshot , suggesting that large-scale chromosomal evolution may contribute to at least some HP1 birth/death dynamics . This phylogenomic analysis sets the stage for a more comprehensive dissection of germline heterochromatin function in D . melanogaster and other emerging model Drosophila species .
Representatives of the HP1 gene family have been documented in many lineages of plants , animals , fungi and even protists , all of which harbor between one and three HP1 genes [15] . The founding family member , Heterochromatin protein 1A ( HP1A ) from D . melanogaster , was first described as a major non-histone chromosomal protein co-localizing with pericentric and telomeric heterochromatin [18] , [19] . HP1A harbors an N-terminal chromodomain ( CD ) [20] and a C-terminal chromoshadow domain ( CSD ) [21] separated by a hinge ( H ) domain . Despite homology , the CD and CSDs are functionally divergent . The CD mediates protein-chromatin interactions via histone modifications [22] ) whereas the CSD mediates protein-protein interactions , specifically recognizing a degenerate pentameric PxVxL domain in interacting proteins [23] . In some cases , the H domain binds RNA and DNA [24] , [25] . We refer to the regions outside the CD and CSD as the N- and C- terminal “tails , ” which are less well characterized . Since many Drosophila proteins encode chromodomains , we define HP1 gene family membership by the presence of both the CD and the CSD ( “full HP1” hereafter ) , a CSD only ( a domain exclusive to HP1 genes ) , or alternatively , a single CD ancestrally related to a full HP1 ( see Materials and Methods ) . Single-domain HP1s are referred to as “partial HP1s” hereafter . We constructed separate CD and CSD Bayesian phylogenetic trees to evaluate support for the ancestral relationship among currently defined full-length HP1s with the 16 partial HP1 genes . This analysis enabled us to delineate previously unknown HP1 lineages and to identify the putative gene duplication events that led to some of the current diversity of HP1s in Drosophila ( Figure 2A , 2B respectively ) . We built separate , domain-based trees for two reasons . First , prior studies had suggested the possibility that the phylogenetic histories of previously known CD and CSD are not always congruent [27] . Fusions of a CD and CSD from different HP1 lineages or evolutionary rate heterogeneity between the two domains may account for this observation . Second , we wished to analyze the origin of multiple CD-only and CSD-only partial HP1 genes , which would not have been possible on a combined ‘CD and CSD’ phylogeny . Since most of the HP1 genes we have identified are completely uncharacterized , we investigated their transcript levels across adult tissues . We prepared cDNA from six tissue types in five species of Drosophila- D . melanogaster , D . ananassae , D . pseudoobscura , D . willistoni and D . virilis ( Figure 3 ) . The selected subsample of species maximized the number of newly defined HP1s analyzed ( Figure 1B ) . Consistent with previous results , we found that HP1A , HP1B , and HP1C are expressed ubiquitously across sampled adult tissues . This expression profile is conserved across all 5 species assayed ( Figure 3A ) . In addition , HP1D/Rhino is expressed predominantly in the ovaries of all species , and is also weakly expressed in D . ananassae testes . In striking contrast , virtually all lineage-restricted HP1 genes reported in our phylogenomic analysis exhibit germline and primarily testes-restricted expression ( Figure 3A , 3B , summarized in Figure 4 ) . The only exception is D . pseudoobscura's HP1F , which is expressed in male and female heads only . HP1E , HP1G , HP1H , HP1J , HP1Kcd , GF19178 , GK19580 , Umbrea , HP1Lcsd , Skadu , GF16620 , GA29223 , GA22675 , GK15590 , GK10195 , HP1Mcsd and HP1Ncsd are all predominantly expressed in testes . Although we have not formally ruled out exclusive expression in the somatic cells of the testis sheath , it is likely that this enrichment reflects specific expression in the germline ( M . Levine , unpublished data ) . Oxpecker is the only partial HP1 expressed in the ovary while HP1H is expressed in both testis and ovary , but only weakly in the latter . We did not recover robust evidence for expression of HP1D3csd in D . melanogaster adults ( data not shown ) . Together , our results argue that constant innovation in the HP1 gene family has been driven by lineage-specific requirements in the Drosophila male germline . We next investigated the possibility that positive selection is associated with this recurrent innovation at the level of whole HP1 genes . A significant excess of positive selection signatures at testis-biased genes is routinely observed ( reviewed in [28] , [29] ) , consistent with pervasive sexual selection , host-pathogen interactions , and/or segregation distortion acting on those loci encoding products active in male reproductive tissue . Moreover , very young genes of comparable age to the young HP1s harbor an excess of such positive selection signatures [30] , [31] . Finally , previously published evidence of positive selection acting on the ovary-restricted HP1D/Rhino [14] implicated an unusual , specialized function for this HP1 gene which was borne out by later functional analyses [9] . To test the hypothesis that pervasive positive selection , and possibly genetic conflict , drives DNA sequence evolution of the germline-restricted , evolutionarily labile HP1s , we performed a comprehensive molecular population genetic and evolution analysis of DNA sequence polymorphism and divergence using publically available datasets of 44 D . melanogaster genomes and the full genome sequences of up to 9 close relatives ( see Materials and Methods ) . Several of these parameter estimates also enabled us to test whether these newly described HP1s are functional . We included the HP1 gene family members that have been previously functionally characterized ( HP1A , HP1B , HP1C , HP1D ) . In particular , the previously published strong signature of positive selection found at HP1D/Rhino [14] makes this locus a convenient “positive control . ” We focused on those HP1s that occur in D . melanogaster for which we have the most population genomic data , many closely related sequenced genomes , and the highest tractability for future functional analyses . We first investigated codon usage bias . The presence of only a narrow subset of redundant codons in coding sequence is consistent with gene function [32] . For each HP1 found in D . melanogaster , we estimated the “effective number of codons” or “ENC” , where 1 is the most biased and 61 is the least . In general , we observe homogeneity of low ENC estimates in HP1A , HP1B , and HP1C , while there is striking heterogeneity among the remaining HP1-like genes ( Table 1 ) . Moreover , elevated ENC estimates ( low codon usage bias ) for Skadu and HP1Lcsd places them in the 99th percentile of all D . melanogaster genes [33] , perhaps indicating loss of functional constraint . We observed a similar trend of heterogeneity in the new HP1 members for the ratio of nonsynonymous to synonymous π , an estimate of intraspecific sequence diversity . An excess of nonsynonymous mutations ( and therefore a high ratio assuming typical synonymous π—a signature of pseudogenes ) may be consistent with a loss of functional constraint . HP1Lcsd is in the 99th percentile for both the π ratio and ENC , which might indicate a loss of constraint at least along the D . melanogaster lineage despite its retention across more than 30 million years of Drosophila evolution . To test for heterogeneity in rates of DNA sequence evolution between species ( D . melanogaster and D . simulans ) among the founding HP1 family members , we calculated pairwise dN/dS ratios using the PAML suite of programs . These estimates are also consistent with substantially different rates of evolution between the founding members and most newly described HP1s ( Table 2 ) . We found that HP1A , HP1B , and HP1C have evolved between D . melanogaster and D . simulans at substantially slower rates than most germline-restricted HP1s . At the other extreme , the dN/dS for the coding sequence of HP1D/Rhino and Skadu are in the 99th percentile of all D . melanogaster genes , while HP1Lcsd and Umbrea are in the 95% [33] . The codon bias and π ratio estimates for HP1Lcsd may be consistent with elevated dN/dS driven by a loss of constraint along the D . melanogaster lineage but Skadu and Umbrea may be evolving under positive selection ( see below ) , as previously shown for HP1D/Rhino [14] . To test for a history of recurrent adaptive protein evolution at these and the remaining loci , we performed a McDonald-Kreitman test ( 20 ) using polymorphism data for both D . melanogaster and D . simulans and the divergence estimates between them . Homogeneity of fixations ( differences between species ) and polymorphisms ( differences within species ) for synonymous and nonsynonymous sites is consistent with neutral expectations , while an excess of nonsynonymous fixations between species is consistent with a history of recurrent positive selection . We found that not a single HP1 analyzed harbors the signature of recurrent positive selection ( Table 1 ) . One qualifier of this analysis is that a locus must experience positive selection at many sites to generate enough power to reject neutrality . This is especially relevant to HP1D/Rhino , for which a history of positive selection has been described , but only on the chromoshadow and C-terminal tail between these species , which would not emerge from this whole-gene analysis and with so little publically available D . simulans polymorphism data . Moreover , several genes harbor exceptionally few synonymous polymorphisms , further weakening our statistical power . Given these limitations , we subjected the same set of genes to a PAML analysis , which has additional power to detect recurrent positive selection acting at sequence encoding only a single domain . As expected , we find a significant signature of positive selection at HP1D/Rhino ( Table 3 ) . The CSD-only HP1 , Umbrea , harbors equally strong evidence of recurrent adaptive evolution . However , we found no evidence of positive selection ( Table 3 ) for any other germline-restricted HP1—both those conserved across the 40 million years of evolution ( e . g . , HP1A and HP1B ) and those that are relatively young ( e . g . , Oxpecker , HP1Lcsd , Skadu ) . This finding was particularly surprising for HP1E , the only full-length HP1 expressed predominantly in male reproductive tissues that we previously hypothesized to serve a functionally analogous role to the ovary-restricted , piRNA defense pathway member , HP1D/Rhino [27] . Our findings are consistent with HP1E and HP1D/Rhino evolving under different evolutionary forces . In summary , molecular population genetic and evolution analyses are consistent with mostly purifying selection and loss of constraint acting on the newly described HP1s that occur in D . melanogaster . The relatively constant HP1 gene number in any given species combined with pervasive birth-death dynamics across the broader tree is consistent with a “revolving door” model [34] , where one gene emerges along a lineage as another is lost . The pattern is readily apparent in Figure 4 . Non-orthologous CSD-only genes , for example , occur in each species or clade harboring at least one exclusive gene of this class ( Umbrea , Skadu , HP1Lcsd , GA29223 , HP1Ncsd ) . HP1E is found in eight of the 12 species . In the four species where HP1E is absent , at least one additional lineage-restricted , full HP1 is present . The D . pseudoobscura/D . persimilis lineage has HP1F , D . willistoni has HP1G and HP1H , and D . grimshawii has HP1J . Even across classes , we observe this pattern – the HP1D/Rhino-derived genes HP1D3csd and HP1D2 are retained in a mutually exclusive manner ( Figure 1B ) . These lineage-restricted HP1s may support a common but dynamic biological function that , like these genes , may be turning over repeatedly across the 40 million years examined . The 40 million year snapshot captured by the 12 Drosophila genomes harbors diversity at all levels of biological organization [2] . Particularly relevant to proteins that localize to chromatin is the diversity of heterochromatin content and chromosomal distribution . Moreover , chromosomal fissions and fusions , as well as satellite expansions and contractions , result in changes to chromosomal environment , e . g . , spreading or retreating of heterochromatin-euchromatin boundaries [35] . Heterogeneity in these features abounds across Drosophila evolution [36] , [37] . Chromosomal rearrangements can therefore serve as proxies for changes in heterochromatin content and distribution . Similar karyotypes , however , can also belie changes in heterochromatin content; satellite DNA content comprises 44% and 2% of D . virilis and D . mojavensis genomes respectively despite a similar karyotype [36] . We wondered if the alternative retention of HP1 genes correlates with the known karyotype and heterochromatin distribution evolution across the 12 genomes . High resolution dating of karyotype evolution in the obscura group [38] represents an opportunity to evaluate this hypothesis . Between 11 and 18 mya , an ancestor within the obscura group evolved an X-D element fusion ( [39] , element “D” = 3L in D . melanogaster ) , a neo-Y chromosome [40] putatively derived from the D element , and a Y∶F chromosome fusion ( [38] , the F refers to the 4th chromosome in D . melanogaster ) . These fusion events combine chromosomes with qualitatively different complements of non-histone euchromatin and/or heterochromatin proteins , in addition to generating a neo-Y that has acquired heterochromatin characteristics typical of the ancestral Drosophila Y chromosome [40] . We therefore undertook the sequencing of the HP1E locus from the obscura group—D . affinis , D . azteca , D . guanche , D . bifasciata—to compare with our D . persimilis and D . pseudoobscura data . Strikingly , we find that the HP1E loss event dates precisely to the ancestral lineage in the obscura group that underwent the chromosomal rearrangements ( Figure 5 , Figure S3 ) . D . affinis and D . azteca , which share the derived karyotype found in D . pseudoobscura and D . persimilis , harbor a highly pseudogenized HP1E in the syntenic location ( Figure 5 , Figure S3 ) . Although only a correlation , this observation suggests the possibility that selection at HP1E was relaxed in association with this karyotype evolution . Alternatively , the HP1E loss may have favored the fixation of one or more of these chromosomal rearrangements ( see below ) . Analysis of HP1E function , guided by this association of gene loss with a major sex chromosome evolution event , will help further illuminate the forces driving its recurrent degeneration . Given the vast evolutionary distance between sampled species , the 12 genomes are admittedly suboptimal for a more general analysis . The well-described karyotypic diversity , however , has the power to at least highlight associations worthy of further fine scale analyses . For example , species in the Drosophila subgenus ( D . virilis , D . mojavensis , D . grimshawii ) exclusively share the ancestral “five-rod” arrangement [37] . They also share many lineage restricted HP1s ( HP1J , HP1Mcsd , HP1Ncsd ) despite spanning virtually equivalent evolutionary distance across the whole tree ( ∼30 my ) . We observe the myriad HP1D/Rhino-derived CD-only HP1s only in lineages with fused Muller B and C elements ( D . melanogaster , D . simulans , D . sechellia , D . yakuba , D . erecta , D . ananassae , D . willistoni ) rather than being randomly distributed across the tree . Notably , one of the best-characterized , germline-expressed piRNA clusters [41] resides near the centromere of element C and these partial HP1s are actually independently derived from the CD of HP1D/Rhino , a piRNA defense protein that localizes to this cluster ( 9 ) . Finally , two independent HP1E loss events date to branches that have undergone independent Muller element X-D fusions and dot chromosome fusions to the ancient Y and ancestral 3R in D . pseudoobscura and D . willistoni , respectively .
The genome sequence of Drosophila melanogaster , published in 2000 , served to expand the HP1 gene family from one to three members—HP1A ( the founder ) , HP1B , and HP1C [42] . A family size of three is currently the maximum number of HP1s identified in any eukaryotic lineage outside of Drosophila . For example , mammalian genomes harbor HP1α , HP1β and HP1γ , which are derived from vertebrate-specific duplications of an ancestral HP1B-like gene [15] , [27] . The early Drosophila HP1 family members are transcribed ubiquitously in both sexes , have persisted for over 40 million years of Drosophila evolution , and participate in many chromatin-dependent , somatic cellular functions ( reviewed in [27] ) . Unlike the founders , the new HP1 gene family members exhibit pervasive lineage restriction , domain degeneration , and predominant germline expression ( summarized in Figure 4 ) . Across the 40 million year snapshot examined here , our analysis expands the Drosophila HP1 gene family from 5 to 26 members . If anything , this staggering increase in HP1 gene diversity is likely to be an underestimate . For instance , with our iterative BLAST search strategy we would not be able to detect CSDs or CDs that are highly diverged from all of the Drosophila HP1 genes identified in this study . Moreover , our methods would not detect HP1-derived genes that have only retained the original hinge or tails due to degeneration/loss of both the CD and CSD . Finally , we observed a somewhat smaller number of partial HP1 genes in species that share a more distant common ancestor with the well-annotated D . melanogaster , which might indicate that genome assembly gaps influence HP1 discovery biases . Nevertheless , our search represents the most exhaustive to date and proved substantially more powerful than previous genome-wide scans . Indeed , automated gene prediction algorithms and annotation software failed to predict coding sequences and/or identify many genes as HP1s , even in the well-annotated genome of D . melanogaster . Poor homology to known genes , some exceptionally short protein lengths especially for the partial HP1s , and extensive divergence/degeneration of the typically conserved CD and CSD domains may have concealed these HP1s from automated , DNA sequence-based , genome-wide methodology ( D . melanogaster R4 . 3 ) Using a phylogenomic approach , we set out to identify new surrogates for dissecting chromatin , and specifically , heterochromatin function and evolution . Given that all previously described Drosophila and non-Drosophila HP1s localize to chromatin [15] , [27] , we expect that the new full-length HP1s also encode non-histone chromosomal proteins . We also predict that the CD-only partial HP1s localize to chromosomes given that the CD specifically recognizes histone modifications [22] , [43] . Although the localization of partial HP1s that harbor only a CSD ( a protein:protein interaction domain ) is harder to predict , virtually all CSD-only HP1s share a common ancestor with a CSD that interacts with chromosomal proteins [15] , [27] . This phylogenetic signature is consistent with chromatin localization even for these proteins . This prediction holds for the only cytologically characterized CSD-only protein , Umbrea , which has been shown to localize to heterochromatin [44] and we have shown more specifically localizes to centromeres ( B . Ross and H . Malik unpublished , [27] ) . Confirming heterochromatin localization for each new HP1 will require detailed cytological analysis . Nevertheless , it is intriguing that none of the newly identified HP1 genes share a most recent common ancestor with HP1C , the only well-characterized HP1 that localizes exclusively to euchromatin . In other words , only the heterochromatin-localizing HP1s–HP1A , HP1B , and HP1D—emerged as parental or sister clades to the new HP1s for which we observe significant phylogenetic support . Whereas the molecular dissection of early HP1 members has illuminated the myriad heterochromatic and some euchromatic functions in somatic cells , the new surrogates we describe here will serve instead as guides in dissecting the germline . With the exception of HP1F , all newly described HP1 members are expressed predominantly in germline tissue and all are highly lineage-restricted , implicating species-specific specialization and possible functional replacements ( Figure 4 ) . However , unlike most testis- and lineage- restricted , young Drosophila genes [28] , [30] , [31] , we found no evidence of positive selection in most genes subjected to close evolutionary analyses . The results implicate biological functions that turnover on relatively longer time scales than the intragenomic conflict that putatively drives positive selection at HP1D/Rhino [9] , [14] and other testes specific processes [45]–[47] . The absence of a positive selection signature is particularly surprising for HP1E , which is the only full-length HP1 paralog in D . melanogaster expressed predominantly in testes . Indeed , we predicted that HP1E was the male functional analog of the female genome defense paralog , HP1D/Rhino , possibly supporting the sexually dimorphic piRNA pathway in males [27] . These data weaken the prediction that HP1E acts at the interface of host-TE interactions and may instead functionally replace HP1A in the male germline , as has been previously suggested [48] . A better candidate male analog might be any of the highly lineage-restricted partial HP1s GK19580 , GF19178 , and GG18261 that are constantly birthing from the HP1D/Rhino CD and may encode male genome-defense proteins that constantly turnover in response to TE turnover . Given the restricted subcellular localization of HP1D/Rhino to piRNA clusters [9] , [27] , we speculate that these HP1D-derived genes may also be involved in germline defense . While the role of HP1E in germline function remains undiscovered , its phylogenetic signature may be illuminating . We had initially predicted that HP1E was functionally replaced by HP1G and/or HP1H in D . willistoni and by HP1F in D . pseudoobscura [27] . To our surprise , however , HP1F is expressed in male and female heads only , weakening this hypothesis . D . pseudoobscura is the only species represented in the 12 sequenced genomes where a testis-restricted , full length HP1 is absent ( see summary in Figure 4 ) . It is also the only species without the ancestral Drosophila Y; instead it now has a neo-Y chromosome [40] . Moreover , the date of the HP1E loss ( and potentially HP1F gain ) precisely matches this karyotypic change . We speculate that the failure of D . pseudoobscura to “replace” HP1E with a full-length , testis-expressed HP1 may be related to the evolutionary dynamics of Y chromosomes in Drosophila species . We predict that HP1E interacts with ( ancestral ) Y-linked heterochromatin in species like D . melanogaster . Loss of this heterochromatin may have obviated the necessity for HP1E retention in D . pseudoobscura . These data put forth a general hypothesis that a species' compendium of chromosome-localizing proteins may evolve following major chromosomal rearrangements and/or heterochromatin-euchromatin boundary shifts . This evolutionary prediction is consistent with the observation that EMS-induced chromosome fusions result in phenotypes modulated by non-histone heterochromatin proteins . For example , two independently-derived X:4 fusion mutants exhibited sex chromosome nondisjunction and aberrantly low transcriptional output from the X-linked , heterochromatin-embedded rDNA locus [49] . Although the rDNA locus was intact in both cases , these mutants nonetheless manifested the classic rDNA deletion phenotype ( bobbed ) that also variegates with heterochromatin dosage . This kind of heterochromatin-dependent gene regulation is enhanced and suppressed by many classes of heterochromatin surrogate proteins . The gain and loss of heterochromatin-localizing proteins over evolutionary time may therefore prove to be recurrent events following naturally occurring chromosome fissions and fusions as well as other events driving expansions and contractions of heterochromatin . Alternatively , the birth and death of HP1 gene family members may drive karyotype evolution . Selfish genomic elements that cheat meiosis are often associated with chromosomal rearrangements that physically link segregation distorter loci and their enhancers ( reducing recombination frequency between them ) . An SD-enhancing HP1 that is linked to the fused chromosome might favor the retention of a rearrangement involving a drive locus . In contrast , an unlinked HP1 suppressor of drive , once fixed , would precipitate drive system breakdown and ultimately , HP1 gene degeneration—a model consistent with the HP1 revolving door we observe . Our phylogenomic analysis of the HP1 gene family over 40 million years of Drosophila evolution introduces many genes with the exciting potential of illuminating germline chromatin-dependent biology . Newly developed tools described for the non-melanogaster Drosophila species [50] , [51] will also aid the functional dissection of HP1 genes not found in D . melanogaster .
We used the chromodomains ( CD ) and chromoshadow domains ( CSD ) of the five previously described HP1 gene family members ( HP1A , HP1B , HP1C , HP1D , HP1E , www . flybase . org ) as queries in tBLASTn searches [52] of the 12 sequenced Drosophila genomes ( [2] , Figure 1A ) . All newly identified CD- and CSD- bearing genes ( identified initially by e-value less 0 . 1 ) were then culled by Prosite prediction of each domain ( www . expasy . org/prosite/ ) or ruled out due to homology to a known non-HP1 gene in D . melanogaster . CSDs are exclusive to the HP1 family and indeed no CSD query from a newly identified HP1 returned a BLAST hit with an E-value less than 1 . 0 to a non-HP1 gene . CD occur in many non-HP1 proteins , such as Polycomb , Su ( var ) 3–9 , and MSL3 [53] . We report the consistently higher e-values for hits to non-HP1 proteins than to the best BLAST hits , which were exclusively previously identified HP1s ( Table S3 ) . These hits subsequently served as queries for new searches of the 12 genomes . This strategy was iterated with both HP1 CDs and CSDs until no new CSDs were recovered or hits to only non-HP1 CDs were recovered . We classified CD-only hits as an HP1 family member only for those genes that share a most recent common ancestor with a full length ( chromo- and chromoshadow- containing ) HP1 clade with high significance ( posterior probability >0 . 95 , see below ) . The only exception was the newly described HP1Kcd , which is a CD-only lineage of HP1 that represents the remnants of an ancestral HP1 no longer present in this 40 million year snapshot or alternatively , a lineage whose rapid evolution obscures its phylogenetic relationships within Drosophila ( see Results ) . In this exceptional instance , BLAST hits to paralogous HP1s only in Drosophila and to Anopheles gambiae HP1A outside of Drosophila support our classification of HP1Kcd as an HP1 family member . In contrast to CDs , we classified all hits harboring a CSD as an HP1 gene family member since CSDs are an exclusive feature of HP1s [21] . Given that D . melanogaster served as the scaffold for genome assemblies , we anticipate that we likely missed proportionately more paralogs from genomes that share an increasingly distant common ancestor with this model species . However , our ability to identify new HP1 genes unique to individual species other than the well-annotated D . melanogaster suggests that this compendium is exhaustive . We cannot rule out , however , that unassembled stretches within the 12 genomes harbor HP1 gene family members that are not reported below . Moreover , any HP1s genes that retain only the “hinge” region ( between the CD and CSD ) or the “tails” ( outside the CD and CSD ) would be missed by our search strategy . Since several genes that we have identified and validated represent either unannotated genes or annotated genes that have yet to be named ( see Table S1 for complete list of flybase IDs or coding sequences if unannotated ) , we adopted a nomenclature scheme where orthologs are identified with the same gene name only if orthology is supported by both phylogenetic analyses and syntenic location ( thus , HP1A in D . melanogaster and all other Drosophila species ) . One exceptional gene is HP1Lcsd , which occurs in the syntenic location in the D . melanogaster subgroup ( Figure 1A , 1B ) , D . ananassae , and D . willistoni , but fails to cluster phylogenetically for the latter two species . We tentatively refer to all of these genes as HP1Lcsd given the low probability of two independent insertion events of a CSD-only HP1 into the same location . In cases where a newly defined HP1 clusters phylogenetically within a broadly distributed HP1 but the synteny criterion is not met , we refer to these genes as potential paralogs ( HP1D2 for “full” HP1s and HP1D3csd for a CSD only gene , for example ) . In cases where no consistent phylogenetic relationships or synteny can be established , or the common ancestor among a previously known and undescribed clade appears to pre-date the 40 million year old ancestor , we refer to these as ‘new’ clades of HP1 genes with a separate letter designation . Thus , we have designated these genes from HP1A to HP1Ncsd , skipping letter “I” for clarity . If a new partial gene is represented in only a single species ( or only the D . pseudoobscura/D . persimilis lineage ) , we used the flybase . org gene name ( e . g . , GA22675 ) . Finally , since the partial HP1s HP6/Umbrea , Skadu ( ‘Skadu’ is the Afrikaans word for ‘shadow’ ) , and Oxpecker have been referred to previously in the literature [27] , [54]–[56] , we retain these names . HP1E sequences amplified from D . affinis , D . azteca , D . guanche and D . bifasciata have been submitted to Genbank under accession numbers JQ889685–JQ889688 . We inferred ancestral relationships among orthologs and paralogs from CD or CSD phylogenetic trees generated by the Bayesian MCMC package BEAST v1 . 6 . 1 [57] using an uncorrelated log-normal relaxed clock [58] and the SRD06 substitution model [59] , which separates the evolutionary model for the third codon position from the first two . The CD tree was generated from 180–183 sites and the CSD tree from 162–168 sites ( Figure S6A , S6B ) . MCMC Chains ran until inspection of the traces and effective sample size of each parameter using the Tracer program ( http://tree . bio . ed . ac . uk/software/tracer ) indicated acceptable mixing ( ESS>200 for every parameter ) and stationarity ( as evaluated by the independent runs ) . For the CD phylogeny , we observed acceptable mixing after a single run of 10 million iterations . The CSD phylogeny required combining three independent runs of 10 million generations each . The first 10% of each MCMC run was discarded as burn-in . Finally , we constructed maximum-clade credibility trees from the posterior tree samples . All analyses were repeated at least once and the results compared for consistency . Evidence of independent evolutionary trajectories of CDs and CSDs ( see Results ) , in addition to the abundance of CD- and CSD- only paralogs , motivated the construction of separate trees for each domain . To investigate expression profiles of each HP1 gene in adult tissues , we extracted RNA from whole bodies , heads , reproductive tracts , and the remaining carcasses of male and female D . melanogaster , D . yakuba , D . willistoni , D . pseudobscura , and D . virilis using the TRIzol reagent ( Invitrogen ) . Following a DNase treatment ( Ambion ) and RNeasy ( Qiagen ) total mRNA clean-up , we generated cDNA ( SuperScript III , Invitrogen ) . A PCR master mix for each primer pair ( primer sequences listed in Table S2 ) was aliquoted into eight tubes containing genomic DNA ( positive control ) , water ( negative control ) , or one of the six tissue-restricted cDNA templates per species . We amplified the housekeeping gene Ribosomal protein L32 ( rp49 ) transcript using intron-spanning primers from all templates in all species to confirm that qualitative comparisons across tissue types for HP1-like genes were robust and to rule out the presence of genomic DNA contamination . For HP1 genes that occur in D . melanogaster , we estimated several population genetic parameters and ran tests of selection using publically available population genomic data and genome sequences from closely related species . We analyzed 44 alleles parsed from Drosophila Population Genomic Project ( DPGP , www . dpgp . org ) . We treated as missing data all bases with a quality score less than 30 , all regions that appeared as identical by descent ( IBD ) , and all regions that exhibited residual heterozygosity ( according to the description on DPGP website ) . We also excluded two alleles of HP1Lcsd from D . melanogaster that had premature stop codons that shortened the coding region by one codon . We used D . simulans polymorphism data from [60] and D . yakuba and D . erecta alleles from [2] as outgroups . For the population genetic analyses , we only considered sites with at least 20 D . melanogaster alleles and three D . simulans alleles . To estimate sequence variation , we calculated π as average pairwise differences [61] . To estimate codon usage bias , we calculated the “Effective Number of Codons” [62] or “ENC” in DNAsp v . 5 [63] for single alleles from D . melanogaster , D . simulans , and D . yakuba . We investigated heterogeneous rates of evolution by estimating linage-specific divergence on the branch leading to D . melanogaster and D . simulans using D . yakuba ( or D . erecta for HP1Mcsd/Ska ) as outgroup ( PAML v . 4 [64] ) . We ranked estimates relative to whole-genome estimates found in [33] . Finally , to test for evidence of positive selection using these population genomic data , we performed a McDonald-Kreitman test ( “MK test” [65] ) . For the test of selection using a phylogenetic approach , we accessed sequence data from D . melanogaster , D . simulans , D . sechellia , D . yakuba , and D . erecta orthologs from www . flybase . org . Preliminary sequence data from D . ficusphila , D . elegans , D . takahashii and D . biarmipes were obtained from Baylor College of Medicine Human Genome Sequencing Center Drosophila modENCODE project site ( http://www . hgsc . bcm . tmc . edu ) . We aligned orthologous genes in CLUSTALX [66] and fit our multiple alignments to an NSsites model implemented in PAML version 4 [64] . Using a likelihood ratio test to determine significance , we compared models M7 ( dN/dS values fit a beta distribution ) and M8 ( model 7 parameters plus one: dN/dS>1 ) assuming the f61 model of codon frequencies and multiple starting values of dN/dS . Tree topology was consistent with a previous report [67] .
|
Our genome is comprised of two compartments . The euchromatin harbors abundant genes and regulatory information , while heterochromatin harbors few genes and abundant repetitive DNA . These characteristic features of heterochromatin challenge traditional methods of sequence assembly and molecular dissection . The analysis , instead , of proteins that localize to and often functionally define heterochromatic sequence has illuminated numerous heterochromatin-dependent , essential cellular processes , including chromosome segregation , telomere stability , and gene regulation . With the aim of increasing our sample of heterochromatin-localizing proteins , we performed a comprehensive search for new members of Heterochromatin Protein 1 gene family over 40 million years of Drosophila evolution . Our report expands this family from a modest five genes to 26 genes . Unlike the founding family members , the HP1s we describe are structurally diverse , largely restricted to male reproductive tissue , and highly dynamic over evolutionary time . Despite recurrent HP1 gene birth and death , gene numbers per species are relatively constant . These gene “replacements” likely support a dynamic biological process . We propose , and present evidence for , the hypothesis that recurrent chromosomal rearrangements drive at least some HP1 gene family dynamics observed . We anticipate that these HP1 genes will help define new heterochromatin-dependent processes in the male germline .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"genomics",
"model",
"organisms",
"genetics",
"biology",
"computational",
"biology",
"evolutionary",
"biology",
"population",
"biology",
"genetics",
"and",
"genomics"
] |
2012
|
Phylogenomic Analysis Reveals Dynamic Evolutionary History of the Drosophila Heterochromatin Protein 1 (HP1) Gene Family
|
In the lifecycle of microorganisms , prolonged starvation is prevalent and sustaining life during starvation periods is a vital task . In the literature , it is commonly assumed that survival kinetics of starving microbes follows exponential decay . This assumption , however , has not been rigorously tested . Currently , it is not clear under what circumstances this assumption is true . Also , it is not known when such survival kinetics deviates from exponential decay and if it deviates , what underlying mechanisms for the deviation are . Here , to address these issues , we quantitatively characterized dynamics of survival and death of starving E . coli cells . The results show that the assumption – starving cells die exponentially – is true only at high cell density . At low density , starving cells persevere for extended periods of time , before dying rapidly exponentially . Detailed analyses show intriguing quantitative characteristics of the density-dependent and biphasic survival kinetics , including that the period of the perseverance is inversely proportional to cell density . These characteristics further lead us to identification of key underlying processes relevant for the perseverance of starving cells . Then , using mathematical modeling , we show how these processes contribute to the density-dependent and biphasic survival kinetics observed . Importantly , our model reveals a thrifty strategy employed by bacteria , by which upon sensing impending depletion of a substrate , the limiting substrate is conserved and utilized later during starvation to delay cell death . These findings advance quantitative understanding of survival of microbes in oligotrophic environments and facilitate quantitative analysis and prediction of microbial dynamics in nature . Furthermore , they prompt revision of previous models used to analyze and predict population dynamics of microbes .
Under favorable growth conditions , microorganisms can grow rapidly . For example , E . coli cells can grow as fast as ∼ 20 min per doubling under ideal growth conditions . If this rate continues , a single E . coli bacterium can generate the mass of the earth in a couple of days . Clearly exponential growth cannot be sustained infinitely . Eventually , nutrients required for cell growth will be depleted and cells will be subject to long periods of starvation . Indeed , a survey suggests that ecosystems are dominated by starving microbes [1] . Due to their dominance , understanding quantitatively how starving microbes live and die is of great interest in various fields of microbiology , ranging from analyzing microbial population dynamics in soils to predicting the number of microbes in freshwater . However , our quantitative understanding of survival kinetics of starving microbes is poor . In textbooks , survival kinetics has been commonly assumed as simple first order kinetics , i . e . , exponential decay [2 , 3] . In the literature , this assumption has been widely used as a basis for analyzing and predicting microbial population dynamics , e . g . , see [4–6] . This assumption , however , has not been rigorously tested . Currently , it is not clear under what circumstances this assumption is true . Also , it is not known when such survival kinetics deviates from exponential decay and if it deviates , what underlying mechanisms for the deviation are . A large body of studies exists that characterizes starvation response at the molecular level; for example , see [7–10] for complex signaling pathways and gene regulations in response to starvation in proteobacteria . However , our molecular-level knowledge is still far from complete even for model systems such as E . coli . Also , much of our knowledge is qualitative and it is not clear to what degree these molecular processes affect cell survival . Thus , our molecular-level knowledge has not contributed to quantitative understanding of survival kinetics of starving cells . In recent years , quantitative and phenomenological characterization of cellular processes proved to be a powerful approach for deeper understanding of complex biological systems , e . g . , see [11–15] . In particular , it was shown that despite complex underlying molecular interactions , simple phenomenological laws governing cellular-level behaviors can exist and such laws greatly facilitate deeper understanding of underlying mechanisms [16] . In this work , using such phenomenology-to-mechanism approach , we rigorously characterized cell survival under starvation using E . coli as a model system . We show that survival kinetics of starving E . coli is biphasic and cell-density-dependent . Quantitative analyses reveal simple quantitative formulas governing the patterns , e . g . , the first and second kinetics are well described by exp ( -t2 ) and exp ( -t ) respectively , and the duration of the first kinetics is inversely proportional to cell density . ( The results show that the previous assumption—exponential decay of survival of starving cells—is true only at very high cell density . ) Next , using this knowledge as a guide , we identified key underlying processes for cell survival . Using mathematical modeling , we showed how these processes contribute to the intricate survival patterns observed .
Cells were grown in minimal media with glycerol as the sole carbon source ( see Materials and methods ) . As cells grow , glycerol is consumed and eventually exhausted , leading to the cessation of growth; we provided low enough amounts of glycerol to ensure that the growth is arrested as a result of the exhaustion of glycerol , not by other nutrient sources ( S1 Fig; see Materials and methods for the exact glycerol concentrations used ) . The cultures containing different amounts of glycerol in the medium initially result in different saturating densities of cells at the onset of the growth arrest ( S1A Fig ) . The onset of growth arrest defines the time zero ( S1B Fig ) . Afterwards , the number of colony-forming units , NCFU , was determined at various time points using a standard plate count method . We define the cells that grow on the agar plates and form colonies as viable . The temporal kinetics of NCFU in glycerol-exhausted cultures with 5 different cell densities is plotted in Fig . 1 ( see S2 Fig for the kinetics of other cell densities ) . For the cultures whose densities are higher than ∼108 cells/ml , NCFU follows a single phase exponential decay . The black dashed lines are plotted for a visual guide and its slope , −μ0 ( = −0 . 018 hr -1 ) , corresponds to the rate of cell death in these cultures . Note that NCFU of starving wild-type E . coli cells reported previously in the literature can be well approximated by a single-phase exponential decay [17–19] . In the cultures with lower densities , however , we see biphasic kinetics of NCFU ( see black diamonds and red circles in Fig . 1 and purple hexagons and green triangles in S2 Fig ) ; NCFU gradually decreases initially ( the first phase ) and eventually decreases exponentially at the rate of −μ 0 ( the second phase ) . The period of the first phase becomes more pronounced at lower cell density , prolonging cell survival . When we repeated this experiment using other carbon sources or using a different E . coli strain , we observed similar density-dependent biphasic kinetics of NCFU ( S3 Fig and S4 Fig ) . Previously , it was shown that cultures starved of nutrients for a long time yield mutants with increased fitness , called the growth advantage in stationary phase ( GASP ) phenotype [20 , 21] . The appearance of GASP mutants results in visible change in NCFU; NCFU initially decreasing at a constant rate reaches a plateau when GASP mutants appear . The timing of appearance of GASP mutants depends on the types of media and bacterial strains used [21]; for example , in Luria-Bertani ( LB ) media , they appeared within several days of growth cessation [21] while in other starvation experiments using minimal media , they appeared after ~ 30 days of starvation [22] . In our experiment , using minimal media , we performed experiments for ~ 12 days . During this time , we did not observe such transition in NCFU ( i . e . , from a rapid decrease to a plateau ) ; see Fig . 1 . This strongly suggests that GASP mutants have not appeared during our experiments . Also , when we repeated the experiment using cells from single colonies obtained from the cultures starved for 12 days , we observed that NCFU of these cells decreases very similarly as NCFU shown in Fig . 1 ( S5 Fig ) . Taken together , we conclude that GASP mutants have not appeared and played no role in the survival kinetics observed in our experiments . It is well known that microorganisms use extracellular signaling to sense the density of the populations and coordinate their behaviors accordingly [23]; they secrete extracellular signals and such signals accumulate in the medium , allowing cells to sense the density and regulate their behaviors accordingly . The cost and benefit of such extracellular signaling has been recently demonstrated quantitatively [24] . It is possible that the density-dependent kinetics of survival and death observed in Fig . 1 could be also mediated by such extracellular signaling; such ( potential ) signals may accumulate to high levels in high cell-density cultures , or in low cell-density cultures at a later time , triggering a rapid , exponential decay of NCFU . Note that the second case requires the signals to be stable at least for ∼100 hrs ( see Fig . 1 ) . To test this possibility , we repeated the experiment above using media designed to remove or concentrate these potential secreted factors , as described below . First , cells were grown as in the previous experiment . When the growth stopped due to glycerol exhaustion at a high density ( NCFU ≈ 7·108/ml ) , we washed the cells and re-suspended them in a fresh medium without glycerol; the fresh medium would not contain these secreted factors . In Fig . 2A , we see that NCFU of cells in the fresh carbon-free medium ( green triangles ) decreases exponentially at a similar rate as NCFU from the previous experiment ( solid blue squares; re-plotted from Fig . 1 ) , indicating that the lack of these secreted factors has little effect on the kinetics . Second , we reason that a spent medium in which cells were grown previously to a high density would contain high levels of the secreted signals . Because the signals should be stable ( discussed above ) , starving cells at low cell density in such a medium would exhibit a rapid , exponential decay of NCFU , similarly to that in high cell density . We prepared such a spent medium ( the old cells were removed from the medium ) , added a low amount of glycerol and a low number of exponentially-growing cells to the medium , and grew them . After the growth was arrested at a low density ( NCFU ≈ 9·106/ml ) due to the exhaustion of glycerol , we measured NCFU over time ( see Materials and methods ) . We observed that NCFU from the spent medium ( green inverse triangles in Fig . 2A ) follows the same biphasic pattern as NCFU of the culture with a similar density from Fig . 1 ( compare green inverse triangles and solid red circles; the solid red circles are re-plotted from Fig . 1 ) . Taken together , these results indicate that the density-dependent kinetics of cell survival is not due to extracellular signaling . Previously , it was known that the master regulator of the general stress response rpoS plays an important role for survival of E . coli cells under various environmental stresses [7–10] . To examine a role of rpoS in the observed kinetics , we repeated our experiment ( that yielded Fig . 1 ) using the ΔrpoS strain and plotted NCFU as open symbols in Fig . 2B and S6 Fig . For all the densities tested , NCFU of the ΔrpoS strain decreases exponentially at the rate of −μoΔrpoS ( = −0 . 035 hr -1; see the dotted lines ) . This is higher than that of the wild type strain , −μ o ( = −0 . 018 hr -1 ) , consistent with previous observation [18 , 25] . NCFU of the low cell density culture of the ΔrpoS strain ( open red circles in Fig . 2B ) exhibits a period of gradual decay before it decreases exponentially at the rate of −μ oΔrpoS ( brown region ) . However , the period is much shorter than the period of gradual decay for the wild type cells ( green region ) ; note that the exact determination of this period is discussed below and in Fig . 3 . This indicates that rpoS plays an important role for the wild type strain to maintain NCFU for extended periods of time in low cell density . To quantitatively analyze the survival kinetics of the wild type cells under starvation , we re-plotted the data in a manner that reveals the power law exponent of exponential functions; we denoted the number of colony-forming units at the time zero by N0 and plotted log ( N0 /NCFU ) against time in a log-log plot ( Fig . 3 and S7 Fig ) . For example , if the kinetics of survival follows a first-order kinetics , meaning NCFU∝exp ( −c1⋅t ) , ( 1 ) where c1 is a coefficient , the plot of log ( N0 /NCFU ) yields a straight line with a slope of 1 ( orange line in Fig . 3A ) . If the kinetics follows NCFU∝exp ( −c2⋅t2 ) , ( 2 ) where c2 is a coefficient , the plot yields a straight line with a slope of 2 ( cyan dashed line ) . For high cell-density cultures ( i . e . , N0 ≥ ∼108 cells/ml ) , the data follows a straight line with a slope of 1 ( Fig . 3B and S7A Fig ) , indicating the temporal kinetics of NCFU is well described by Eq . ( 1 ) , i . e . , exponential decay , as discussed above . When we fit the data ( in Fig . 1 and S2 Fig ) using Eq . ( 1 ) , we see c1 remains constant for different N0 ( navy left triangle , blue square and orange right triangle in Fig . 3G ) and c1 ≈ μo ( = 0 . 018 hr -1 ) . For lower cell-density cultures ( i . e . , N0 < ∼108 cells/ml ) , the slope is initially 2 ( green region in Fig . 3C and 3D , and S7C Fig—S7E Fig ) , but becomes 1 later , revealing the biphasic decay seen in Fig . 1 at low density . Thus , the first phase and second phase of the survival kinetics are well described by Eqs ( 2 ) and ( 1 ) respectively . In these figures , the time at which the transition from the slope 2 and slope 1 occurs is marked as T0 ( see arrows; it is the time point at which the two lines intersect ) . In Fig . 3E , we see T0−1 is linearly proportional to N0 . Alternatively , T0∝N0−1 , ( 3 ) indicating the period of the first phase becomes shorter as cell density increases . This suggests that we observe only the second phase of survival kinetics in high density ( i . e . , exponential decay in Fig . 1 ) , because T0 is small . To obtain coefficients in Eqs ( 1 ) and ( 2 ) for the low cell-density cultures , we fit the data in Fig . 1 and S2 Fig using the equations; the data in t < T0 and in t ≥ T0 are fitted using Eqs ( 2 ) and ( 1 ) respectively . We see that c2 increases linearly to N0 in Fig . 3F . Hence , c2 = c ⋅ N0 , where c is a constant . Also , we see that c1 remains constant for different N0 , and c1 ≈ μo in Fig . 3G . Thus , together with Eq . ( 3 ) , the temporal kinetics of NCFU is well described by NCFU={N0⋅exp ( −c⋅N0⋅t2 ) N1⋅exp ( −μ0⋅t ) if0≤t<T0ift≥T0 , ( 4 ) where N1 is set to make NCFU a continuous function , being equal to N0exp ( −c⋅N0⋅T02+μ0⋅T0 ) . The quantitative formula ( Eq . ( 4 ) ) reveals that the previous assumption—NCFU decreases exponentially under starvation—is valid only at high cell density . At low cell density , however , NCFU gradually decreases initially , before it decreases exponentially . The initial gradual decrease , well described by exp ( -t2 ) , is extended at lower density , resulting in prolonged survival of starving cells . What is the mechanistic basis of the prolonged survival that appears in the density-dependent manner ? Because the kinetics is significantly altered in the ΔrpoS strain ( Fig . 2B ) , we first considered known regulation of RpoS expression and its effects on cell survival . As cells grow and consume substrates , the concentration of substrates in the medium will decrease ( green line in Fig . 4A ) . When the concentration falls to the level reducing the rate of cell growth , the expression of RpoS is activated ( blue line; note that higher RpoS levels at lower substrate concentrations were previously established [26 , 27] ) . The RpoS expression subsequently leads to expression of other new genes ( i . e . , RpoS regulon ) and the expression of these genes protects cells from stress [7–10] . Importantly , this protection is expected to be density-independent , because RpoS expression itself is independent of cell density [26 , 27] . In Fig . 3G , we see that in the second phase of the survival kinetics , NCFU decreases at the rate of −μo ( = −0 . 018 hr -1 , dashed line ) independently of cell density . This is lower than the rate of decrease in the ΔrpoS strain , −μ oΔrpoS ( = −0 . 035 hr -1 , see Fig . 2B ) , suggesting that the protection lowers the rate of viability loss during the second phase independently of cell density . This protection , however , is not likely to be a major cause for the extension of the first phase at low density , because the extension is strongly dependent on cell density; see Fig . 1 and Fig . 3E . ( There are studies suggesting that RpoS expression may be possibly higher at higher cell density [28 , 29] . Even if this is true , it cannot account for our observation that the first phase is extended further at lower cell density . ) Next , we turn to another major effect of RpoS . It is well known that the expression of RpoS represses cell growth ( red line in Fig . 4A ) [30–32] . Currently , the molecular mechanism of the repression is not clear , although it was proposed that RpoS directly inhibits the uptake of nutrients [39] . Importantly , with this repression , a negative feedback loop among RpoS , substrate concentration and cell growth is formed as depicted in Fig . 4A ( blue and green lines were described above ) . In biological systems , negative feedback is frequently employed to achieve a homeostatic maintenance or a gradual change of a system , e . g . , see ref . [40 , 41] . The negative feedback loop suggested above may play a similar role , providing a mechanism for a gradual change of NCFU observed in the first phase of the survival kinetics ( Fig . 1 ) for the wild type cells in the following way . For biomass increase , cells consume substrates in the medium . As the substrate concentration in the medium decreases to low levels due to the consumption ( green line in Fig . 4A ) , the feedback loop would exert repression on biomass increase ( blue and red lines ) , and hence , the substrate consumption ( green line ) . The repression would be stronger as the substrate concentration in the medium is further reduced . Eventually , it will lead to cessation or near-cessation of the substrate uptake for biomass increase , and consequently , prevents cells from completely depleting the substrate in the medium . Indeed , when we measured glycerol concentration in the medium at the onset of growth cessation ( time zero in Fig . 1 ) , we see that the glycerol concentration is not zero , but in μM range ( see Materials and methods ) . This observation also agrees with previous studies [33–35]; in these studies , it is shown that as the substrate concentration S decreases , the growth rate λ decreases , but λ becomes zero at a non-zero substrate concentration . Denoting this concentration by S1 , this phenomenon is illustrated in Fig . 4B as λ = 0 at S = S1 > 0 . Note that this is contrary to a prediction from the Monod equation , a well-known kinetic equation describing the relation between λ and S [42] , which predicts λ = 0 when S = 0; see S2 equation . However , the Monod equation does not address the decrease in a population size during starvation ( because λ in the Monod equation is always greater than or equal to 0 ) , and is not applicable to our study . In fact , the Monod equation is a purely empirical formula based on curve fitting of experimental data ( see the description below S2 Equation ) . A great deal of studies show that the Monod equation does not describe the dynamics of change in a population size well at very low substrate concentrations; see ref . [36 , 43] for review and S1 Text for details . Importantly , even when the growth rate of a population is zero ( i . e . , λ = 0 at S = S1 in Fig . 4B ) , the substrate consumption rate is not zero [37 , 38 , 44 , 45]; also , see ref . [36] for review . These studies have shown that it requires continuous influx of the substrate into the medium to maintain the population size at a constant level , termed maintenance requirement . ( It was proposed that the substrate is used to fix chemical “wear and tear” of cell materials and fulfill other non-growth related functions . See [36 , 46] for detail . ) . If the influx rate of the substrate meets the maintenance requirement , the population size is maintained; in Fig . 4B , this occurs when S is kept at S1 by continuous influx of the substrate against the consumption of the substrate for the maintenance . If the influx rate is less than the level needed for the maintenance , the population size decreases ( λ < 0 , green region in Fig . 4B ) . The rate of the decrease is faster at a lower influx rate of the substrate and , with no influx , the rate of the decrease reaches its maximum , i . e . , λ ( 0 ) in Fig . 4B . In our experiments , after the onset of growth arrest ( time zero in S1B Fig ) , there is no additional influx of the substrate to the medium . But , as discussed above ( 3 paragraphs above ) , a certain amount of the substrate ( i . e . , S1 ) remains in the medium at the onset of growth arrest . This conserved substrate can be used for the maintenance , allowing cells to maintain their population size initially . Such usage will result in continuous decrease of S ( cyan line in Fig . 4C ) , leading to a gradual decrease of λ below 0 ( see λ < 0 when S < S1 in Fig . 4B ) . Consequently , the population size will gradually decrease , giving rise to the first phase of the biphasic decay ( cyan line in Fig . 4D ) . Eventually , the substrate is completely exhausted at T0 ( Fig . 4C ) , hence , S = 0 ( orange line in Fig . 4C ) . Thus , after T0 , NCFU will decrease at the constant rate of λ ( 0 ) , i . e . , exponential decay , giving rise to the second phase ( orange line in Fig . 4D ) . In this model , the density-dependence of the first phase in the survival kinetics arises because , for the culture with higher cell densities , the conserved substrate ( S1 ) will be consumed by more cells . Thus , it will be depleted faster for high cell density , leading to shorter periods of the first phase . Therefore , in our model , the density-dependent survival kinetics can be accounted for without invoking presence of ( unknown ) extracellular signaling molecules , agreeing with our observation in Fig . 2A . On a related note , there exists a study that shows a density-dependent response to bacterial survival under antibiotic treatment and such density dependence can be accounted for without invoking extracellular signaling [47] . To examine whether the biological processes described above can quantitatively account for the survival kinetics observed in our experiments , we constructed a mathematical model based on them . The details of our model are described in S1 text . Briefly , our model contains two key components , both of which are discussed above . The first component is the dependence of λ on S , which is plotted in Fig . 4B . Because we are particularly interested in the change of the population size when the substrate is nearly or completely exhausted , ( i . e . , S is close or equal to 0 ) , the dependence of λ on S can be approximated to the first order in our model ( see S3 Equation—S5 Equation ) . The second component of our model is the decrease of the substrate concentration due to the consumption for the maintenance ( Fig . 4C ) . Here , based on previous studies [37 , 38] , we assume the substrate consumption rate per cell is constant over time and the total consumption rate is proportional to cell density ( S6 Equation ) . Quantitative formulation of these processes straightforwardly leads to a mathematical solution equal to the empirical formulas; compare Eqs ( 3 ) and ( 4 ) , and S11 Equation and S12 Equation . The solution states that a ) the decay of NCFU is biphasic , exp ( −c ⋅ N0 ⋅ t2 ) decay followed by exp ( −μ⋅t ) decay , and b ) the time at which the transition occurs ( i . e . , T0 ) is inversely proportional to cell density . The solution contains two fitting parameters , μ and c . Representing the rate of a population decrease at the zero substrate concentration ( i . e . , λ ( 0 ) ; see the description below S4 Equation ) , the μ can be obtained from the rate of decrease of NCFU in the second phase of survival kinetics in Fig . 1 and S2 Fig . Hence , λ ( 0 ) = − μ ≈ − μ0 . Alternatively , the μ as well as c can be obtained by fitting the solution ( S11 Equation and S12 Equation ) to the data shown in Fig . 1 and S2 Fig . The result of the fit is plotted as lines in these figures , which yielded μ = μ o = 0 . 018 hr -1 and c = 4 . 7×10–12 ml·hr-2 ( λ ( 0 ) = −μ = −μ0 in Fig . 4B is based on this result ) . The fit shows that the model can quantitatively account for our data—such consistency is expected because the solution of our model is equal to the empirical formula . The lifecycle of bacteria consists of short periods of feast , intercepted by long periods of starvation [1] . Quantitative analysis of how cells persevere during starvation is the focus of this study . Our findings show that after the onset of starvation , in high density cultures the loss of viability begins immediately at a constant rate . However , in low density cultures , the viability is maintained for extended periods of time before it decreases at the same constant rate . Such density-dependent survival kinetics is mediated by the master regulator of the general stress response rpoS . Integration of previously known processes reveals a thrifty strategy of bacteria , by which upon sensing impending starvation , cells repress nutrient consumption for biomass increase and use the remaining nutrient in the environment to delay cell death . Mathematical modeling of these processes accurately accounts for the density-dependent , biphasic survival kinetics . The benefit of such thrifty behavior is obvious; it delays cell death . However , we note that such behavior has a cost in bacterial fitness because it diverts the limited nutrients away from cell growth , reducing the number of offspring . Thus , we expect the evolution of such behavior would depend on environmental conditions and be favored when the benefit outweighs the cost . The benefit is expected to depend on the length of starvation that cells routinely experience . If starvation periods are very short , the benefit of delaying death for long-term survival becomes negligible and may be outweighed by the cost . ( in such case , it is expected that rpoS mutants outcompete the wild type cells . ) The benefit would increase as the starvation periods become longer . Of course , if starvation periods are very long , it would lead to the emergence of GASP mutants [20 , 21] , which is outside of the scope of this study . Thus , we expect that the evolution of such behavior would be strongly dependent on the starvation periods cells routinely experience . Another factor to affect the evolution of such behavior would be spatial structure of the environments . In structured environments where cells grow clonally , such behavior would be beneficial . However , in homogenous environments where the nutrients conserved to delay cell death by one species could be accessed by other species of bacteria , such behavior would not be beneficial . In such case , it would be more advantageous to use up all the nutrients and the rpoS mutants may be more fit than the wild type cells . Obviously , conserving the limiting nutrients by the wild type cells is one form of cooperation and rpoS mutants may appear as cheaters . However , the mixed population of the wild type cells and rpoS mutants may get fragmented and disperse at some point , and new monoclonal populations of wild types cells and those of rpoS mutants will be formed . During starvation , the latter will die rapidly , while the former will survive longer ( Fig . 2B ) . As such , how often such population fragmentation occurs will affect the evolution; see the previous studies [48 , 49] that quantitatively examined how such fragmentation affects the evolution of cooperative behavior . These considerations , taken together , suggest that the evolution of the thrifty strategy observed in our study depends on various environmental factors , and it would be interesting , in future studies , to determine the dependence quantitatively . It is worth noting that in previous experiments , when cells were grown in the nutrient-limited chemostat where nutrient levels were artificially kept very low , rpoS mutants were frequently found [50 , 51] . The observation agrees with our argument in that at low nutrient levels , wild type would try to conserve the nutrients by not growing , while rpoS mutants will continue to grow . On a related note , we believe such studies would draw an interesting analogy with a recent work that characterized the conditions affecting evolution of spore-formation in spore-forming bacteria [52] . Some bacterial species , such as B . subtilis , form spores upon sensing nutrient limitation [53] . Spores are very resistant to stress , persisting through starvation for long periods of time . In the recent work [52] , it was shown that it is beneficial to initiate spore-formation before nutrients are completely depleted by biomass increase and , in some conditions , extracellular signaling may evolve to assist this process . The first finding is analogous to our findings in that upon sensing impending starvation , these cells take action for long-term survival before the nutrients are completely depleted . Also , the second finding has bearing on understanding why in the cells we studied ( E . coli ) , extracellular signaling was not evolved ( Fig . 2A ) . We believe our study will advance our understanding of starved bacteria , especially their starvation survival physiology . Because ecosystems are dominated by starving microbes [1] , our findings will facilitate deeper understanding of microbial population dynamics in microbial ecology and environmental sciences . We expect that such knowledge will have important implications in public health sectors [54]; e . g . , accurate prediction of how pathogens persevere in freshwater will lead to better understanding of how infectious diseases spread and developing better public health policies .
Escherichia coli wild-type K12 strain NCM3722 [55 , 56] was used in our experiment . To make the ΔrpoS strain , we purchased the deletion allele of ΔrpoS from Keio deletion collection [57] , transferred it to NCM3722 using P1 transduction [58] . N-C- minimal media [59] , supplemented with 20mM of NH4Cl and various concentrations of glycerol , were used for cell growth . The glycerol concentrations used were 5 mM , 1 mM , 0 . 7 mM , 0 . 5 mM , 0 . 3 mM , 0 . 2 mM , 0 . 15 mM , and 0 . 05 mM . Note that although glucose is a common carbon source for cell growth , we did not use glucose in our experiments because of bacterial Crabtree effect [60]; cells growing on glucose excrete acetate , and the excreted acetate is used as the cell density increases and the glucose level decreases . This would complicate our study to characterize the cell density dependence of NCFU decay . Cells were grown at 37°C with shaking at 250 r . p . m . in a water bath ( New Brunkswick Scientific ) . To monitor their growth , optical density ( OD600 ) was measured using a Genesys20 spectrophotometer ( Thermo-Fisher ) . When the OD600 values were too low for the measurement using a standard sample holder ( 16 . 100-Q-10/Z8 . 5 , Starna Cells Inc ) , a sample holder ( 18B-SOG-40 , Starna Cells Inc ) that is 4 times longer ( OD600×4 ) was used . Cells were first grown in LB broth for 4∼5 hrs ( seed culture ) , transferred to a N-C- minimal medium with 20 mM of glycerol and 20 mM of NH4Cl and grown overnight ( pre-culture ) . The next morning , the cells growing exponentially in the pre-culture were transferred to the media specified above ( experimental culture ) . The initial density of cells in the experimental culture was adjusted such that cells continued to grow exponentially for at least 4 more doublings in the experimental culture , before their growth stopped due to the depletion of glycerol ( S1 Fig ) . The experiment in which the effects of extracellular signals were tested ( Fig . 2A ) was performed in the following way . First , cells were grown in the minimal medium with 5 mM of glycerol . When their growth stopped at high density due to glycerol depletion ( NCFU ≈ 7·108/ml ) , we waited ∼7 hrs . Then , cells were spun down ( the supernatant was set aside ) , transferred to a carbon-free medium with 20 mM of NH4Cl . The volume of the carbon-free medium was adjusted in such a way that the initial cell density ( measured from OD600 ) matches that from the viability curve of blue squares in Fig . 1 . Then , their viability was measured afterwards ( green triangles in Fig . 2A ) . Then , to the supernatant obtained from the procedure above , we added 0 . 05 mM of glycerol , transferred exponentially growing cells into it ( NCFU ≈ 5·105/ml ) , and grew them until growth stopped due to glycerol depletion at low cell density ( NCFU ≈ 9·106/ml ) . Then , we measured their viability afterwards ( green inverse triangles in Fig . 2A ) . Please note that initial cell density was first estimated from the OD600 value of the culture ( with the knowledge that 1 OD600 corresponds to ∼109 cells/ml ) and later confirmed ( using the viability assay as described below ) . The viability was determined by counting the number of colony-forming-unit ( NCFU ) on LB agar plates . After platting , the plates were incubated at 37°C overnight before counting . NCFU did not change even if the plates were incubated for 3∼5 more days . Through serial dilutions , we ensured NCFU to be around 100∼200 per agar plate ( 100 × 15 mm petri dish ) . NCFU reported was averaged values of 3 replicate measurements . Each experiment was independently repeated 2∼4 times ( e . g . , see S8 Fig ) . Glycerol concentration in the medium was measured using Glycerol assay kit ( SigmaAldrich , F6428 ) as described in the manual , except the ratio between the medium and the agent was increased to 1 to 1 . 5 . In four independently repeated experiments , we observed that the glycerol concentration at the onset of growth arrest of glycerol-starved cultures was between 0 . 5∼2 μM . We note that this is below the range of quantitative measurement of the method employed , and absolute quantification of such low concentrations is very difficult . However , we always observed positive values . ( The measurement was calibrated using media with known glycerol concentrations . In this calibration , the medium without glycerol is used as the reference for zero glycerol concentration . )
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Long periods of starvation are common in the lifecycle of microorganisms . Textbooks routinely describe that during starvation periods , cells die at a constant rate , i . e . , exponential decay . The exponential decay of cell survival has been commonly assumed in the literature to analyze and predict population dynamics of microbes . Here , we show that this assumption is true only at high cell density . At low cell density , cells can persevere for extended periods of time , before dying at a constant rate . Quantitatively analyzing the kinetics , we uncover mathematical formulas governing the density-dependent , biphasic decay of cell survival . Using mathematical modeling , we further reveal key underlying processes responsible for the perseverance . Our model highlights a thrifty strategy of bacteria; upon sensing impending starvation , small amounts of nutrients are conserved and used to persevere during starvation periods . In addition to advancing our fundamental understanding of physiology of bacteria in nature , our study will facilitate the analysis and prediction of microbial dynamics in nature . We expect that our findings will have broad impacts . For example , our findings can be used to accurately predict how pathogens survive in natural environments , which will lead to better public health policies .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Survival Kinetics of Starving Bacteria Is Biphasic and Density-Dependent
|
G-quadruplexes ( G4 ) are secondary structures formed by guanine-rich nucleic acid sequences and shown to exist in living cells where they participate in regulation of gene expression and chromosome maintenance . G-quadruplexes with solvent-exposed guanine tetrads show the tendency to associate together through cofacial stacking , which may be important for packaging of G4-forming sequences and allows for the design of higher-order G4 DNA structures . To understand the molecular driving forces for G4 association , here , we study the binding interaction between two parallel-stranded G-quadruplexes using all-atom molecular dynamics simulations . The predicted dimerization free energies show that direct binding through the 5’-G-tetrads is the most preferred of all possible end-to-end stacking orientations , consistently with all available experimental data . Decomposition of dimerization enthalpies in combination with simulations at varying ionic strength further indicate that the observed orientational preferences arise from a fine balance between the electrostatic repulsion of the sugar-phosphate backbones and favorable counterion binding at the dimeric interface . We also demonstrate how these molecular-scale findings can be used to devise means of controlling G4 dimerization equilibrium , e . g . , by altering salt concentration and using G4-targeted ligands .
G-quadruplexes ( G4 ) are non-canonical four-stranded structures formed by guanine-rich sequences of nucleic acids , in which sets of four guanine residues associate into planar arrays ( G-tetrads ) through cyclic Hoogsteen hydrogen bonding [1–3] . By stacking on top of each other , G-tetrads make up the core of the G4 structure ( see Fig 1A ) , and , in unimolecular G-quadruplex , are connected by three intervening loops of variable length and sequence . G-quadruplexes can fold into a variety of topologies , differing in the relative orientation of the four guanine runs and in the arrangement of loop regions [4 , 5] . A delicate conformational equilibrium between these topologies depends on the length of the G-runs , the length and sequence of the loops , and the type concentration of alkali metal cations which are known to be crucial for the G-quadruplex formation [6–9] . Recently , using structure-specific antibodies and in-cell NMR , DNA G-quadruplexes have been shown to occur throughout the genome in living cells [10–12] , with a markedly higher density observed at the telomeric regions ( up to 25% of all G4 DNA ) [13] . Indeed , consisting of tandem repeats of the TTAGGG sequence and single-stranded 3’-overhang , vertebrate telomeric DNA is more likely to fold into G4 structures . G-quadruplex-forming sequences are also over-represented in other regulatory regions of the genome , including promoters [14] , immunoglobulin switches [15] , introns [16] , and 5’ untranslated regions [17] . Accordingly , G-quadruplexes are thought to be involved in regulation of DNA replication and transcription , genetic recombination , maintaining chromosome stability , and other fundamental cellular processes . With their unique molecular structure and biological significance , G-quadruplexes attracted much attention as drug-design targets [18] . In particular , since G4 structures have been shown to inhibit , among others , telomerase [19] and HIV integrase [20] , there is reason to believe that selective G4-stabilizing ligands could act as anti-cancer or anti-viral agents [21 , 22] . It has long been thought that , due to their layered structure , G-quadruplexes should show tendency to associate through stacking interactions between the external G-tetrads . This should be possible especially for parallel-stranded G-quadruplexes which have their external G-tetrads almost fully exposed to the solvent . As expected , the formation of higher order G4 structures was observed in a thermal denaturation study of parallel G-quadruplexes formed in a ‘bead-on-a-string’ fashion by long GGGT [23] and TTAGGG [24] DNA sequences . Furthermore , by using a combination of circular dichroism and mass spectrometry , it has been shown that aggregation of parallel G-quadruplexes ( composed of GGGT repeats ) depends upon the presence of flanking bases and therefore is likely to occur through stacking of the external G-tetrads , with G4 dimers and trimers being the most probable aggregated forms [25] . Analysis of dimerization equilibrium of the propeller-type G-quadruplexes with NMR spectroscopy confirmed the above finding and showed that out of the three possible end-to-end orientations ( see Fig 1A ) , the 5’-5’ stacking is strongly preferred [26] . Consistently , the 5’-5’ stacking arrangement is also found in all high-resolution NMR structures of G4 DNA dimers determined to date , including ( GGA ) 4 and GIGT ( GGGT ) 3 model sequences [27 , 28] , as well as the G4-forming regions of the N . gonorrhoeae pilE gene and the human CEB1 minisattelite [29 , 30] . The preference for the 5’-5’ mode is also reflected in the x-ray structures of parallel G-quadruplexes in which individual G4 units tend to stack with each other in the crystal lattice through the 5’-terminal G-tetrads [31–33] . It has been suggested that dimerization of G-quadruplexes provides additional stabilization of the individual G4 DNA units , and therefore might be important for packaging of G4-forming sequences [34 , 35] preferentially adopting parallel conformations . However , predicting whether particular G-quadruplexes are prone to aggregation ( e . g . , dimerization ) is far from trivial , because this process depends on several factors including the overall folding topology , the loop and flanking sequences and the concentration and type of cations [24 , 26] . In addition , the dimerization equilibrium can be modulated by small-molecule ligands , such as mesoporphyrin and naphthalene diimide derivatives . By associating with the 3’-terminal G-tetrad , these ligands favor the formation of the parallel G-quadruplexes , leaving the 5’-terminal G-tetrad free for favorable interaction with the other G4 unit [32 , 36] . Furthermore , some molecules , such as cationic porphyrins , trisubstituted acridines and berberines , were shown to increase the stability of G-quadruplex dimers by intercalating between interfacial G-tetrads [37–42] . Previous computational studies have shown that the preformed dimeric and trimeric assemblies of the parallel-stranded G-quadruplexes with 3’-5’ stacking orientations are stable on the time scale of 15 ns [43] . MM-PBSA calculations further suggested a significant stability of the parallel G4 dimers relative to the monomeric state [44] . Absolute stacking energies for simple models of isolated G4 cores and stacking interfaces have also been determined by force-field and quantum chemical calculations combined with structural database search [45] . However , despite this research , the origin of the driving forces for the dimer formation and specifically of the strong preference for the 5’-5’ stacking mode remains largely unexplored , making it difficult to predict and control the dimerization process [46] . Therefore , in the present work , we probe the determinants of the stability of G4 dimers by computing the free energy profiles for all possible π-stacked assemblies formed by the parallel telomeric G-quadruplexes , using explicit-solvent all-atom molecular dynamics simulations with a total simulation time of ∼100 μs . These calculations correctly reproduce the predominance of the direct 5’-5’ stacking mode over the remaining dimeric forms and show that dimerization equilibrium is governed largely by a competition between the electrostatic repulsion of the sugar-phosphate backbones and favorable counterion binding at the interface between the G4 monomers . We further show that this detailed knowledge can be used to predict shifts in the dimerization equilibrium in response to changes in salt concentration and addition of G4-binding ligands .
To examine the relative stability of possible dimeric structures formed by the parallel telomeric G-quadruplexes , we computed the free energy profiles for the main dimerization modes defined by three distinct end-to-end stacking orientations: 3’-3’ , 3’-5’ and 5’-5’ , hereinafter referred to as the 3-3 , 3-5 and 5-5 modes ( Fig 1A ) . As a collective coordinate describing the dimerization process , we used the separation distance between the centers of mass of the guanine cores of the two associating G-quadruplexes ( inset of Fig 1B ) . The distributions of the relative orientations between G4 units ( S1 Fig ) confirm association through cofacial stacking but also show that at longer distances G-quadruplexes sample the entire range of relative orientations , possibly facilitating the free energy convergence ( S2 Fig ) . The free energy profiles , G ( r ) , in Fig 1B reveal unexpectedly large differences in the stability of the three dimeric structures , with the 5-5 mode being by ca . 4 and 24 kcal/mol more stable than the 3-5 and 3-3 modes , respectively . By assuming that translation and rotational entropy loss is similar for the three modes , we estimated the corresponding dimerization free energies ( Table 1; see Methods ) and found that the 5-5 orientation is assumed with 99 . 9% and 3-5 with only 0 . 1% probability , while the 3-3 mode is virtually absent from the dimeric ensemble . Importantly , a clear preference for the 5-5 mode seen in our simulations , both CHARMM36 and parmbsc1 ( see S3 Fig ) , is fully consistent with the available experimental data . Indeed , by using NMR spectroscopy , it has been found that the parallel DNA G-quadruplexes composed of the GGGC , GGGT and GGA motifs ( PDB codes: 2LE6 and 1MYQ ) [26–28] , as well as the human CEB1 minisatellite ( 2MB4 ) and the bacterial pilE ( 2LXV ) G-quadruplexes [29 , 30] show a strong tendency to form dimers via the 5’-5’ stacking interface . Similar preference was observed for the human telomeric G-quadruplexes under molecular crowding conditions [47] and for TERRA G-quadruplexes [48 , 49] . Interestingly , the propeller-type telomeric G-quadruplexes also crystallize preferentially in the 5’-5’ stacking arrangement , as found in crystallographic studies [31] . The shape of the computed profiles with several free energy minima suggests diversity of dimeric structures , even for a given end-to-end orientation . Since the average distance between the adjacent G-tetrads in a guanine core is about 0 . 35 nm , the deepest minimum at 1 . 1 nm has to correspond to direct stacking between the terminal G-tetrads ( states labeled as ‘G-mediated’ in Fig 1B ) . In turn , the position of the local minima at 1 . 4 and 1 . 7 nm suggest that adenine residues may also be involved in mediating dimer formation ( ’A-mediated’ states in Fig 1B ) , especially as in telomeric G-quadruplexes , adenines tend to stack onto the 5’-G-tetrad [50 , 51] , and hence two minima are seen for the 5-5 mode ( minima II and III ) and one for the 3-5 mode ( II ) ( see also detailed structural analysis below ) . For separation distances from 1 . 9 to 2 . 9 nm , we observed various poorly-defined and non-specific interactions between the two monomers , and beyond 2 . 9 nm G-quadruplexes are no longer in contact yielding a plateau in the free energy profile . To confirm the above characterization of the free energy minima and investigate how structurally diverse are different dimerization modes , we performed cluster analysis of the MD-generated unbiased dimeric ensemble , separately for each of the six minima indicated in Fig 1B . This was done using the hybrid k-centers k-medoids clustering algorithm for all heavy atoms of the two guanine cores , with a RMSD cut-off of 0 . 3 nm [52] . Fig 2A shows schematic representations of dimeric structures identified by cluster analysis in the individual minima along with their equilibrium contributions to a given state . As expected , the lowest free energy minima ( labeled as I in Fig 1B ) correspond largely to the well-defined dimers with full stacking overlap between the two interacting G-tetrads ( ca . 2 . 2 nm2 , see S4 Fig ) providing maximum stacking stabilization . More specifically , in the dominant 5-5 G-mediated state ( 5-5 , I in Fig 2B ) , the relative polarity of the stacked G-tetrads allows for the largest possible stacking interaction between guanines with the pyrimidine ( i . e . , 6-member ) rings of one G-tetrad overlapping with the imidazole ( 5-member ) rings of the other and vice versa ( Fig 2D and S6 Fig ) . Additionally , in this alignment , dipole moments of stacked guanines are oriented roughly perpendicular with respect to each other leading to the most favorable electrostatic interaction between G-tetrads among the three possible dimerization modes ( Fig 2D ) . Notably , the same arrangement of guanines at the stacking interface was previously found experimentally for the 5-5 dimers of parallel G-quadruplexes formed both in aqueous solution [28] and in the crystal structure [31] , which further supports our predictions ( see S7 Fig a detailed comparison of the structures ) . For the other G-mediated dimers , the stacked guanines either almost do not overlap ( 3-5 , I ) or contact only via their imidazole rings ( 3-3 , I ) , suggesting less favorable interaction ( Fig 2D ) . Cluster analysis also revealed that , in the dominant 5-5 G-mediated mode , the two G-quadruplexes are twisted with respect to each other such that their 4-fold symmetric sugar-phosphate backbones form a regular alternating pattern ( Fig 2B ) . In particular , they are spatially shifted by one half-period , i . e . , ∼45° ( S8 Fig ) , which ensures that all the phosphate groups in one monomer are kept , on average , at the maximum possible distance from their nearest counterparts in the other monomer ( S9 Fig ) . This specific relative arrangement of monomers in the G-mediated dimer supposedly allows for minimization of electrostatic repulsion between the negatively charged backbone chains . Consequently , it was also observed in the crystal structure of parallel telomeric G-quadruplexes where it possibly contributes to the stability of the crystal lattice ( see S8 Fig for comparison of the relative arrangement o backbones ) [31] . In the 3-5 and 3-3 G-mediated dimers , the relative arrangements of the sugar-phosphate backbones are different and markedly less regular ( S8 Fig ) causing the neighboring phosphate groups on the two strands to be , on average , closer to each other compared to 5-5 ( S9 Fig ) . This is especially visible for the 3-3 mode , where ca . 3 pairs of phosphates are less than 0 . 6 nm apart . At the same time , we did not observe any significant dimerization-induced changes in the loop regions and sugar puckerings in individual G4 monomers that could account for the above difference ( see S10 and S11 Figs ) . Interestingly , the structure of G-mediated dimers in 5-5 mode also suggests additional stabilization by the outer ring formed by adenine residues stacking across the interface ( right panel of Fig 2B ) . Indeed , analysis of the adenine contact area confirms formation of , on average , ca . 2 cross-strand adenine-adenine contacts ( S4 Fig ) . This finding agrees well with the X-ray and NMR data showing 2 and 3 adenine-adenine stacking interactions , respectively , between the associated parallel G-quadruplexes [27 , 31] . Among the G-mediated structures identified by the cluster analysis , only a very small percentage—0 . 01% and 7% in the 5-5 and 3-5 binding mode , respectively—show a partial stacking overlap between the two G-tetrads ( ca . 1 . 68–1 . 84 nm2 ) which are shifted by ca . 0 . 41–0 . 49 nm with respect to each other ( see S12 Fig ) . In contrast , the remaining free energy minima ( II and III in Fig 1B ) are much more structurally diverse . They mainly correspond to structures mediated by one ( II , see Fig 2C ) or two ( III ) adenine layers with ca . 2–3 adenines per layer stacked between G-quadruplexes ( A-mediated states ) . However , in both minima , a significant fraction ( 30–49% ) of structures is found in which G-quadruplexes are only partially stacked onto each other showing the contact area of ca . 0 . 89–1 . 84 nm2 ( see S4 and S12 Figs ) . To identify main driving forces of dimerization process and the energetic determinants of the stability of G-quadruplex dimers , we have determined the enthalpy of dimerization , ΔH , and decomposed it , for each of the three stacking orientations , into contributions due to interactions between individual structural elements of the system . The contributions , shown as interaction matrices in Fig 3A , involve both electrostatic and van der Waals energies and were calculated by averaging the enthalpy differences between dimeric and dissociated states ( defined consistently with Fig 1B ) over the unbiased ensembles . Large positive values of the overall ΔH ( in the range of 185–720 kcal/mol ) suggest that the formation of the considered G4 dimers is enthalpically highly unfavorable and thus that it is driven by solvent-mediated entropic forces . The interaction matrices in Fig 3A demonstrate that the dominant force opposing the formation of the G-mediated dimers is a strong electrostatic repulsion of the two sugar-phosphate backbones ( ΔHBB1-BB2 ≈ 5 . 4–5 . 9 × 103 kcal/mol ) . This repulsion is effectively screened by potassium counterions ( ΔHK-BB1/BB2 + ΔHK-K ≈ −5 . 2–6 . 3 × 103 kcal/mol ) that , in the dimeric state , tend to localize in newly-created binding sites constituted by regions of strongly negative electrostatic potential between the G4 backbones ( see also discussion below ) . High absolute values of these nearly canceling contributions to ΔH indicate that the stability of G4 dimers involves a fine balance between competing electrostatic forces . This finding also provides a molecular-level explanation for the effect of salt concentration on the extent of G4 dimerization [26] and is consistent with previously reported participation of the loop-bound cations in stabilizing the folded state of G4 monomers [51] . Notably , dimerization does not significantly affect the K+-binding properties of the central channels that remain mostly occupied by counterions . Occasional binding of K+ in the additional binding site between the stacked G-tetrads is however less important for the stability of the dimers ( with maximum contribution ΔHK-G1/G2 ≈ −190 kcal/mol seen for 3-5 ) . Quite unexpectedly , a very similar balance of interactions and the critical role of counterions in stabilization is also found for the A-mediated states ( lower triangles in Fig 3A and S13 Fig ) , which are characterized by a greater separation between the sugar-phosphate chains . A lower stability of the A-mediated dimers ( see Table 1 ) arises from the fact that the repulsion between phosphates is not offset by attractive interactions to the same extent as in the G-mediated case . Specifically , as seen from S13 Fig , the A-mediated dimers lack additional stabilization provided by π-stacking interaction between the adjacent G-tetrads ( ΔHG1-G2 ≈ − 34–40 kcal/mol in the G-mediated case ) and by the thymine-backbone and adenine-backbone interactions ( ΔHT/A-BB ≈ − 10–100 kcal/mol in the G-mediated case ) . Energy decomposition in Fig 3 also shows that , despite a common compensation pattern , the three possible dimerization modes differ markedly in terms of individual contributions to ΔH . In particular , from Fig 3B it can be seen that , in the dominant 5-5 dimer , interphosphate repulsion is considerably ( by 9% ) weaker than in 3-3 and 3-5 , and thus might underlie the preference for the 5-5 dimerization mode . In order to examine molecular basis of the differences in interphosphate repulsion , we calculated the electrostatic energy density of cross-strand pairwise interactions between the phosphates as a function of the distance between them ( Fig 4A and S14 Fig ) . Low energy density at small P–P distances ( <1 . 4 nm ) in the 5-5 dimer indicates that the relatively weak electrostatic repulsion observed in this case can be attributed to the small number of very unfavorable close contacts between the phosphate groups at the dimer interface . This is also reflected in the 3D distribution maps in Fig 4B showing the largest spatial separation of the interfacial phosphates in the 5-5 dimer . In contrast , the 3-3 and 3-5 energy density profiles reveal that the number of close-contact repulsive interactions between the interfacial phosphates in the two remaining less stable dimerization modes is clearly greater , which is also depicted in the 3D distributions in Fig 4B . The electrostatic potentials surrounding G4 monomers , computed using the Poisson-Boltzmann approach [53] , independently confirm that the 5-5 mode is characterized by weakest phosphate-phosphate repulsion among the three dimers considered ( S15 Fig ) . Fig 3A indicates that some of the less dominant contributions to ΔH also favor the 5-5 dimerization mode . Notably , in this mode , the stacking interaction between the G-tetrads , ΔHG1-G2 , is by ∼5 kcal/mol more favorable than in both 3-3 and 3-5 , which results from a more favorable alignment of guanine dipole moments at the 5-5 interface ( see Fig 2D ) . Additional stabilization of the 5-5 dimer is provided by the cross-strand adenine-adenine interactions ( ΔHA1-A2 ≈ −18 kcal/mol ) that are missing in the 3-3 and 3-5 modes , as described above in the contact analysis ( see Fig 2A and S4 Fig ) . As shown by the inset in Fig 4A , the total interphosphate repulsion energy does not differ significantly between the 3-3 and 3-5 dimers , consistently with the values of ΔHBB1-BB2 in Fig 3A and ΔHBB-BB in Fig 3B . This then raises a question as to why the 3-5 mode is found in our free energy simulations to be by ∼20 kcal/mol more stable than 3-3 . A hint comes from the energy densities in Fig 4A , which show that association of parallel G4 units via their 3’-terminal G-tetrads leads to a number of energetically unfavorable van der Waals contacts between the phosphate groups ( non-zero density at distances <0 . 55 nm ) . Since this destabilization of the 3-3 dimer cannot be sufficiently compensated for by counterion screening , this suggests that the difference in the stability between the 3-3 and 3-5 modes might arise from disparate ion binding properties . The above analyses suggest that the differences in electrostatic screening of the phosphate groups at the stacking interface by K+ counterions might be responsible for a significantly higher stability of the 3-5 dimer over the 3-3 dimer . To investigate these differences in more detail , we first re-computed the binding free energy profiles for all three dimers in the presence of K+ counterions only , i . e . , at the effective K+ concentration lowered from the physiological concentration ( 0 . 15 M ) to about 0 . 04 M . From the free energy profiles in Fig 5A , it can be seen that , as the K+ concentration is decreased 2 . 5-fold , the dimers are destabilized by 2–7 kcal/mol , depending on the mode . This demonstrates directly that the presence of counterions is essential for G4 dimerization , in line with the experimental findings [26] . A 5 kcal/mol greater destabilization of the 3-5 than of the 3-3 mode confirms that K+ binding at the dimeric interface does in fact underlie a much higher stability of the 3-5 dimer , as was expected from the phosphate-phosphate electrostatic energy density . Unexpectedly , however , a decrease in the number of K+ ions at the 3-3 interface upon lowering the salt concentration ( Fig 5B ) is actually more pronounced than at the 3-5 interface ( 1 . 4 vs . 1 . 1 , respectively , for K+ present between the interfacial phosphates ) . This indicates that binding of individual K+ ions at the 3-5 stacking interface has to be energetically more favorable , so as to provide greater stability to the 3-5 dimer . The spatial distributions of K+ ions at the three dimeric interfaces , shown in Fig 5C and S17 Fig , provide a possible explanation for the above differences in the K+ binding strength . As can be seen , in the 3-5 mode , counterions are distributed non-uniformly at the stacking interface and penetrate deeper into the cleft between the two monomers , thereby being able to more effectively screen the electrostatic repulsion between the sugar-phosphate backbones . A large fraction of them ( 52% ) is found in the three separate sites located between the pairs of opposite double-chain-reversal loops of the G4 units . These well-defined sites ( Fig 5D ) , each formed by three phosphate groups—one from one G4 unit and two from the other—show a high cation-binding capacity and are on average occupied by ∼2 . 0 K+ ions at a given time . In contrast , in the 3-3 mode , the K+ distribution is more uniform , with interfacial ions spread over a larger area , which indicates less specific and weaker binding . Unlike in the two remaining dimers , in the 3-3 case , K+ ions are mostly found outside the interface and penetrate less readily between the phosphates groups . The reason is that very closely separated phosphate groups at the 3-3 interface ( Fig 4 ) do not allow counterions to bind between them and effectively mitigate the repulsive forces . The differences in hydration of the three interfaces are less pronounced; only in the 3-3 case , we observed a decreased hydration of the interfacial phosphates with respect to the monomeric state , probably due to above-mentioned involvement of some of the phosphates in direct interactions ( S18 Fig ) . The free energy profiles at increased concentration of counterions ( 0 . 3 M; Fig 5A ) further confirm the observed differences in K+-binding properties between the two dimers . Despite a 3–4 kcal/mol increase in the stability of the 3-5 mode , the number of K+ ions at the interface does not increase concurrently ( Fig 5B ) , indicating saturation of the binding sites already at lower concentrations . In turn , the 3-3 dimer remains unstable even at higher salt concentrations , even though the number of counterions non-specifically bound at the interface clearly increases . Because the distances between the phosphate groups across the 5-5 interface are generally greater than 0 . 6 nm they do not form particularly favorable K+-binding sites . As a result , the number of ions present at this interface is markedly lower than at the two remaining ones , with 28% of interfacial K+ found in 8 low-affinity binding sites ( Fig 5C ) . Notably , at the low salt concentration , the 5-5 dimer remains highly stable with Δ G bind ° = -13 . 0kcal/mol ( Fig 5A ) , which shows that the relatively small number of K+ ions is sufficient for screening the interphosphate repulsion between the monomers in the 5-5 dimer . Accordingly , adding more counterions to the solution reduces the preference for the 5-5 dimer , which is most pronounced at the low concentration , when its binding sites are already almost saturated . To test our conclusion that unfavorable interphosphate repulsion is responsible for destabilization of the two less preferred stacking modes , we recomputed the free energy profile for the formation of the most unfavorable 3-3 dimer , using a model aromatic ligand as a spacer to increase the distance between the interfacial phosphates . For this purpose , we used the cationic 3 , 4-Tetramethylpyridiniumporphyrazine ( 3 , 4-TMPyPz , Fig 6A ) , which was shown to selectively bind to human telomeric G-quadruplex DNA by stacking on the G-tetrad surface [54 , 55] . Because of the square shape , 3 , 4-TMPyPz mimics an additional aromatic plane between the two G4 units . Fig 6A shows that 3 , 4-TMPyPz present between the 3’-terminal G-tetrads indeed ensures the stability of the dimer relative to the dissociated state . As assumed , this actually originates from increased separation distance between the interfacial phosphates that reduces the electrostatic energy density at small P–P distances compared to the ligand-free 3-3 mode or even the 3-5 mode , however , not to the degree observed in the locally-optimal 5-5 mode ( S19 Fig ) . At the same time , the number of K+ ions at the interface decreases by 66% relative to the ligand-free 3-3 case ( see S20 Fig ) which , given a non-optimal phosphate arrangement , may partially explain only a moderate increase in the dimer stability ( by ∼ 6 kcal/mol ) . In this work , we examined the molecular determinants of the dimerization of two parallel-stranded G-quadruplexes ( G4 ) using molecular dynamics-based free energy calculations . We found that G-quadruplex dimers are formed almost exclusively ( 99 . 9% ) by direct aggregation of the 5’-end G-tetrads ( the G-mediated 5-5 mode ) , in agreement with all available experimental data [26–33] . At the same time , our simulations reveal that other dimeric G4 forms , particularly the 3-5 mode and even adenine-mediated dimers ( A-mediated ) , are also thermodynamically stable relative to the dissociated state . An important exception is the G-mediated dimer formed by aggregation of the 3’-terminal G-tetrads ( the 3-3 mode ) , which is found to be absent from the dimeric ensemble . The prevalence of the 5-5 dimer with the exposed 3’-terminal G-tetrads , that is unlikely to aggregate further , might explain a generally low tendency of G-quadruplexes to form higher-order oligomers [25 , 56 , 57] . Our results further indicate that , although the dimerization equilibrium is affected by a number of different enthalpic contributions , the observed aggregation propensities are primarily governed by a fine balance between the repulsion of the negatively-charged sugar-phosphate backbones and favorable counterion binding at the interface between the G4 monomers . Importantly , we found that the strong preference for the 5-5 mode results from a locally optimal arrangement of the backbones with largest inter-phosphate distances across the interface and , therefore , weakest electrostatic repulsion between the monomers . This finding provides an explanation for the experiment in which an additional phosphate group attached at the 5’-end of the parallel G-quadruplex prevents 5-5 dimerization [58] . In the two remaining less stable dimers , 3-5 and 3-3 , electrostatic repulsion between the monomers is similar and significantly larger compared to the dominant 5-5 dimer . We found that a much higher stability of the 3-5 mode can be attributed to stronger counterion binding at the specific binding sites formed by the phosphate groups at the interface between the G4 units . Another notable contribution that promotes the 5-5 dimer turned out to be the stacking interaction between the 5’-terminal G-tetrads , which is characterized by almost maximum possible overlap and a favorable relative arrangement of the guanine dipole moments , as has been also suggested previously [45] . A molecular-level understanding of the G4 dimer formation process provided by our study suggests methods for shifting the dimerization equilibrium by controlling the electrostatic repulsion-attraction balance and thereby opens up new opportunities for designing oligomeric G-quadruplex structures . Specifically , we predict that by doubling the concentration of K+ counterions we can significantly ( from 0 . 1 to 16% ) increase the equilibrium population of the 3-5 dimer which is especially suited to bind cations from aqueous solution . Moreover , our model indicates that the stability of the G-mediated dimers can be greatly enhanced by reducing the interphosphate repulsion which is the main destabilizing factor especially pronounced in the 3-3 and 3-5 cases . Indeed , increasing the separation distance between the interfacial phosphates by inserting a model aromatic ligand between the G4 units markedly improves the stability of the originally unstable 3-3 dimer relative to the monomeric state .
All simulated systems contained two monomers of the parallel G-quadruplexes with the human telomeric sequence d[AGGG ( TTAGGG ) 3] , whose initial structure with two K+ ions coordinated in the central channel was taken from the PDB database ( PDB id 1KF1 ) [31] . G4 dimers were solvated with 22826 TIP3P water molecules [59] in dodecahedron box with a cell vector length of 10 . 1 nm , at physiological ionic strength ( 150 mM KCl ) and , additionally , at two different salt concentrations , i . e . , at 300 mM KCl , and at 40 mM which corresponds to 42 K+ counterions only ( including 2 ions in the central channel ) . The CHARMM36 force field [60] was used for DNA and ions because , as previously shown , it reproduces the structure and stability of parallel G-quadruplexes in aqueous solution [50 , 61–64] . To test whether our conclusions are force-field independent , all dimerization simulations were additionally carried out using the AMBER parmbsc1 force field as a reference [65] . In additional simulations of the ligand-mediated dimer , the 3 , 4-TMPyPz ligand was parameterized using the CHARMM generalized force field ( CGenFF ) [66] and partial charges obtained from HF calculations in Gaussian [67] via Merz-Kollman ESP fitting , using the 6-31G* basis set ( see S1 Table for numerical values ) . The MD simulations were performed using Gromacs 5 . 0 . 4 [68] in the NPT ensemble , with the temperature kept at 300 K and using the v-rescale thermostat [69] and the pressure kept at 1 bar using Parrinello-Rahman barostat [70] . Periodic boundary conditions were applied in 3D , and electrostatic interactions were calculated using the particle mesh Ewald ( PME ) [71] method with a real-space cutoff of 1 . 2 nm and a Fourier grid spacing of 0 . 12 nm . A cut-off of 1 . 2 nm was used for Lennard-Jones interactions . All bond lengths were constrained using P-LINCS [72] for DNA and SETTLE [73] for water . The equations of motion were integrated using the leap-frog algorithm with a 2 fs time step . To study the relative stability of the dimers of the parallel G-quadruplexes with three different end-to-end stacking orientations ( dimerization modes ) , we calculated the corresponding free energy profiles using replica exchange umbrella sampling ( REUS ) . The calculations were carried out using the PLUMED 2 . 0 plugin [74] coupled to Gromacs . To generate the initial configurations for the REUS simulations , we first performed short equilibrium simulations ( <250 ns ) of the two G4 monomers initially fully separated , with the center of mass distance between their guanine cores ( the reaction coordinate , r; see inset in Fig 1B ) being in the range of 1 . 9–2 . 0 nm . Initially , the two monomers were oriented parallel to each other to promote their spontaneous association in one of the three considered dimerization modes . Indeed , in the case of the 3’-5’ and 5’-5’ modes , we observed spontaneous binding through base stacking interactions between the two interacting guanine planes ( the G-mediated states ) within 180 and 210 ns , respectively . To obtain the G-mediated state for the 3’-3’ mode that did not form spontaneously , we ran an additional steered MD simulation , in which the G4 monomers were driven towards each other during 100 ns using a moving harmonic potential with a force constant of 286 . 1 kcal/ ( mol⋅nm2 ) applied to the coordinate r . Next , to initially sample the full range of the reaction coordinate from the G-mediated bound state ( 1 . 0 nm ) up to a fully unbound state ( 3 . 5 nm ) , for each of the dimers , the two G4 units were forced to dissociate over 100 ns by applying the same moving harmonic potential as above . To ensure better convergence of the free energy profiles , in the critical range of r from 1 . 0 to 2 . 0 nm , the initial frames were taken alternately from the association and enforced dissociation trajectories , whereas in the range of 2 . 0–3 . 5 nm from the latter only . We used 25 uniformly distributed 0 . 1-nm separated REUS windows . In each of these windows the system was simulated for 0 . 5 μs , using the harmonic potential with a force constant of 286 . 1 kcal/ ( mol⋅nm2 ) to restrain the system along the reaction coordinate r . The exchanges between neighboring windows were attempted every 2 ps and the acceptance rate turned out to be ∼21% . No additional restraints were applied on the relative orientation of the associating G4 units . The free energy profiles were determined from the last 450 ns of thus obtained trajectories using the standard weighted histogram analysis method ( WHAM 2 . 0 . 9 ) [75] . Uncertainties were estimated using bootstrap error analysis taking into account the correlation in the analyzed ftime series . The dimerization free energies were estimated from the free energy profiles using a simple approach: Δ G d i m ° = - k B T ln ( 1 V 0 ∫ 0 R d r ∫ 0 π d θ ∫ 0 2 π d ϕ r 2 sin θ exp ( - G ( r ) k B T ) 1 4 π r 2 ) ( 1 ) where G ( r ) is the free energy profile taken directly from the REUS calculations , ( 4πr2 ) −1 is a radial correction term , V0 is the standard volume ( 1661 Å3 ) corresponding to the standard concentration of 1 M , R is the upper distance limit defining the dimeric state , kB is the Boltzmann constant and T the temperature [76 , 77] . All molecular images were created using VMD 1 . 9 . 2 [78] .
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Native DNA usually folds to form the canonical double helix , however , under certain conditions , it can also fold into other secondary structures . Some of the most interesting ones are G-quadruplexes ( G4 ) —compact DNA structures in which guanines assemble into multilayered tetrads , and whose formation has been reported at the ends of linear chromosomes ( telomeres ) and at different regulatory regions of the genome . Although structural and basic energetic properties , as well as some biological functions of G-quadruplexes are quite well understood , not much is known about their propensity to form agregated structures . A very high density of G-quadruplexes at telomeres along with their large exposed planar surfaces indeed favor G4 aggregation through end-to-end stacking , which might be important for the protection of telomeres and DNA packaging . In this research , using computer simulations , we provide insight into moleculsr origins of stability of the higher-order G-quadruplexes and explain in structural and energetic terms a strong preference for one particular end-to-end stacking orientation . Based on the recognized aggregation driving forces , we also suggest methods for controling the aggregation preferences openining up new opportunities for designing oligomeric G-quadruplexes .
|
[
"Abstract",
"Introduction",
"Results",
"Methods"
] |
[
"chemical",
"compounds",
"monomers",
"phosphates",
"electricity",
"nucleotides",
"electrostatics",
"materials",
"science",
"oligomers",
"thermodynamics",
"physical",
"chemistry",
"chemical",
"properties",
"polymer",
"chemistry",
"guanine",
"dimerization",
"chemistry",
"adenine",
"free",
"energy",
"physics",
"biochemistry",
"biology",
"and",
"life",
"sciences",
"materials",
"dimers",
"physical",
"sciences"
] |
2019
|
Why do G-quadruplexes dimerize through the 5’-ends? Driving forces for G4 DNA dimerization examined in atomic detail
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Riverine tsetse transmit the parasites that cause the most prevalent form of human African trypanosomiasis , Gambian HAT . In response to the imperative for cheap and efficient tsetse control , insecticide-treated ‘tiny targets’ have been developed through refinement of tsetse attractants based on blue fabric panels . However , modern blue polyesters used for this purpose attract many less tsetse than traditional phthalogen blue cottons . Therefore , colour engineering polyesters for improved attractiveness has great potential for tiny target development . Because flies have markedly different photoreceptor spectral sensitivities from humans , and the responses of these photoreceptors provide the inputs to their visually guided behaviours , it is essential that polyester colour engineering be guided by fly photoreceptor-based explanations of tsetse attraction . To this end , tsetse attraction to differently coloured fabrics was recently modelled using the calculated excitations elicited in a generic set of fly photoreceptors as predictors . However , electrophysiological data from tsetse indicate the potential for modified spectral sensitivities versus the generic pattern , and processing of fly photoreceptor responses within segregated achromatic and chromatic channels has long been hypothesised . Thus , I constructed photoreceptor-based models explaining the attraction of G . f . fuscipes to differently coloured tiny targets recorded in a previously published investigation , under differing assumptions about tsetse spectral sensitivities and organisation of visual processing . Models separating photoreceptor responses into achromatic and chromatic channels explained attraction better than earlier models combining weighted photoreceptor responses in a single mechanism , regardless of the spectral sensitivities assumed . However , common principles for fabric colour engineering were evident across the complete set of models examined , and were consistent with earlier work . Tools for the calculation of fly photoreceptor excitations are available with this paper , and the ways in which these and photoreceptor-based models of attraction can provide colorimetric values for the engineering of more-attractively coloured polyester fabrics are discussed .
There are two forms of HAT , each caused by a different subspecies of Trypanosoma brucei . A small minority of cases ( ca . 2% ) comprise an acute disease termed Rhodesian HAT that occurs in Eastern and Southern Africa [1] . These cases are caused by T . b . rhodesiense for which savannah , or Morsitans species group , tsetse are the most important vectors . Because Rhodesian HAT is a zoonosis , tsetse control is central to disease control [6] . Large , insecticide-treated blue and/or black cloth panels with accompanying odour lures , and insecticide-treated cattle , have both proved effective in controlling savannah tsetse [7 , 8] . However , the vast majority of HAT cases ( ca . 98% ) comprise a chronic disease termed Gambian HAT that occurs in Central and Western Africa [1] . This form of the disease is caused by T . b . gambiense and chiefly transmitted by riverine , or Palpalis species group , tsetse . Of these , G . fuscipes spp . are estimated to transmit 90% of all Gambian HAT [3 , 5] . Unlike Rhodesian HAT , Gambian HAT is considered an anthroponosis , and case detection and treatment programmes are the predominant method of disease control . This is because control methods developed for savannah tsetse are not cost effective or logistically feasible for the control of riverine tsetse in remote , rural locations , and where cattle rearing densities are low [3 , 4 , 6] . However , case detection and treatment programmes suffer from diagnostic insensitivity and incomplete attendance of the local population for screening , causing under-detection and allowing disease transmission to be sustained [9] . Tsetse control , meanwhile , has proved effective in reducing tsetse numbers below those required for HAT transmission , and sustaining such a programme , perhaps in concert with active case detection and treatment , might achieve local elimination of the disease [4 , 5] . Therefore , concerted efforts have been underway to improve the cost and efficiency of control devices for riverine tsetse so that they might contribute to efforts to eliminate Gambian HAT ( e . g . [10 , 11 , 12 , 13 , 14 , 15 , 16] ) . Pronounced differences are evident in the behaviour of riverine and savannah tsetse , with the former less repelled by visual and olfactory stimuli emanating from humans , more likely to feed from smaller hosts such as reptiles and small mammals , and generally less responsive to odour lures [7] . In addition , although larger targets are most attractive to both riverine and savannah tsetse , the former are relatively more attracted to smaller visual targets than the latter [7 , 12] . These behavioural differences are probably not the result of differences in tsetse physiology . Instead , narrow and densely vegetated riverine habitats mean that odour plumes are of limited utility in host seeking , and the reduced probability of encountering hosts in such habitats necessitates less selectivity when one is encountered [7 , 17] . Identification of these crucial behavioural differences has allowed the development of ‘tiny targets’ for riverine tsetse , which comprise a 0 . 25 m x 0 . 25 m blue polyester panel adjacent to a 0 . 25 m x 0 . 25 m black polyethylene mosquito net panel , with both panels impregnated with deltamethrin insecticide [5 , 10 , 12 , 14] . The blue fabric panel serves to attract tsetse , whilst the mosquito net panel is thought to intercept circling flies , overcoming their reduced tendency to alight directly on small visual targets [12] . Versus the large devices used for savannah tsetse , tiny targets offer considerable savings in costs associated with materials , transport , and deployment , but with only a small penalty in terms of reduced attractiveness to tsetse [10 , 12] . As a result of these improvements , tsetse control can now form an important component of Gambian HAT control [4 , 5 , 16] . As an added benefit , such cheap and efficient technology might permit community-led control operations , and through them some protection against disease resurgences that have resulted from the neglect of control operations at times of political instability ( e . g . [2] ) . Tiny targets are undoubtedly a hugely important innovation that already permits cost effective tsetse control , but their efficiency might be improved still further through optimisation of the colour of the attractive polyester panel . Multiple large scale field studies pre-dating the development of tiny targets established that colour was an important determinant of tsetse attraction , and that phthalogen blue-dyed cotton was highly attractive to tsetse [8 , 14 , 18 , 19] . Phthalogen blue cotton is now reportedly difficult to obtain , whilst polyester is the material of choice for tiny targets because it is lighter , more robust under field conditions , and holds insecticide more effectively [14] . Although the blue polyester used in tsetse control devices is sometimes referred to as ‘phthalogen blue’ polyester , phthalogen blue dye can only be applied to cotton , and the reflectance spectra of such polyester fabrics differ subtly from that of the original cotton material [14 , 20] . Experiments conducted during the development of tiny targets found that identically sized panels of ‘phthalogen blue’ polyester frequently attracted significantly less tsetse than phthalogen blue cotton , and the numbers of tsetse caught at these targets was often only ca . 50% of those caught at a phthalogen blue cotton standard [14] . The implication of this is clear: identification of polyester fabrics that achieve the same level of efficiency as phthalogen blue cotton has the potential to as much as double the efficiency of tiny targets . Although such a polyester fabric could not be identified through screening a wide selection of differently coloured polyesters in field trials [14] , I argue that an attractively coloured fabric can be deliberately engineered if the mechanistic basis of tsetse attraction is understood . On that basis , polyester dye concentrations and combinations that would best exploit the implicated mechanism can be identified , using techniques based on those already employed to colour engineer fabrics for the human eye [21 , 22 , 23] . Visual information is received by an animal’s photoreceptors , and it is the responses of these photoreceptors that provide the inputs to visually guided behaviour and the basis of colour perceptions [23 , 24 , 25] . For this reason , colorimetric approaches to match colours for the human eye do not attempt to match the desired reflectance spectrum , but instead design a reflectance spectrum that evokes the same response in the human cone photoreceptors [23] . Since flies differ from humans in the number and spectral sensitivity of their photoreceptors , human colour perceptions are not useful in understanding the visual behaviour of flies . Fortunately , photoreceptor spectral sensitivities are well established for Musca and Calliphora spp . , and are considered typical of all higher flies [26 , 27 , 28] . Methods to model photoreceptor responses to measured reflectance spectra using such sensitivity functions are now well established [24 , 25] . Each ommatidium in the dipteran compound eye contains eight photoreceptors ( also called retinula cells ) , named R1-R8 . R1-6 are broadband photoreceptors that are similar across all ommatidia in the eye , and they make output synapses in the lamina of the optic lobe [26 , 28] ( see Fig 1 ) . Photoreceptors R7 and R8 are stacked centrally within each ommatidium and bypass the lamina to make output synapses in the medulla of the optic lobe . Excluding specialised areas of the eye such as that for the detection of polarised light , R7 and R8 each occur in two forms [26 , 28 , 29] . In 70% of ommatidia the ‘y’ ( yellow ) form occurs , where C40 carotenoid screening pigments are present in the R7 rhabdoms and these shape the sensitivity of both R7y and R8y receptors [26 , 28 , 30 , 31] ( Fig 1A ) . In the remaining 30% of ommatidia , the ‘p’ ( pale ) form of these photoreceptors occurs [26 , 28 , 30 , 31] ( Fig 1A ) . Based on these spectral sensitivities and field data from previously published studies of savannah and riverine tsetse species [14 , 18 , 19] , attraction to visual targets of different colours was modelled using calculated photoreceptor responses as predictor variables . In these studies , tsetse attraction could be explained by a mechanism to which the R7y photoreceptor contributes positively , and the R8y and R7p receptors contribute negatively ( see Fig 1A ) [21] . Such a mechanism explains the greater attractiveness of blue and black fabrics versus alternatives , and the marked unattractiveness of UV reflecting fabrics [8 , 14 , 18 , 19] . These receptor-based models , therefore , permit a colorimetric approach to fabric colour engineering for improved attractiveness to tsetse , but to facilitate that aim some further exploration is required . Tsetse photoreceptor sensitivities are indeed broadly similar to those of Musca and Calliphora , as was assumed in earlier work [29] . However , differences in detail deserve consideration and may have ramifications for photoreceptor-based behavioural explanations . Electrophysiological work on laboratory-reared G . m . morsitans found that the R1-6 photoreceptor class had its ‘green’ sensitivity peak at approximately 10 nm longer than the equivalent receptor class of Musca [29] ( Fig 1B ) . In addition , the R7y and R8y photoreceptors of G . m . morsitans had broader sensitivity functions with greater sensitivity to blue wavelengths than those of Musca , due to a complete lack of diet-derived C40 carotenoid screening pigment in the R7y rhabdoms [29] ( Fig 1C ) . Biochemical analysis of retinae from G . palpalis palpalis reared on a different diet did recover C40 carotenoids at about one third the concentration normally found in Calliphora , which would likely result in somewhat screened photoreceptor responses closer to the generic sensitivity functions , but no accompanying electrophysiological work was conducted [29] . Therefore , the differing R7y and R8y sensitivities of G . m . morsitans appear to have resulted from diet . However , due to the unique life history of tsetse in which nutrition is only via animal blood and larvae do not feed , it is certainly plausible that spectral sensitivities vary between the extremes of screened and unscreened sensitivities in wild populations , according to the vertebrate hosts locally available . In addition , earlier work assumed that all photoreceptor responses could contribute to behaviour through a single mechanism that summed their weighted excitations ( c . f . [32] ) , partly because recent work on Drosophila has demonstrated that all receptor classes can contribute to colour discrimination in that species [33] . However , the R1-6 and R7-8 photoreceptors are anatomically distinct and have long been hypothesised to supply segregated , parallel processing channels in which the R7-8 photoreceptors provide chromatic information contributing to colour vision , and the R1-6 photoreceptors provide achromatic ( luminance ) information [27 , 34 , 35 , 36] . Furthermore , conditioned colour discrimination experiments with the blowfly Lucilia sp . suggest comparison of R7p versus R8p , and R7y versus R8y responses in separate opponent channels for the two types of ommatidia , with categorical encoding of just four discriminable colours based upon the signs of each of these photoreceptor response comparisons [37] . Although this categorical model of colour perception is yet to be shown experimentally for any fly other than Lucilia , it has become the most widely applied model of fly colour vision ( see [27] , and references therein ) , and should also be considered for tsetse . The principal aim of the work reported in this paper was to develop photoreceptor-based models of tsetse attraction by exploring modified assumptions about the visual sensitivities of tsetse and the neurophysiological organisation of their visual system . This was done using an existing set of field data on the attraction of G . f . fuscipes to fabric panels of a range of different colours , since this species is considered the most important vector of Gambian HAT and the study provided the only detailed investigation of tsetse attraction to tiny targets of different colours [14] . The goal was not to determine which assumptions about the tsetse visual system were closest to the true situation in the population under investigation , but to find out whether robust colorimetric principles for fabric optimisation could be determined regardless of these assumptions . The work has direct application in the engineering of polyester fabrics for optimal tsetse attraction , and to facilitate this , calculation tools are provided with this paper and the ways in which they can be employed in fabric colour engineering are explained .
Analyses were performed on a large dataset reporting the attraction of G . f . fuscipes to a total of 37 tiny targets of different colours in 15 separate experiments conducted on Chamaunga Island , Lake Victoria , Kenya [14] . Unlike the tiny targets employed in control operations where fabric and net panels are impregnated with insecticide , tsetse were sampled in this experimental study using grids of electrocuting wires overlaying the fabric and net portions of the target [14] . The fabrics tested in these experiments included phthalogen blue and black cotton fabrics , and a variety of polyesters including examples of ‘phthalogen blue’ and royal blue polyesters similar to those used in the production of tsetse traps and targets [14] . This dataset was one of three analysed in initial attempts to develop a receptor-based model of tsetse attraction [21 , 22] . Each experiment compared tsetse catches at a sample of five tiny targets of different colours , one of which was always a phthalogen blue cotton standard [14] . The experimental design comprised two Latin squares of five days by five sites , and the total number of male and female tsetse caught at each target over the duration of the experiment was directly reported ( ‘sample sizes’ in the right hand columns of tables 1 and 2 in the source publication ) [14] . This contrasts with the reporting of ‘catch indices’ alone ( the de-transformed mean catch of each target expressed as a proportion of that at the phthalogen blue cotton standard ) , which were used in initial receptor-based modelling work [21] . The reflectance spectrum for each fabric in the original study was provided by the authors as online supplementary materials [14] . These spectra quantified fabric reflectance from 190 nm to 900 nm , at 10 nm increments . Photoreceptor excitations can be computed from the reflectance spectra of the stimuli of interest and a number of additional input functions [21 , 24 , 25] . Reflectance spectra for each tiny target , It ( λ ) , were linearly interpolated to achieve 2 nm resolution , and transformed to express reflectance as a proportion . Green leaves were assumed to provide the background to these targets , and this assumption is justified by photographs of similar tsetse-sampling equipment set up for field trials [12 , 13] . The typical green leaf function of [25] , linearly interpolated for 2 nm resolution , was thus employed as the background reflectance spectrum , Ib ( λ ) . As a daylight illuminant function , D ( λ ) , the CIE standard D65 was employed , linearly interpolated for 2 nm resolution , converted to photon units as in [24] , and normalised to a maximum of unity . In this analysis , all functions were rounded to three decimal places . A spreadsheet that includes these functions and conducts the calculations described is provided ( S1 File ) . In addition to the above , spectral sensitivity functions , S ( λ ) , are required for each photoreceptor class , and an important aim of this study was to investigate two extreme assumptions about tsetse spectral sensitivities . In earlier work , well-established sensitivity functions for Musca and Calliphora were employed for this purpose , extracted from [26] using Data Thief software [38] ( Fig 1A ) . For the current work , these functions were extrapolated beyond the original 310–600 nm range . In addition , measured R1-6 , R7y , and R8y spectral sensitivities for G . m . morsitans were extracted from [29] using Data Thief , and the available data points connected by linear interpolation , before extrapolation and combination with data from the generic functions for Musca and Calliphora . The full sensitivity spectra are illustrated in Fig 1B and 1C , and further details on their construction are provided in S1 Text . Based on the above input functions , the effective photon catch ( P ) of reflected light from a given tiny target , was calculated for each of a tsetse’s five photoreceptor classes ( r ) , as follows: Pr=Rr∫300700It ( λ ) Sr ( λ ) D ( λ ) dλ R is a range sensitivity factor that adjusts the sensitivity of each photoreceptor such that background stimulation would elicit a half maximal response in each photoreceptor class , representing photoreceptor adaptation: Rr=1/∫300700Ib ( λ ) Sr ( λ ) D ( λ ) dλ The resulting photon catches were non-linearised to represent the transduction process in each photoreceptor , providing excitation ( E ) based upon: Er=Prn/ ( Prn+1 ) The exponent , n , was set to 1 . 0 , as occurs in fully light adapted photoreceptors [39] ( c . f . [25 , 40] ) . Photoreceptor excitations calculated as above were used in some models of tsetse attraction . In addition , and in order to compare structured models of photoreceptor excitation processing , a number of additional predictor variables were computed from calculated photoreceptor excitation values . These predictor variables were chosen to represent specific hypotheses about the organisation of the fly visual system , and not to evaluate all possible organisations of opponent processing and determine the most likely ( c . f . [40] ) . To represent the potential organisation of photoreceptor excitations into separate opponent mechanisms for the R7 and R8 photoreceptors of ‘y’ and ‘p’ type ommatidia [27 , 37] , a range of indices were calculated and evaluated ( described in S2 Text ) . The index that provided the best fit to the data and is presented in the main text was calculated as follows: Opps=ER7s/ER8s Where s denotes the ‘y’ or ‘p’ opponent system . In order to represent the categorical encoding of these separate opponent mechanisms [37] , the above index was re-coded as 0 if <1 . 0 , and 1 otherwise . The evaluation of models including these categorical predictor variables is fully described in S2 Text . Finally , the calculated excitations of the R7-8 photoreceptors were each expressed relative to the summed excitation across all four such receptors , in order to represent a generic encoding of colour information separated from luminance: Relr=Er/ ( ER7p+ER7y+ER8p+ER8y ) Where r here denotes photoreceptors R7p , R7y , R8p , or R8y only . The availability of actual tsetse catches , rather than catch indices alone , permitted a refined statistical analysis versus previous work [21] . In overview , the aim was to explain tsetse catches in the complete dataset , based upon the photoreceptor excitations that would be elicited when a tsetse viewed each tiny target . Analyses were conducted in four separate blocks comprising separate analyses of male and female tsetse catches , and within these , separate analyses using photoreceptor excitations calculated using screened ( Fig 1B ) and unscreened ( Fig 1C ) sensitivity functions . The original dataset comprised 15 separate experiments and it was logical to assume that tsetse catches at different tiny targets within the same experiment would be related . This might happen if , for example , the number of tsetse in the local area varied between experiments . For this reason , Generalised Estimating Equations were employed to account for these experimental clusters within the complete dataset [41 , 42 , 43] . These analyses were implemented using the GENLIN procedure of IBM SPSS version 22 . 0 . 0 . 2 ( IBM Corp . , Armonk NY , USA ) . I chose the total number of tsetse sampled at each tiny target over the course of an experiment as the response variable , and since this variable is a count , it was assumed to follow a negative binomial distribution . The negative binomial distribution provides an alternative to the Poisson distribution for count data where the variance cannot be assumed to equal the mean [43] . The negative binomial distribution is specified by a dispersion parameter , k , which was estimated for the saturated five photoreceptor predictor model in each analysis block via the GENLIN procedure , and then fixed at that value for investigation of all models within that analysis block ( i . e . all models explaining the same response variable based upon subsets of the same predictors , or indices calculated from them; see S2 Text ) . Since each experiment used two Latin squares of five days by five sites for each tiny target colour , the total tsetse catch of each tiny target was assumed to be equally related to that of every other within the same experiment ( i . e . effects of relative target position and local fly depletion within each experimental cluster were controlled for by its design ) . As such , the correlation matrix representing this dependence within each experimental cluster was specified as exchangeable . A log link function was specified , similar to earlier analyses [14 , 19 , 21] . An information-theoretic approach to model evaluation and selection was employed [44] . This was based upon the corrected quasi-likelihood under independence model criterion , QICC , which is a modification of AIC ( Akaike’s Information Criterion ) for use with GEE that is corrected for small sample sizes with a stricter penalty for model complexity [43 , 45 , 46] . In order to simplify the main text of this manuscript , model selection methods and results are fully described in S2 Text , whilst the best-fitting models from each stage of analysis are described in the main text .
For the 37 fabric reflectance spectra under investigation , photoreceptor excitation values calculated with the tsetse-like R1-6 sensitivity function ( Fig 1B and 1C ) were strongly correlated with those calculated using the generic R1-6 sensitivity function ( Fig 1A ) , ( Spearman’s rank correlation; rs = 0 . 992 , p<0 . 001 , N = 37 ) . Similarly , photoreceptor excitation values calculated using the unscreened , G . m . morsitans R7y sensitivity function ( Fig 1C ) were strongly correlated with those calculated using the screened , generic R7y sensitivity function ( Fig 1B ) , ( rs = 0 . 988 , p<0 . 001 , N = 37 ) ; and the same was true of unscreened and screened R8y sensitivity functions ( Fig 1C and 1B respectively; rs = 0 . 951 , p<0 . 001 , N = 37 ) . As such , modified spectral sensitivity assumptions resulted in only subtle differences in the excitation values calculated for individual photoreceptor types . Generic sensitivity functions for the R7 and R8 photoreceptors ( with carotenoid screening of R7y and R8y ) , and the R1-6 sensitivity function based upon data from G . m . morsitans , were used to represent the hypothesised spectral sensitivities of a non-carotenoid-deprived tsetse ( henceforth ‘screened sensitivities’; Fig 1B ) . Substitution of the unscreened R7y and R8y sensitivity functions recorded from G . m . morsitans into this set represented the known spectral sensitivities of a carotenoid-deprived tsetse ( henceforth ‘unscreened sensitivities’; Fig 1C ) . Within each complement of assumed sensitivities , particularly strong correlations ( rs>0 . 9 ) were present between R1-6 excitations and both R8p and R8y excitations , and between R7y and R8p excitations ( Tables 1 and 2 ) . However , these correlations were generally stronger within the unscreened sensitivity set , which also included strong correlations between R1-6 and R7y excitations , and R8y and R8p excitations ( Table 2 ) . I first modelled G . f . fuscipes attraction based upon weighted combinations of between one and five photoreceptor excitations computed using screened sensitivity functions . The best-fitting model common to the male and female datasets employed the excitations of R7y , R7p , and R8y as predictor variables ( Table A in S2 Text ) . The coefficients that translate these photoreceptor excitations into the predicted natural log-transformed tsetse catch of a tiny target are given in Table 3 . These coefficients indicated a positive influence of R7y , and negative influences of R7p and R8y , on tsetse attraction ( Table 3; S1 and S2 Figs ) . I next repeated this analysis using photoreceptor excitations computed using unscreened sensitivity functions . Although this analysis provided moderate support for the +R7y -R7p -R8y model , the best-supported model common to the male and female datasets included the excitations of R1-6 , R7p , R8p , and R8y ( Table B in S2 Text ) . Like the +R7y -R7p -R8y model implicated using screened sensitivity functions , these models included significant negative coefficients for R7p and R8y responses ( Table 3 ) . However , rather than including a positive effect of R7y excitation , these models included positive effects of R1-6 excitation and an additional negative ( though not always significant ) effect of R8p excitation ( Table 3 ) . Due to the similarity between unscreened R7y and R1-6 sensitivity functions at short wavelengths ( Fig 1C ) , and the enhanced negative effect of R8p and unscreened R8y at longer wavelengths ( Fig 1C; Table 3 ) , the functional effect of this combination of predictors was qualitatively similar to that of the three predictors in the screened models ( see also S1 Fig , S2 Fig ) . I next evaluated a range of models that incorporated the structured processing of photoreceptor excitations . In contrast to the simple , weighted photoreceptor excitation models above , the most widely applied model of fly colour vision is based upon categorically encoded R7y versus R8y , and R7p versus R8p opponent mechanisms [27 , 37] . However , such categorical predictor variables alone provided a poor fit to the attraction data ( Table C in S2 Text ) . When R1-6 excitations were added to these models to represent the evaluation of luminance separate to the categorical encoding of colour , their fit was improved substantially . Despite this , none of these models was competitive with the weighted photoreceptor excitation models ( Table C in S2 Text ) . The next set of models considered the possibility that photoreceptor excitations were processed in the previously described opponent channels , but without categorical encoding of their outputs . Calculated in a variety of different ways ( S2 Text ) , a pair of opponent comparisons alone provided a relatively poor fit to the data that was not competitive with the weighted photoreceptor excitation models ( Table D in S2 Text ) . However , the fit of these models was greatly improved by the addition of the R1-6 photoreceptor excitation representing a separate luminance channel ( Table D in S2 Text ) . The fit of these models to the data was better than the weighted photoreceptor excitation models when either screened or unscreened photoreceptor sensitivities were assumed . Further , these models included the best supported of all models examined for the male data ( Table D in S2 Text; S1 and S2 Figs ) . In all such models , R1-6 excitation had a significant , negative coefficient ( Table 4; S1 Table ) . The various representations of the ‘p’ opponent system had a significant negative coefficient ( Table 4; S1 Table ) , indicative of a negative effect of R7p excitation and a positive effect of R8p excitation on attraction . The effect of the ‘y’ opponent system was not always significant in the best-fitting model of this kind ( Table 4 ) , but was in models that represented this opponent interaction using different computations ( S1 Table ) . Nevertheless , the sign of the ‘y’ opponent system coefficient was positive in all models ( Table 4; S1 Table ) , consistent with a positive effect of R7y excitation , and a negative effect of R8y excitation , on tsetse attraction . Thus , these models shared similarities with the weighted photoreceptor excitation models in terms of the nature of the effect of individual classes of photoreceptor on tsetse attraction ( Table 3 ) Finally , I analysed a model in which the relative excitations of the four R7-8 photoreceptors were used as predictor variables , intended to represent a generic encoding of colour information separated from luminance ( Table D in S2 Text ) . Without the addition of R1-6 excitation to represent a separated luminance channel the fit to the data was poor . However , with the addition of R1-6 excitation this was among the best-fitting models for male data and was the strongest supported of all models for female data ( Table D in S2 Text; S1 and S2 Figs ) . Interpretation of the coefficients from such analyses is complicated because relative photoreceptor excitations are proportions , and thus a change in any relative photoreceptor excitation must cause a change in at least one other . Thus , coefficients are presented for models with each relative excitation value excluded in turn . The interpretation of the coefficient for each relative photoreceptor excitation is thus the change in predicted natural log-transformed tsetse catch resulting from an increase in the relative excitation of the photoreceptor in question with a concomitant decrease in that of the omitted photoreceptor ( Table 5 ) . In all models , the R1-6 luminance channel was a significant negative predictor of attraction ( c . f . Table 4 ) . A negative influence of relative R7p excitation on attraction was strongly supported by its negative coefficient in all of its models , meaning that an increase in the relative excitation of R7p and a decrease in that of any other photoreceptor , resulted in decreased tsetse attraction; this is also supported by the positive coefficients of all relative excitations where R7p was excluded , meaning that an increase in relative excitation of any photoreceptor at the expense of R7p increases tsetse attraction ( Table 5 ) . The opposite pattern was observed for photoreceptor R7y , strongly supporting a positive influence of relative R7y excitation on tsetse attraction ( Table 5 ) . Relative R8p and R8y excitations had a less clear-cut influence on attraction , with the sign of their coefficients depending on the photoreceptor omitted ( Table 5 ) . Thus , once again , the individual contributions of the R1-6 , R7y and R7p classes were similar to those suggested by the previously considered models . It is beyond the available data to evaluate the true physiological mechanism of tsetse attraction , and the value of the above models is in their similar predictions about the contribution of individual photoreceptor classes to attraction: the best-fitting models supported negative influences of R7p and R8y excitation on attraction , and positive influences of R7y excitation on attraction ( Tables 3–5 ) . All models in which R1-6 excitation provided a separate luminance channel suggested a negative influence on attraction ( Tables 4 and 5 ) . In order to illustrate these common principles I conducted a graphical analysis of experiment eight reported by [14] which compared the tsetse catches of five fabrics with particular applied importance . These comprised two traditional cotton materials that were available from previous studies of tsetse target design , a standard phthalogen blue ( standard ) and a black ( black 1 ) ; and three polyester materials used in the production of modern tsetse targets , a phthalogen-like blue ( blue 7 ) , a royal blue ( blue 8 ) , and a black ( black 2 ) . The reflectance spectra for these fabrics are shown in Fig 2 , and the calculated excitations of screened and unscreened fly photoreceptors to these fabrics , expressed both as excitation values for photoreceptors R1-8 , and as relative excitations across the R7-8 photoreceptors , are shown in Fig 3 . Fig 4 shows the natural log-transformed catches of female G . f . fuscipes ( only ) from this single experiment , and the different tiny targets are now re-ordered according to their relative attractiveness . The coefficients from the best-fitting GEE models ( Tables 3–5 ) , have been used to compute predicted log-transformed catch values for each tiny target based upon the photoreceptor excitation values in Fig 3 . In this experiment , less tsetse were caught than the models predicted ( see also S1 Fig and S2 Fig for an illustration of such experimental clustering across the complete dataset ) , but the pattern of target attractiveness was effectively predicted by all candidate models . A qualitative analysis of the factors that bring about this pattern provides a means to illustrate the similarity of the models generated in this analysis , and general principles for the future optimisation of fabrics for tsetse attraction . Firstly , the best-supported models ( excluding the weighted photoreceptor excitation model using unscreened spectral sensitivities; Tables 3–5 ) , generally indicate that fabrics are most attractive to tsetse when they maximise relative excitation of the R7y and possibly R8p photoreceptors , and minimise that of the R7p and R8y photoreceptors . In practical terms this means reflection of light between ca . 380 nm and ca . 500 nm , and minimal reflection outside of this range ( ignoring reflection at >650nm , to which flies are not sensitive ) , ( Fig 1 ) . This pattern of reflectance and photoreceptor excitation is strongly evident for the phthalogen blue cotton standard fabric in Figs 2 and 3 , and versus this pattern it can clearly be seen that the black fabrics elicit relatively higher excitation in the R7p photoreceptor than in R7y or the R8 photoreceptors , providing an explanation for their lesser attractiveness ( Figs 3 and 4 ) . Of the blue fabrics , blue 8 differs from the others in that it reflects maximally at a shorter wavelength , resulting in greater reflectivity of UV wavelengths ( Fig 2 ) , and higher relative excitation of R7p ( Fig 3 ) . This might explain its reduced attractiveness to tsetse versus the phthalogen blue standard ( Fig 4 ) . Blue 7 , meanwhile , appears to provide a relatively attractive ratio of excitation in R7y and R8p , versus that in R7p and R8y , although this pattern is not as marked as for phthalogen blue cotton ( Fig 3 ) . A second factor determining attractiveness implicated by the models presented is that of overall brightness . In the best models using weighted photoreceptor excitations this comes about because negative coefficients sum to a greater absolute value than positive ones in each model ( Table 3 ) . Therefore , if all photoreceptors responded equally to a given stimulus , predicted natural log-transformed tsetse catch would have a negative relationship with the strength of their excitation ( i . e . negative effects dominate , and reducing them even at the expense of positive effects makes the target more attractive ) . In the models where colour is represented separately to luminance ( Tables 4 and 5 ) , the broadband R1-6 photoreceptor’s excitation is always a negative predictor of attraction . This principle can explain the lesser attractiveness of blue 7 versus the phthalogen blue standard because this fabric elicits strong responses in all photoreceptors including R1-6 ( Figs 3A and 4 ) . The same principle in reverse explains the relatively higher attractiveness of the black fabrics than might be expected from the pattern of excitation across the R7 and R8 photoreceptors alone ( Fig 3 ) . The rising reflectance functions of blue 8 and black 2 above 650nm are immaterial , because flies have no sensitivity to light in this region of the spectrum ( Figs 1 and 2 ) . Thus , regardless of whether screened or unscreened sensitivity functions are assumed , or which photoreceptor-based model of attraction is chosen , the recommendations for fabric optimisation are that: ( i ) reflectance should be minimised in the regions that strongly excite R7p and R8y ( < ca . 380 nm , and > ca . 500 nm ) relative to the regions that most strongly excite R7y and R8p ( ca . 380 nm < > ca . 500 nm ) ; and ( ii ) the overall reflectance of the fabric should be relatively low .
Identifying the true photoreceptor basis of tsetse attraction within the G . f . fuscipes population investigated in the original field study was an aim beyond the data available . This is partly because the stimuli investigated in that experiment were chosen to prospect for attractive fabrics and not to evenly sample all regions of fly colour space in order to determine the mechanism of visual attraction . Thus , unravelling the photoreceptor basis of tsetse attraction will require dedicated experiments , but the models presented in this work are expected to capture important principles of these visual mechanisms useful in the applied context . Many of these principles were evident across models with different underlying assumptions . Firstly , the best-fitting models from each stage of analysis were chromatic , in that they incorporated excitation values for more than one photoreceptor class and processed them in an opponent fashion [24 , 32] . These models always explained the data better than simple achromatic models using excitation values for any single photoreceptor class . Initially , models were considered in which weighted photoreceptor excitations were combined via a hypothesised single opponent mechanism ( c . f . [21 , 32] ) . Within this group of models , that preferred under screened and unscreened spectral sensitivity assumptions differed . Under screened assumptions , the preferred model was characterised by a positive influence of R7y on attraction , and negative influences of R7p and R8y , as in an earlier analysis conducted using different methods and incorporating field data for riverine and savannah tsetse [21] . However , the model preferred using unscreened sensitivity functions substituted the positive R7y effect for a positive contribution of R1-6 excitation , and an additional negative contribution of R8p excitation . This scheme was contrary to the other well-supported models in this analysis , and to intuition from the widely acknowledged principle that tsetse are attracted towards darker or bluer stimuli [8 , 47] . Biochemical analyses of the retinae of G . f . fuscipes from the original study location would be required to determine the presence or absence of screening pigments in their eyes , and thus their true spectral sensitivities [29 , 31] . However , because structured models were better-supported explanations for tsetse behaviour , and these were similar regardless of spectral sensitivity assumptions , it is suggested that this issue is of limited immediate importance in the applied context . There was very little evidence to support the involvement of a categorical , four colour system in innate colour preference in tsetse , as was proposed to explain conditioned colour discrimination in Lucilia [37] . The same conclusion was reached in earlier work [21] , but was extended here by examining different underlying spectral sensitivities , and the separate involvement of the R1-6 photoreceptors as an achromatic channel . This result might be explained if the visual mechanisms employed differed between fly species and/or behavioural contexts ( innate attraction versus learned discrimination ) . However , the categorical fly colour model has become the most accepted model of fly colour vision and is very widely applied across species and contexts ( e . g . [27] , and references therein ) . Since this model differs to the standard models of colour vision applied by default in other species [24 , 48 , 49] , it is recommended that researchers investigating the visually guided behaviour of other flies consider both categorical and alternative colour visual models , at least until a colour model is firmly established for the fly species and context under investigation . Regardless of the photoreceptor spectral sensitivities assumed , those models that separated chromatic ( comparisons of R7-8 photoreceptor excitations ) from achromatic cues ( actual R1-6 photoreceptor excitations ) provided a better fit to the data than those models that combined weighted photoreceptor excitations with no particular assumption about their role . Furthermore , these models were qualitatively similar regardless of the spectral sensitivity functions assumed . The hypothesised organisation of the fly visual system into segregated chromatic and achromatic systems has been proposed for some time based upon anatomical and physiological evidence [34 , 35 , 36] . However , there is also increasing anatomical , physiological , and behavioural evidence for the interaction of these pathways and against complete segregation [33 , 34 , 50] . It should also be noted that the current analyses focussed on particular hypotheses about opponent coding and did not seek to investigate the plausibility of all possible organisations ( c . f . [40] ) . Thus , the models presented in this analysis provide physiologically plausible , but likely simplistic , explanations for tsetse behaviour suited to use in fabric colour engineering . An important additional consideration is that each of the best-fitting models of attraction described in this paper incorporates inputs from R7 or R8 receptors of ‘y’ and ‘p’ types ( although the ‘y’ opponent system effect was not always significant in the best ‘y’ and ‘p’ opponent system models ) . These ‘y’ and ‘p’ type receptors are located in separate ommatidia and are randomly distributed over the eye [26] . Considering partial interommatidial angles in the horizontal plane ranging from 0 . 6 to 1 . 7° ( across males of Calliphora and Musca combined [28] ) , and angular sensitivity functions with widths at 50% sensitivity of 1 . 7° for R7y and 2 . 7° for R1-6 ( for G . m . morsitans , [29] ) , a target would presumably need to subtend greater than ca . 4° at the eye in order to effectively excite photoreceptors of neighbouring ommatidia . Given the size of tiny targets , this could occur at a maximum range of ca . 3 . 6 m . Because chromatic cues also have limited range for foraging honeybees , they utilise green photoreceptor contrast to guide their initial approach towards flowers [51] , so it is possible that the initial approach of tsetse towards targets is also elicited by simpler visual cues . However , after approaching a target tsetse characteristically circle in its vicinity [52] , and often depart without landing on it [8 , 53] , so their natural behaviour is certainly consistent with the evaluation of targets at relatively close range . Of greatest relevance to the applied context of tsetse control , a set of common features were evident across all models in the analysis ( though not necessarily all evident in each individual model ) . These principles were that tsetse were attracted to targets that maximised excitation of the R7y and possibly R8p photoreceptors relative to the R7p and R8y photoreceptors , and when the overall brightness of the fabric was relatively low . These mechanistic principles explain the widely-acknowledged attraction of tsetse towards blue and black targets , and the ineffectiveness of other target colours , particularly those with high UV reflectance [8 , 18 , 19 , 21] . As such , calculated excitations for fly photoreceptors , and combinations of them in the best-supported photoreceptor-based models can provide behaviourally relevant colorimetric values for the engineering of more-attractive polyester fabrics for use in tiny targets . Before describing the ways in which receptor-based models can facilitate fabric colour optimisation , it should first be emphasised that a highly attractive colour is not the only important property of an optimised fabric . Although not the subject of this analysis , specular reflectance ( mirror-like shininess ) appears to decrease tsetse attraction , and can result from the fine weave of some synthetic fabrics [20] . As such , the weave and texturisation of the fabric are important considerations . Furthermore , attractive combinations of fabric and dyes must also display high levels of colour fastness under field conditions , as phthalogen blue cotton does [8] . Nevertheless , because phthalogen blue cottons attract tsetse often twice as effectively as some blue polyesters [14] , colour engineering of polyesters for greater attractiveness holds considerable potential for tiny target improvement . In the absence of receptor-based models , attempts could be made to engineer polyester fabrics with reflectance spectra matched to that of phthalogen blue cotton . This can be tackled using single-constant Kubelka-Munk theory which relates the spectral reflectance of a dyed fabric sample at a particular wavelength to K/S , the ratio of absorbance , K , to scattering , S , coefficients [23] . Because K/S values scale approximately linearly with dye concentration , the relationship between K/S and dye concentration at each wavelength can be determined experimentally . Dye recipes can then be modelled on the assumption that the K/S values of the different dyes in the mixture at any particular wavelength sum , resulting in a theoretical K/S spectrum that can be related to its probable reflectance [23] . Such an approach might determine a dye mixture that produces a reflectance spectrum matched to that of phthalogen blue cotton . However , this approach fails when the spectrum of interest cannot be matched exactly . This can occur if the same dyes are not available , as is the case for the phthalogen blue dye which can only be applied to cotton and not polyester [14] . Because colour perception depends on photoreceptor responses and not directly on reflectance spectra , large mismatches in some regions of a reflectance spectrum may be unimportant , whilst small mismatches elsewhere may result in large differences in appearance to the intended viewer [23] . The tsetse-specific receptor-based models described in this paper provide a solution to this problem . Metamerism is the phenomenon by which spectrally dissimilar stimuli can evoke the same visual response , by virtue of eliciting a similar pattern of excitation in the viewer’s photoreceptors [23] . Thus , rather than trying to match the reflectance spectrum of interest , colorimetric colour matching approaches attempt to match values that represent the responses of the viewer’s photoreceptors [23] . Tristimulus values calculated using CIE standard observer functions represent human cone photoreceptor responses , and allow colour matching to the human eye [23] . Unfortunately , these values are irrelevant to fly vision due to the differing spectral sensitivities of their photoreceptors . However , fly photoreceptor excitation values can be calculated using the tools provided in the supporting information of this paper ( and easily adjusted for different assumptions about background and illuminant ) , and these can provide a set of basic colorimetric values that can be employed for fly’s eye view colour matching . The findings of this work imply that it makes little difference whether screened or unscreened sensitivity functions are assumed , but all could be considered in a detailed colorimetric approach . Thus , using standard approaches modified with fly photoreceptor excitation values , it may be possible to engineer a polyester metamer of phthalogen blue cotton . A potentially more powerful way in which the findings of this study can be applied is in polyester colour optimisation , rather than matching . The presented photoreceptor-based models provide common recommendations for the direction of change required in the calculated excitation values of each photoreceptor for increased tsetse attraction: namely , increased excitation in R7y and possibly R8p relative to R7p and R8y; and decreased excitation in R1-6 . The coefficients for these models allow photoreceptor excitation values to be combined into a single value that scales with tsetse attraction . As such , once the relationship between concentration and K/S was understood for a series of candidate dyes , single-constant Kubelka-Munk theory would allow the theoretical reflectance spectra of different dye recipes to be calculated [23] , from which fly photoreceptor excitations and then predicted attractiveness could be calculated . Dye recipes that maximised predicted attractiveness could then be identified , and a wide variety of computational approaches are now available to tackle such tasks . A potential advantage of this approach over colour matching is that a fabric even more effective in attracting tsetse than phthalogen blue cotton might be identified . A second advantage is that if it proved impossible to spectrophotometrically or colorimetrically match phthalogen blue cotton , an optimisation approach would yield the most attractive fabric that could be created from the candidate dyes , rather than the closest visual match . These are not necessarily the same thing because the different photoreceptor types make different contributions to attraction . In addition to colorimetric tools for the engineering of more-attractive polyester fabrics , this paper also presented a graphical analysis of tsetse attraction and photoreceptor responses elicited by a range of specific fabrics already used in tsetse control devices [14] . This analysis suggests that a phthalogen blue-like polyester used for this purpose elicits a reasonably attractive pattern of relative responses in photoreceptors R7-8 . However , the attractiveness of this fabric would be improved by decreasing its overall reflectance . This might be achieved by applying its dye in higher concentration , although the effectiveness of this will depend on the properties of the dye and base fabric . The royal blue polyester examined had high reflectance of UV wavelengths , which explained its lesser attractiveness versus phthalogen blue cotton . This fabric might be improved by addition of an optical brightener , a fluorescent dye that absorbs light at UV wavelengths and emits it in the blue , as has been suggested previously [18] . Whilst such modifications are likely to be more effective if carried out rationally and quantitatively using the previously discussed methods and the provided calculation tools , these suggestions can facilitate relatively simple and direct improvement of existing fabrics .
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Tsetse flies transmit the parasites that cause sleeping sickness . Tsetse control can contribute to disease control thanks to cheap and efficient ‘tiny targets’ that attract tsetse using a panel of blue fabric , a highly attractive colour for the flies . However , the modern blue polyesters employed are only about half as attractive as traditional phthalogen blue cottons . It will be possible to engineer more-attractive polyesters using techniques based on those already employed for fabric colour matching to the human eye . However , because fly photoreceptors differ to those of humans , these methods must be modified to evaluate colour from the fly’s eye view . This paper continues recent work attempting to explain tsetse attraction to differently coloured fabrics using the calculated responses of fly photoreceptors to those fabrics . In particular , this paper investigates several different assumptions about the sensitivities of tsetse photoreceptors and the ways in which their responses are processed . Regardless of these assumptions , common principles for the engineering of attractive fabrics were determined . The tools provided with this paper , along with fabric engineering methods already in use , will permit the engineering of more-attractively coloured polyesters for the increased efficiency of tsetse and sleeping sickness control .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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2017
|
Developing photoreceptor-based models of visual attraction in riverine tsetse, for use in the engineering of more-attractive polyester fabrics for control devices
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Tip growth has been studied in pollen tubes , root hairs , and fungal and oomycete hyphae and is the most widely distributed unidirectional growth process on the planet . It ensures spatial colonization , nutrient predation , fertilization , and symbiosis with growth speeds of up to 800 μm h−1 . Although turgor-driven growth is intuitively conceivable , a closer examination of the physical processes at work in tip growth raises a paradox: growth occurs where biophysical forces are low , because of the increase in curvature in the tip . All tip-growing cells studied so far rely on the modulation of cell wall extensibility via the polarized excretion of cell wall–loosening compounds at the tip . Here , we used a series of quantitative measurements at the cellular level and a biophysical simulation approach to show that the brown alga Ectocarpus has an original tip-growth mechanism . In this alga , the establishment of a steep gradient in cell wall thickness can compensate for the variation in tip curvature , thereby modulating wall stress within the tip cell . Bootstrap analyses support the robustness of the process , and experiments with fluorescence recovery after photobleaching ( FRAP ) confirmed the active vesicle trafficking in the shanks of the apical cell , as inferred from the model . In response to auxin , biophysical measurements change in agreement with the model . Although we cannot strictly exclude the involvement of a gradient in mechanical properties in Ectocarpus morphogenesis , the viscoplastic model of cell wall mechanics strongly suggests that brown algae have evolved an alternative strategy of tip growth . This strategy is largely based on the control of cell wall thickness rather than fluctuations in cell wall mechanical properties .
The prostrate filaments of the alga Ectocarpus develop via tip growth [28] . Prior to identifying the underlying mechanisms , a series of additional biophysical information was collected . The cell wall dye calcofluor-white was used in pulse-chase experiments to measure the growing region more precisely . The stain was localized in the first 3 μm distal from the tip of the cell , corresponding to roughly half of the dome ( Fig 2A ) . To assess the direction of growth at the local level , 0 . 2 μm–diameter fluorescent beads ( microspheres ) were loaded on the surface of the cell , and their displacement during growth was followed using time-lapse microscopy . This method was initially developed for other plant cell types [30] and recently optimized for Ectocarpus [31] . Bead trajectories were drawn , and the angles these trajectories made with the cell contour were calculated . Statistical analyses of the distribution of these angles showed a moderate deviation ( relative mean difference < 10% ) between the fluorescent marker trajectory and an orthogonal displacement pattern . Moreover , linear regression exhibited no systematic dependence of the angle on meridional abscissa ( Pearson correlation coefficient r = −0 . 03 ) , indicating that growth can be considered orthogonal to the cell surface in the dome independently of the position along the meridional abscissa ( Fig 2B and S1 Fig ) . In plants , turgor is the essential force for growth , whatever the mechanical properties of the wall . Although it exerts the same pressure throughout the cell wall , the resulting wall stress σe perceived locally in the cell wall varies because of fluctuation in local measurements ( see below ) . The calculation of wall stress is independent of the mechanical features of the cell wall ( e . g . , elastic , viscoplastic , plastic ) and therefore independent of the biophysical model used subsequently . In addition to turgor , wall stress depends on the curvature of cell κ and on the thickness of the cell wall δ at each position of the cell surface ( Fig 3A ) . Wall stress is partitioned into three directions: meridional ( s ) , circumferential ( θ ) , and normal ( n ) ( see equation S2 in S1 Text ) . Because the cell wall is thin compared to cell size , the normal component of the wall stress is considered negligible compared to the two others [32] . To calculate the wall stress at many different points in an Ectocarpus apical cell , we obtained quantitative data for three components: ( 1 ) turgor ( P ) , ( 2 ) curvature ( κ ) of the cell surface , and ( 3 ) cell wall thickness ( δ ) . First , turgor in the apical cells was measured using the nonintrusive technique of incipient plasmolysis [34] on >100 cells for each of the 10 solutions of different osmolarities used in the experiment ( Fig 4A ) . The value was subsequently corrected to take into account cell shrinking according to the protocol described in [34] ( S2 Data ) . The calculated apical cell turgor was 0 . 495 MPa , which is about 5 times the atmospheric pressure and is on the same order of magnitude as tip-growing cells from other eukaryotic groups , including the pollen tube ( 0 . 1–0 . 4 MPa , average at 0 . 2 MPa; [5] ) . The second component of wall stress is the curvature of the cell surface ( κ ) . To measure κ , the contour of Ectocarpus apical cells was first drawn manually . Then from 17 individual cell contours ( S2 Fig ) , both the meridional and the circumferential curvatures as well as an average cell contour were calculated ( Fig 4B ) . The same procedure was used for the tobacco pollen-tube contour . Compared with the pollen tube , the Ectocarpus apical cell displayed a sharper tip and a higher circumferential curvature on the shanks because of its smaller radius . The third component of wall stress is cell wall thickness ( δ ) . Staining of Ectocarpus filaments with calcofluor-white , which labels cellulose ( 1–4 ) and callose ( 1–3 ) -beta-D-glucans [35] , displayed a very clear gradient in thickness from the tip to the shanks of the apical cell ( Fig 5A , also visible in 3D reconstruction from confocal microscopy ) . However , cellulose microfibrils are only a minor component of the brown algal cell wall ( 8% maximum dry weight ) , because they are immersed in a more abundant matrix of polysaccharides ( 45% dry weight ) made of alginates ( linear polymers of β-[1→ 4]-D-mannuronate and α-[1→ 4]-L-guluronate ) and fucans ( α-L-fucosyl residues ) [23 , 36] . Therefore , we prepared longitudinal sections of apical cells . First , 300 nm–thick serial sections showed a gradient in thickness increasing from the tip to the shanks in the most meridional sections ( Fig 5B , middle section ) , whereas the thickness appeared even throughout the cell in the most tangential sections ( Fig 5B , top and bottom sections ) . Measurements of cell wall thickness across 70 nm–thick serial sections observed with transmission electron microscopy ( TEM ) further supported the presence of a cell wall thickness gradient ( Fig 5C ) . Overall , 2 , 500 measurements were corrected ( see Materials and methods ) and plotted as a function of s . The distribution depicted a gradient that could be modeled as a Pearson-like function characterized by the lowest value δmin = 36 . 2 nm at the tip ( s = 0 ) , the asymptotic maximum value δmax = 591 nm , and a midpoint at s1/2 = 16 . 8 μm ( Fig 5C ) . Cell wall thickness at the distal part of the dome ( s = 8 μm ) was 169 nm , i . e . , 4 . 7 times the thickness at the tip ( Fig 5C , close-up ) . The establishment of a cell wall thickness gradient contrasts with most tip-growing cells from other eukaryote groups [13 , 38] , in which cell wall thickness is either constant ( e . g . , 250 nm in pollen tube [39] ) or higher at the tip ( e . g . , oscillating growth in the pollen tube [40 , 41] ) . Fig 6A , 6B and 6C show a diagram of these biophysical factors in both Ectocarpus and pollen tube apices . Using this set of biological data , wall stress was calculated in both the meridional ( σs ) and the circumferential ( σθ ) directions , which ultimately allowed calculating the overall wall stress σe ( Fig 3A; equation S3 ) . Although σe fluctuates between 2 . 5 and 3 . 5 MPa ( with the lowest value in the dome ) in the pollen tube , it reaches a maximum of 25 . 6 MPa in the Ectocarpus tip and decreases distally , reaching values similar to that in the pollen tube 70 μm away from the tip ( Figs 6D and 7A ) . This stress value in the dome of Ectocarpus apical cells is remarkably high compared to other tip-growing cells , which , moreover , show the opposite stress gradient , increasing from tip to shank . Using the model , we tested the impact of the cell wall thickness gradient on tip shapes and growth rates . Steeper or gentler cell wall thickness gradients were sufficient to substantially alter the typical Ectocarpus cell shape and growth rate , suggesting that the cell wall thickness gradient must be tightly regulated in vivo ( S6 Fig , central column; S4 Movie ) . However , cells display some significant variation in cell wall thickness ( Fig 5C ) . In vivo observation of Ectocarpus tip growth also showed variability in growth rate and in cell shape ( e . g . , displayed in S2 Fig ) , which may be due to transitory variation in cell wall thickness . The extremely low growth rate of this species can easily allow the activation of regulatory mechanisms that adjust the cell wall thickness gradient through modifications in cell wall biosynthesis . We performed the same experiments on cells with three different initial cell shapes ( flat , typical Ectocarpus-like , and sharp ) . Using the Ectocarpus cell wall thickness gradient “Normal” resulted in convergence of the resulting shapes to the typical Ectocarpus shape ( S6 Fig , middle row; S5 Movie ) . Therefore , the cell wall thickness gradient may also govern the tip resilience to deformation so that initial cell shape can be recovered after transient deformation ( e . g . , due to an accident during growth ) . When simulations used a modified cell wall thickness gradient ( “Steep” or “Gentle” ) on these different initial cell shapes , all cells grew and converged to the same final shape specific to the given thickness gradient ( S6 Fig , top and bottom rows; S6 Movie ) . These simulations supplement those by Dumais and colleagues [33] , who explored various gradients in Φ and σy in a context where cell wall thickness was constant . The preponderant role of the cell wall thickness gradient in the control of tip growth raises the question of how this gradient is established and maintained . Calculations considering the cell wall extension rate and the maintenance of the cell wall thickness gradient during growth allowed inference of the level of cell wall material delivery and/or biosynthesis along the cell . According to this calculation , the overall delivery rate of cell wall material and/or synthesis in the pollen tube is much higher than in Ectocarpus ( note the different scales of the x-axis in Fig 9A , left , top versus bottom ) . The maximum culminates 3 . 0 μm away from the most distal position and drops to nil in the tube shanks ( Fig 9A , top left ) . This calculation is in agreement with former in situ observations using FM4-64 that labels both endocytic and exocytic vesicles [52–54] ( Fig 9A , top middle ) . This pattern is also in agreement with TEM observations in pollen tubes [55] and in other tip-growing walled cells where vesicle trafficking is concentrated in the most distal part of the tip ( root hairs and green algae reviewed in [56] , ascomycetes [13] ) . This mechanism contrasts with Ectocarpus , in which the cell wall flux is predicted to be significant in the shanks of the cell ( Fig 9A , bottom left ) . How the cell wall is constructed in brown algae is still largely unknown . Cellulose may be synthesized from cytosolic uridine diphosphate ( UDP ) glucose via linear complexes of cellulose synthases localized in the plasma membrane , where they elongate cellulose microfibrils into the cell wall [57] . It is still unknown how the other main cell wall components ( alginates and fucans ) reach the cell wall at the tip of the Ectocarpus apical cell , but the current delivery mode is thought to be through Golgi-derived vesicles [58] . Therefore , we used FM4-64 to investigate the pattern of vesicle trafficking in Ectocarpus . FM4-64 displayed an homogeneous spatial pattern all along the cell , with no specific vesicle localization ( Fig 9A , bottom middle ) . TEM observations provide further support because vesicles were never concentrated in any of the meridional sections of the dome of an apical cell ( bottom right ) . Instead , chloroplasts and chloroplastic endoplasmic reticulum ( CER ) involved in the production of photosynthates [14] were observed in the dome as well as in the shanks of the cell ( Fig 9A , bottom right ) . Therefore , observations of biological activity are compatible with the establishment and maintenance of a cell wall thickness gradient at an extremely slow rate , where CER can deliver the main components of the cell wall all throughout the cell with nevertheless the highest rate in the dome . To confirm this initial observation , we performed fluorescence recovery after photobleaching ( FRAP ) assays on Ectocarpus apical cells . We compared the fluorescence signal recovery dynamics in 5 different zones in the dome and shanks of the cell ( Fig 9B , left ) . Considering the increase in the fluorescence signal over time , we used the normalized slope at t = 0 as a proxy for the intensity of membrane replacement by exocytosis , potentially reflecting cell wall–building activity ( S7 Fig ) . The results showed that the exocytosis rate ( Fig 9B right ) reflects the cell wall flux inferred from the model ( Fig 9A , bottom left ) . Our FRAP experiments support the prediction of the highest exocytosis activity at the base of the dome ( zone C at s ≈ 5 μm ) and significant activity in the shanks ( zone E ≈ 10 μm from the dome end ) . Altogether , FRAP and TEM observations are compatible with the calculation of the cell wall flux inferred from the model .
Using a combination of serial longitudinal sections observed by TEM and optical microscopy , we first showed that Ectocarpus displays a gradient of cell wall thickness in its apical cells . Reports indicate that cells from other organisms display a cell wall thickness gradient . However , in most cases , accurate measurements could not be obtained from the methods employed such as epifluorescence microscopy of plant trichomes stained with propidium iodide [59] or bright-field microscopy of entire ghost cell walls of healing tips of the green alga Acetabularia [60] ) . Recently , Davì and colleagues [61] developed a technique on fission yeast enabling a resolution of 30 nm in living cells . However , this resolution is in the lower limit of Ectocarpus cell wall thickness , and TEM therefore appeared to be the most reliable technique . The accuracy of the TEM technique revealed a very steep thickness gradient ranging from 36 nm at the very tip to 169 nm at the base of the dome , corresponding to an average slope of 1 . 6% . No such gradient has been reported in the growth zone of other organisms . In the diffusely growing trichome of Arabidopsis , the cell wall thickness increases in the cell with a slope of 0 . 3% [59] . In the apical cell of Neurospora , cell wall thickness is constant in the dome and gradually increases along the shanks [62] , a pattern similar to that observed in fission yeast [61] . In terms of biophysics , this gradient in cell wall thickness resulted de facto in a decrease in the stress from the shanks to the tip . The biological measurements specific to the Ectocarpus apical cell ( turgor , dome geometry , and cell wall thickness ) were integrated in the viscoplastic model initially proposed by Lockhart and further developed for tip growth by Dumais and colleagues [33] . The observed cell wall thickness gradient quantitatively compensated for the reduction of stress with an increase in curvature from the shanks to the tip . After adjusting the plasticity values , the model was able to achieve self-similar growth at the speed observed in vivo . Regarding the cell wall mechanical properties , the model inferred two main differences with the pollen tube . First , the extensibility Φ and the yield threshold σy remained constant throughout the Ectocarpus cell , in contrast to the pollen tube models in which the constant thickness of the cell wall necessarily requires modification of the cell wall mechanical properties to allow growth [63] . Plotting σy and Φ together with cell wall thickness δ clearly illustrates the different strategies developed by Ectocarpus and the pollen tube ( Fig 7D ) : in Ectocarpus , δ is the only varying factor , but in the pollen tube , both σy and Φ vary , whereas δ remains constant . Using a Lab-on-a-Chip platform , Shamsudhin and colleagues [64] confirmed that the pollen tube displays an apparently increasing elastic modulus from the tip to the shanks , which is correlated with the presence of methyl-esterified pectins [65] . Secondly , compared with the pollen tube , the overall value of strain rate is approximately 100 times lower , but stress is approximately 10 times higher in Ectocarpus ( Fig 6 ) , suggesting that the Ectocarpus cell wall is generally more resilient to yielding during growth . Experimental work is clearly still needed to refine the values of the yield threshold and extensibility , but our calculation of wall stress offers a solid basis on which their order of magnitude can be inferred . Nano-indentation of Ectocarpus cell wall produced values of elastic modulus much lower ( approximately 1–4 MPa , [27] ) than those reported in the pollen tube ( approximately 20–400 MPa , [64] ) . However , the different nano-indentation experimental procedures used in these studies ( depth of indentation , shape of the indenter , osmotic conditions , physical model ) make comparisons questionable [47] . Nevertheless , the elastic modulus assessed using nano-indentation and the cell wall mechanical properties inferred from the growth model together suggest that Ectocarpus is more elastic but less prone to expansion during growth than the pollen tube . The distinction between cell wall elasticity and growth has already been made in the green alga Chara [66] and has since been reported in other plant cells ( reviewed in [67] ) . The inverse relationship observed in Ectocarpus is fairly compatible with the dual role of the cell wall in brown algae , i . e . , coping with frequent environmental changes in osmotic pressure ( tides ) , which requires a high elasticity , and resistance to yielding in the face of high wall stress due to the thin cell wall and high turgor . The lack of a functional relationship between intrinsic elasticity and cell wall extensibility has already been reported in land plants [67] . Likewise , the presence of stiff or soft polysaccharides—as assessed in vitro—does not correlate with the expansion of the cell wall during plant growth ( e . g . , [68 , 69] and reviewed extensively in [67] ) , nor apparently during growth in brown algae [70] . Another puzzling question is how Ectocarpus controls the cell wall thickness gradient necessary to ensure the maintenance of cell shape . It is unknown whether cell wall thickness fluctuates during growth , as recently reported in the fission yeast [61] , but this fluctuation may account for the variation in cell shape and growth rate observed in living organisms . Nevertheless , the gradient in thickness requires regulation of cell wall biosynthesis , which in brown algae like in land plants involves both in muro cellulose synthesis and the delivery of other components ( fucans and alginates in brown algae ) through vesicle trafficking ( Golgi and flat cisternae respectively in Fucales; [58] ) . FRAP data showed that the highest exocytosis activity was localized in the basal region of the dome , just before the cell adopts its cylindrical shape . This coincides with the highest cell wall flux computed from the model and with the pattern described in the pollen tube [71 , 72] . How exocytosis vesicles are targeted to these positions is unknown . In yeast and land plants , mechanosensors localized in muro control cell wall biosynthesis enzymes to modulate cell wall thickness and respond to cell wall damage [60 , 73] . The Ectocarpus genome codes for several mechanosensor proteins ( integrins , transmembrane proteins containing the WSC carbohydrate-binding domain [25 , 74] ) , and these proteins may well be key regulatory factors in this process . The palette of tip-growing strategies among species is not restricted to the control of cell wall thickness and of cell wall mechanical properties through pectin methyl-esterification . Other molecular mechanisms , including pectate distortion cycle in Chara [75] , secretion of glucanases and chitinases in fungi [13] , and intussusception in prokaryotes [76] , have been proposed to account for the differential cell wall mechanics along the cell . Therefore , distinct key cell wall biophysical factors , and potentially a combination of them [61] , appear to have been selected during evolution to achieve cell wall growth . The evolutionary history of brown algae is short ( approximately 250 My ) and distinct from that of land plants . The marine environment characterized by high physical pressure and ionic concentrations , low gravitational forces , and high drag forces due to tremendous sea currents may have promoted the development of specific , singular strategies in these peculiar organisms . In the case of tip growth , although we cannot formally exclude the possibility that a gradient of wall mechanical properties exists and contributes to morphogenesis in Ectocarpus , our results suggest that this organism has favored a singular approach based on cell wall thickness and hence on control of wall stress . The question remains whether the particular features of this organism , including its slow growth , make the control of cell wall thickness more efficient than the control of cell wall mechanical properties .
Parthenosporophyte filaments of Ectocarpus sp . ( CCAP accession 1310⁄4 ) were routinely cultivated in natural seawater ( NSW ) as described in [77] . For microscopic observations and time-lapse experiments , early parthenosporophytes were obtained from gamete germination on sterile coverslips or glass-bottomed petri dishes . Ectocarpus prostrate filaments were treated with 1 , 10 , and 50 μM IAA ( Sigma-Aldrich I3750 ) prepared in 2 , 20 , and 100 μM NaOH , respectively ( final concentration ) . Growth rates were measured for each concentration 24 h post treatment ( n = 10 ) , using NSW supplemented with 2 μM NaOH as a control . Turgor was measured in 1 μM IAA using 2 μM NaOH as the control ( see Measurement of turgor in the apical cell and correction for details ) . Ectocarpus filaments were immersed for 1 min in a range of sucrose concentrations ( diluted in NSW ) , and the proportion of plasmolyzed apical cells was measured by counting apical cells ( n > 100 ) under an optical microscope . The rate of plasmolysis was plotted against external osmolarity ( ce ) . The limit plasmolysis ( cpl ) corresponds to the value of ce at which 50% of apical cells were plasmolyzed . The mean cpl value was calculated from 3 independent experiments . Solution osmolarities were measured with an osmometer ( Osmometer Automatic , Löser , Germany ) . Because the cell wall of Ectocarpus is partly elastic , plasmolyzed cells have a reduced volume that must be taken into account to calculate the real internal osmolarity ( ci ) and thus the real internal turgor ( P ) . To do so , the coefficient of apical cell volume shrinking ( x , equal to the ratio of the cell volume upon plasmolysis to the cell volume in normal growth conditions ) was measured on apical cells ( n = 9 ) , and the corrected internal osmolarity was calculated as ci = x . Cpl . The difference between internal and external osmolarities is Δc = ci − 1 , 100 with the seawater osmolarity = 1 , 100 mOsm L−1 , and the turgor is P=ci–ce410 , in MPa . Apical cell contours were drawn manually from confocal images of meridional plans of apical cells immersed in NSW . Similar procedure was followed for tobacco pollen tubes from photos given by Gleb Grebnev ( B . Kost’s lab , Erlangen Univ . , Germany ) . We devised a Python 3 script to compute the average contour for a series of images and used it on Ectocarpus ( n = 17; S2 Fig ) and tobacco pollen tubes . The program starts with a hand-drawn contour for each cell , from which it computes a smoothed cubic spline curve . A set of equidistant points ( we used a point-to-point distance of 50 nm ) are extracted from the spline , and the meridional curvature κs is computed at each point ( S2 Fig ) . To obtain average symmetrical curvatures , a pair of windows starting from the tip point and sliding in both directions was used ( window width = 200 nm , sliding step = 50 nm ) . The discrete values of the κs = f ( s ) function were used to iteratively compute the position of cell wall point coordinates as values of x ( the axial abscissa ) and r ( the distance to the axis ) , together with the meridional abscissa s , the curvatures κs and κθ , and φ the angle between the axis and the normal to the cell wall . In particular , the circular symmetry of the dome imposes at the tip ( where s = 0 ) , that κθ = κs and thus σθ = σs , whereas in the cylindrical part of the cell κs = 0 and thus σθ = 2σs . Ectocarpus filaments were prepared for TEM . Filaments grown on sterile glass slides were fixed with 4% glutaraldehyde and 0 . 25 M sucrose at room temperature and washed with 0 . 2 M sodium cacodylate buffer containing graded concentrations of sucrose . The samples were post-fixed in 1 . 5% osmium tetroxide , dehydrated with a gradient of ethanol concentrations , and embedded in Epon-filled BEEM capsules placed on the top of the algal culture . Polymerization was performed first overnight at 37 °C and then left for 2 d at 60 °C . Ultrathin serial sections were cut tangentially to the surface of the capsule with a diamond knife ( ultramicrotome ) and were mounted on copper grids or glass slides . Two types of sections were produced . Serial sections ( 300 nm thick ) were stained with toluidine blue to show the main cellular structures , including the cell wall , and mounted on glass slides . Sections ( 70 nm thick ) were stained with 2% uranyl acetate for 10 min and 2% lead citrate for 3 min , mounted on copper grids ( Formvar 400 mesh; Electron Microscopy Science ) , and examined with a Jeol 1400 transmission electron microscope . A compilation of the sections for the 15 cells is shown in S3 Fig . Original photos are available at https://www . ebi . ac . uk/biostudies/studies/S-BSST215 . From TEM pictures obtained on fixed Ectocarpus apical cells , only longitudinal sections with the thinnest walls were considered to avoid bias due to misaligned sections ( all images are shown in S3 Fig ) . Measurements were carried out every 386 nm along 15 different cells , at the meridional abscissa from the tip ( s = 0 ) up to s = ±70 μm using Fiji image analysis software . Altogether , 2 , 500 measured values of apparent thickness w were corrected , making the assumption that actual cell radius was R = 3 . 27 μm ( but was seen as apparent radius a ) and applying the following formula: δ=R-a2+R2- ( a+w ) 2 ( S4 Data ) . As askew sectioning results in cell walls looking thicker , the only remaining bias is expected to cause overestimation of the thickness at the tip . Corrected values δ for cell wall thickness were plotted as a function of the position s along the cell . As the relationship δ = f ( s ) displayed the aspect of an inverted bell , we designed 3 functions with this shape , derived from classical functions , to match them with the experimental values— ( 1 ) “Gauss”: δ=δmax- ( δmax-δmin ) exp ( - ( s/s1/2 ) 2log ( 2 ) ) ; ( 2 ) “Lorentz”: δ=δmax- ( δmax-δmin ) ( 1+ ( s/s1/2 ) 2 ) -1; and ( 3 ) “Pearson”: δ=δmax- ( δmax-δmin ) ( 1+3 ( s/s1/2 ) 2 ) -1/2 . The values δmin , δmax , and s1/2 were adjusted for each of these functions , with a respective residual standard error of 0 . 08 , 0 . 05 , and 0 . 04 . Therefore , we used the Pearson model with its optimized values δmin = 36 . 2 nm , δmax = 591 nm , and s1/2 = 16 . 81 μm for further modeling ( Fig 5C ) . Ectocarpus cells were boiled twice in 1% SDS , 0 . 1 M EDTA and then treated with a solution of 0 . 5 M KOH at 100 °C . Pellet was rinsed extensively with MilliQ water and dried on a glass slide . Imaging was performed on dried samples . A Veeco Bioscope catalyst atomic force microscope coupled with a Zeiss inverted fluorescent microscope was used for imaging . RTESP probes ( Bruker ) were used in Scanasyst mode . The protocol was adapted from [30] and is described in detail in [31] . Young sporophyte filaments grown in glass-bottom petri dishes were covered with sonicated 0 . 1% ( w:v NSW ) of FluoSpheres amine , 0 . 2 μm , red ( F8763 , Molecular Probes ) , washed with NSW and mounted under a TCS SP5 AOBS inverted confocal microscope ( Leica ) controlled by the LASAF v2 . 2 . 1 software ( Leica ) . The growth of 25 apical cells growing parallel to the glass surface was monitored , and bright-field and fluorescent pictures of median planes for each apical cell were acquired at several time points . Cell wall contours were hand-drawn on time-lapse images using GIMP , together with their respective indicator points . The position of the extreme tip ( s = 0 ) was fixed for each meridional contour , and the drawing of cell contours and microsphere positions were aligned during the time course by using steady microspheres attached on fixed positions . A spline was adjusted on each contour and on each series of indicator points . The angle at each possible intersection between these trajectories and the cell contour splines were computed , making use of their first derivatives . Further analysis performed using R [78] consisted of ( 1 ) determining the distribution of angles , their mean , and standard deviation and ( 2 ) testing the hypothesis of dependence between the angle and the meridional abscissa . From the 156 measured angles between the tangent to cell wall and the trajectory , we computed the mean value m = 1 . 71 = π/1 . 83 radian ( or π/2 − 9 . 16% ) and the standard deviation s = 0 . 52 = π/6 . 09 radian . To test independence between the angle and the position in the dome , we computed the Pearson correlation coefficient between the angle and the absolute value of the meridional abscissa . It was r = −0 . 031 . Staining of Ectocarpus filaments with calcofluor-white was carried out as described in [28] . FM4-64FX ( F34653 , Invitrogen ) stock solution was diluted to 385 μM in DMSO and then diluted to 7 . 7 μM in NSW . Coverslips with Ectocarpus filaments were immersed in 50 μL of 7 . 7 μM cold FM4-64FX on ice and immediately mounted on a confocal microscope . Endocytosis and further trafficking of the fluorochrome was followed for 1 h at room temperature . The fluorochrome was excited with a 561 nm neon laser , and emission was observed with a 580–630 nm PMT . For the FRAP assay , filaments were stained with 100 μM FM4-64FX for 10 min at 4 °C and rinsed 4 times with cold , fresh seawater . Photobleaching was performed on about 25 μm ( s ) along the cell from the tip , and recovery was monitored using an inverted Nikon Ti Eclipse Eclipse-E microscope coupled with a Spinning Disk ( Yokogawa , CSU-X1-A1 ) and a FRAP module ( Roper Scientifics , ILAS ) . Images were captured with a 100x APO TIRF objective ( Nikon , NA 1 . 49 ) and an sCMOS camera ( Photometrics , Prime 95B ) . For the detection of the FM4-64FX stained samples , we used a 488 nm laser ( Vortran , 150 mW ) for the excitation and the bleaching steps and collected the fluorescence through a 607/36 bandpass filter ( Semrock ) . Image acquisition using the MetaMorph software 7 . 7 ( Molecular Devices ) was as follows: 1 image/s , displaying 6 images before bleaching , 1 image at the precise time of bleaching , 50 images during the recovery phase , for a total of 57 images by cell . Images for one given cell were processed as a stack using Fiji [79] and R [78] . For each time point t ( with bleaching occurring at t = 0 ) , the background signal Z ( t ) was averaged from 4 separate square regions of approximately 1 μm2; the spontaneous fluorescence decrease was estimated by monitoring the signal U ( t ) in an unbleached region; the local signal was recorded in regions A–E as defined in Fig 9B . Note that all zones , including E , are sufficiently far from the edge of the photobleached zone to be unaffected by homogenization due to membrane lateral flux in the considered timescale . Following [80] , the corrected signal for region A ( and similarly for regions B–E ) was computed as: Ac ( t ) = ( A ( t ) -Z ( t ) - ( A ( 0 ) -Z ( 0 ) ) ) U ( 0 ) -Z ( 0 ) U ( t ) -Z ( t ) . The recovery activity was estimated by matching the measured Ac ( t ) values to the function Y ( t ) = Y ( 0 ) + α ( 1 − exp ( −t/τ ) ) , where Y ( 0 ) and α and τ are free parameters . We computed the normalized slope at t = 0 as ( 1/α ) ( dAc/dt ) ( 0 ) = 1/τ , for 9 observations in each of the 5 ( A–E ) zones selected ( see S7 Fig ) . The meridional contour of 6 tobacco pollen tube apices were traced from photos given by Gleb Grebnev ( B . Kost’s group , Erlangen University , Germany ) , and the curvature was computed as described for Ectocarpus cells . Turgor and cell wall thickness were obtained from the literature [38] . In the absence of precise determination of their respective values , we derived a working hypothesis from previous literature reports showing that variations of Φ and σy occur simultaneously in opposite directions [49–51] . This intuitive relationship is consistent with molecular models of the cell wall [50] . Given that our model can derive the value of the expected strain rate ε˙* from other values ( S1 Text ) , we propose to partition this product equally between its two members . Thus , we computed Φ=ε˙* and ( σe-σy ) =ε˙* , leading to σy=σe-ε˙* . These arbitrary values were useful for giving an example of what could be a possible state ( Fig 6F and 6G; Fig 7B right ) and performing simulations . Programs developed as part of this work were written in Python 3 . 6 [81] , making use of NumPy [82] and Matplotlib [83] libraries , in a GNOME-Ubuntu environment ( laptop and workstation ) . The source code is available at https://github . com/BernardBilloud/TipGrowth . Modeling is described in S1 Text . The simulation program performed a simple simulation with graphic output or an array of simulations within a range of Φ and σy values . The input was a list of cell wall point coordinates and values from , for instance , computations of average contours ( ad hoc generated data were also used for simulations starting with geometrically designed profiles ) . For each point , the stress was computed from turgor , curvature , and cell wall thickness values . Then , using Φ and σy , the strain rate and the normal velocity were computed . The velocity and displacement direction ( normal to the cell wall ) gave the new position of the point , calibrated for a tip growth of 1 nm at each step . After computing new positions for all points , the program designed a cubic spline ( without smoothing ) from which a new sample of points was extracted , thus keeping a constant distance between points throughout the simulation . Accuracy of the simulation was evaluated by averaging point-to-point distances between the simulated profile and the initial profile translated at the expected speed . Values of Φ and σy were progressively optimized using a steepest-descent approach . As starting values , we used the coefficients of the linear model derived from the points ( σe , Φ ( σe − σy ) ) for which Φ ( σe − σy ) ) > 1: Φ = 2 . 5 × 10−3 min−1 MPa−1 and σy = 11 MPa . These values were used to simulate growth up to 25 μm , and divergence with the expected behavior was evaluated by comparing them to the initial points translated by 25 μm in the axial direction . As a numerical value , we took the logarithm of rD ( residual distance ) , which was the weighted average point-to-point distance , where the weight was exp ( s2log ( 2 ) ) , to maintain the dome shape . Optimized values Φ = 2 . 51 × 10−3 min−1 MPa−1 and σy = 11 . 18 MPa gave a simulation with a log ( rD ) of −3 . 0 . As a comparison , the mean log ( rD ) between the initial average contour and the 17 experimental contours used to build it was −4 . 41 , with a standard deviation of 0 . 35 . To assess the robustness of the results , we performed a bootstrap analysis . Three thousand samples were constructed by drawing with replacement 17 cell contours and 15 cell wall TEM images out of their respective datasets . For each sample , the average contour and the cell wall gradient were computed as explained above . The stress σe and expected strain rate ε˙* were computed as functions of the meridional abscissa s . To test consistency with the model , the ( σe;ε˙* ) points were fitted a Lockhart equation by adjusting values Φ and σy and computing the Pearson correlation coefficient ( r2 ) for the increasing part of the function , i . e . , σe > σy;ε˙*>0 .
|
Tip growth is known in organisms with filament-like structures , such as fungi ( e . g . , hyphae ) , plants ( e . g . , root hairs , moss protonemata ) , and algae ( e . g . , filamentous thalli ) . The driving force for growth in these organisms is the difference in osmotic pressure ( turgor ) between the inside of the cell and the external medium , a force contained by the cell wall . Physical laws imply that the higher the curvature of the cell , the lower the pressure ( stress ) perceived by the cell wall . Paradoxically , growth takes place at the dome-shaped cell apex , which has high curvature . Tip-growing cells studied so far ( mainly plants ) compensate the low wall stress in the apex by chemically loosening their cell wall . We studied Ectocarpus , which is a representative of brown algae , a eukaryotic branch very divergent from land plants , fungi , and green algae . We carried out a series of quantitative measurements at the cellular level and showed that the cell wall is thinner at the tip ( 36 nm ) than on the shanks ( 170 to 500 nm ) . Using a viscoplastic model of cell wall expansion , we showed that the cell wall thickness gradient , together with dome curvature , generates sufficient wall stress to account for the observed growth pattern .
|
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2019
|
The brown algal mode of tip growth: Keeping stress under control
|
Prion diseases are fatal , progressive , neurodegenerative diseases caused by prion accumulation in the brain and lymphoreticular system . Here we report that a single subcutaneous injection of cellulose ethers ( CEs ) , which are commonly used as inactive ingredients in foods and pharmaceuticals , markedly prolonged the lives of mice and hamsters intracerebrally or intraperitoneally infected with the 263K hamster prion . CEs provided sustained protection even when a single injection was given as long as one year before infection . These effects were linked with persistent residues of CEs in various tissues . More effective CEs had less macrophage uptake ratios and hydrophobic modification of CEs abolished the effectiveness . CEs were significantly effective in other prion disease animal models; however , the effects were less remarkable than those observed in the 263K prion-infected animals . The genetic background of the animal model was suggested to influence the effects of CEs . CEs did not modify prion protein expression but inhibited abnormal prion protein formation in vitro and in prion-infected cells . Although the mechanism of CEs in vivo remains to be solved , these findings suggest that they aid in elucidating disease susceptibility and preventing prion diseases .
Prion diseases or transmissible spongiform encephalopathies are fatal neurodegenerative conditions caused by prion accumulation in the brain and lymphoreticular system [1] . Creutzfeldt–Jakob disease is the most common human prion disease that sporadically occurs mostly in the elderly . The number of cases of human prion disease is very small at a few cases per million persons , but the prevalence has been gradually increasing in accordance with the aging of society [2] . Despite recent tremendous therapeutic developments [3–6] , remedies or preventive measures to inhibit disease progression or achieve significantly beneficial improvements have not yet been established . In animal prion diseases such as scrapie in sheep and bovine spongiform encephalopathy in cattle , not only classical but also atypical , cases are known to sporadically occur [7] . In addition , cervine prion diseases such as chronic wasting disease are prevalent in domesticated as well as wild animals [8] . These animal prion diseases have become potential threats to public health and the economy . In particular , the issue of chronic wasting disease in wild animals is serious because affected animals or prion-carriers are difficult to eliminate , prions of chronic wasting disease are shed into excreta , and prions resist decomposition in soil and cadavers [8] . No means for preventing these animal diseases have been established , and development of prophylactic measures such as vaccines has long been awaited . However , prions are not efficiently eliminated by the immune system , which has stalled efforts to develop safe effective vaccines [9–11] . In our early study on the development of a certain anti-prion compound , we noticed that not only anti-prion compound-containing tablets but also placebo tablets prolonged the lifespan of peripherally prion-infected animals . Subsequent analysis of the tablet ingredients revealed that cellulose ethers ( CEs ) modified disease progression of the prion-infected animals . Here we report the anti-prion prophylactic efficacy of CEs , which have remarkable post- and pre-infection protective effects of a single injection into prion-infected animals . These compounds are non-digestible , non-ionic , water-soluble , polysaccharide derivatives commonly used as inactive ingredients in foods , cosmetics , and pharmaceuticals . We also examined the effectiveness of CEs when administered at various times post- or pre-infection in prion-infected animals . In addition , we examined the pharmacokinetics , biological features , structure-activity relationships , and effectiveness of CEs in other prion disease models , and mechanism of action . Finally the significance of the findings is discussed .
Hydroxypropyl methylcelluloses ( HPMCs ) were mainly used in this study because these compounds are the most popularly utilized CEs . First , we analyzed the post-infection effectiveness of HPMCs , which had similar contents of methyl modification [ca . 1 . 91 mol/anhydrous glucose unit ( AGU ) ] and hydroxypropyl modification ( 0 . 24 mol/AGU ) , but different viscosities . Chemical summaries and cumulative molar masses of molecular weight distribution of HPMCs are shown in Fig 1a . It is obvious that depending on the viscosity , each HPMC had a distinct molecular weight distribution of polymers with certain ranges of molecular sizes . Because it is expected that macromolecules are not delivered from the blood to the brain parenchyma through the blood–brain barrier , HPMCs were continuously infused into the cerebral ventricle to bypass the blood–brain barrier , as described in a previous study on pentosan polysulfate [12] . A 4-week continuous intracerebroventricular infusion ( 150 μg/day ) of HPMC samples when given 3 days post-infection ( dpi ) demonstrated remarkable extension of survival times in Tg7 mice expressing hamster prion protein ( PrP ) [13–15] intracerebrally infected with the hamster-adapted 263K prion [16] . Although two of the most viscous HPMC samples could not be tested because of difficulty in handling the solution , the most effective was 60SH-50 , which extended the median survival time by about 4-fold ( 62 days → 238 days ) , as compared to the vehicle control ( Fig 1b ) . On the other hand , unlike the case of previously reported macromolecules , such as pentosan polysulfate [12] , it was interesting that a single subcutaneous injection ( 4 g/kg body weight ) of HPMCs when given immediately after infection , demonstrated remarkable extension of survival times in Tg7 mice intracerebrally infected with the 263K prion . The most effective was also 60SH-50 , which extended the median survival time by about 3-fold ( 48 days → 155 . 5 days ) , as compared to the vehicle control ( Fig 1c ) . When the median survival time ( % of vehicle control ) of HPMC-treated animals was plotted against HPMC viscosity , efficacy was obviously related to viscosity . The efficacy–viscosity relationships were bell-shaped , and an HPMC with a viscosity of approximately 100 mPa•s in a 2% solution at 20°C ( equivalent to a 140-glucose-unit size ) was most effective ( Fig 1d ) . Meanwhile , CEs as short as hexamers were still effective when administered into the cerebral ventricle , although the effectiveness was not as remarkable as with large-sized CEs ( S1 Fig ) . The relationship between dosage and effectiveness revealed that efficacy was dependent on dosage by either single subcutaneous injection or 4-week continuous intracerebroventricular infusion ( S2 Fig ) . Next , we determined whether variations in methyl or hydroxypropyl modification had any effect on the efficacy of CEs with similar viscosities and found that efficacy was not associated with the variations conferred by methyl or hydroxypropyl modifications ( S3 Fig ) . In addition , we investigated whether contaminated materials had any effect on the efficacy of CEs and found that efficacy was not associated with contaminant removal by activated carbon treatment ( S4 Fig ) . Although age [17] and sex [18 , 19] are known to affect the incubation times of prion-infected rodents at some instances , but the observed CE efficacy was similar in animals irrespective of these variables ( S5 Fig ) . A single injection of a representative HPMC , TC-5RW , into either the peritoneal cavity or the tail vein demonstrated considerable efficacy in intracerebrally infected animals ( S6a Fig ) . However , daily oral administration of TC-5RW to intracerebrally infected animals was not effective , even if it was started before they contracted the infection ( S6b Fig ) . This result may be due to the poor intestinal absorption of CEs [20] . On the other hand , in the case of peripheral infection such as intraperitoneal infection , CE efficacy was enhanced , as compared to that of intracerebral infection . For instance , daily oral administration of TC-5RW , which was ineffective against intracerebral infection , was remarkably effective , as continuous treatment with a diet containing 15% TC-5RW from 7 dpi extended the median survival times of animals by about 3-fold ( 98 days → 296 days ) ( Fig 2a ) . A single subcutaneous injection of TC-5RW ( 4 g/kg body weight ) at 3 dpi extended the median survival times of animals by about 6 . 7-fold ( 97 days → 651 . 5 days ) ( Fig 2b ) . The results suggest that even a small amount of CE absorbed through the intestinal tract is effective over a long period of time in case of peripheral infection , although absorption of CEs in the intestinal tract is reportedly very limited when orally administered [20] . Because symptom onset in Tg7 mice was not clearly determined , Syrian hamsters were used . Syrian hamsters infected with the 263K prion showed ataxia or unstable gait as an initial obvious disease sign at approximately 60 dpi . Thus , we examined the effectiveness of TC-5RW given in pre-symptomatic or post-symptomatic disease stages . Similar to that of previously reported anti-prion materials [12 , 21] , the efficacy of CEs decreased with the delay of post-infection timing of injection ( Fig 3 ) . A single administration of TC-5RW at an early symptomatic stage ( 65 dpi ) although significantly effective , had a very limited effect on extending the survival . Because the effectiveness of a single post-infection CE administration continued over a long period , we examined the effectiveness of a single CE administration given months before infection and found that HPMCs given in a single subcutaneous injection prior to infection were still clearly effective . HPMCs given 6 or 12 months prior to infection were slightly less effective than , or as effective as , those given immediately after infection; even HPMCs given 19 months before infection were still markedly effective ( Fig 4a ) . When the median survival time ( % of vehicle control ) of HPMC-treated animals was plotted against the administration timing , efficacy tended to gradually decrease according to the pre-infection interval ( Fig 4b ) . However , there was no significant difference in median survival times between the immediate post-infection intervention group and the 12-month pre-infection intervention group injected with 60SH-50 or 60SH-400 . The most potent HPMC in the 12-month pre-infection intervention was slightly more viscous than the most potent HPMC in the post-infection intervention ( Figs 1d and 4c ) . Pre-infection prophylactic effects of CEs were also observed in Syrian hamsters ( S7 Fig ) . By intraperitoneal infection , 60SH-50 or 60SH-400 extended the survival times of animals treated at the 0-month pre-infection by about 3 . 8-fold ( 233 days → about 890 days ) and that of animals treated at the 13-month pre-infection by about 2 . 0- to 2 . 3-fold ( 195 days → 398 ~ 449 days ) . Therefore , it is obvious that even a single administration of CEs not only around the time of infection , but also as long as one year prior to infection , effectively extended the survival times of prion-infected animals . To elucidate the mechanism of action of CEs , pharmacokinetics of subcutaneously injected radiolabeled TC-5RW were investigated in Tg7 mice . Immediately after injection , radiolabeled TC-5RW was taken up into the blood ( S8a Fig ) and excreted in the urine and feces at a rate of 70% of the initial dose within 3 days . Thereafter , it was excreted considerably more slowly , with 20% of the initial dose remaining in the body 2 weeks post-injection ( S8b Fig ) . GPC analysis indicated that smaller-sized molecules of TC-5RW were preferentially excreted in the urine and feces , and larger-sized molecules remained in the plasma ( S8c Fig ) . Next , long-term pharmacokinetics and distribution were investigated in Tg7 mice given a single subcutaneous dose of radiolabeled TC-5RW . Radiolabeled TC-5RW was distributed in various tissues for long periods , but a little was found in the brain parenchyma , where prions accumulate and cause neurodegeneration ( Fig 5a and 5b ) . Even after 6 months , amounts up to a few percent of the injected dose per gram of tissue or fluid were observed in various body parts , such as the adrenal cortex , choroid plexus , mandibular gland , thyroid gland , lymph , spleen , and skin , whereas less than 0 . 02 percent of the injected dose per gram of tissue ( equivalent to ~10 μg/g tissue ) was observed in the brain parenchyma . The elimination half-life of TC-5RW in these tissues was 50–350 days ( Fig 5c ) and longest elimination half-life periods were observed in the skeletal muscle , adrenal cortex , brain , and testis . GPC analysis revealed that larger portions of administered TC-5RW remained in tissues ( Fig 5d ) . Consequently , a persistent residue of CE in the body is linked to long-lasting effects . Because CEs have been recognized to be biologically inactive macromolecules , we speculated that macrophages might be involved in the degradation and excretion of CEs administered in the body . Thus , we investigated macrophage uptake of CEs using fluorescein–labeled HPMCs and peritoneal macrophages of Tg7 mice and found that macrophage uptake ratios of HPMCs differed from each other and were independent of viscosity ( Fig 6a ) . When compared with the data of the median survival times ( % of vehicle control ) of Tg7 mice treated with a single subcutaneous dose of HPMCs , the macrophage uptake ratio was inversely correlated , particularly with the survival time of 12-month pre-infection intervention , rather than that of the immediate post-infection intervention ( Fig 6b ) . Therefore , more effective HPMCs in pre-infection protection were phagocytized to a lesser extent by macrophages . As a representative CE compound , methyl cellulose SM-4 was used for structure–activity studies . The chemical properties of tested compounds are shown in Fig 7a . The results of survival analysis of Tg7 mice treated with each compound are shown in Fig 7b . Comparison of SMR vs . SM-4 and SMR-HP vs . SMOx-HP indicated that a reduced modification of the reducing end produced better effects . Diethylaminoethyl modification ( SMR-DEAE ) produced the most excellent effects; carboxymethyl modification ( SMR-CM ) produced similar effects as hydroxypropyl modification ( SMR-HP ) . In contrast to these hydrophilic modifications , hydrophobic modifications with a propyl group ( SMR-PR and SMR-PR-HB ) were much less effective than unmodified SMR . Further propyl group modification ( SMR-PR-HB ) was less effective than less modification ( SMR-PR ) . These results suggest that the hydrophilicity of the CEs contributes to the effectiveness . Hydroxypropyl and methyl ether compounds with sugar backbones other than cellulose were also analyzed in intracerebrally prion-infected Tg7 mice by a similar manner as performed with CEs . Tested sugar structures included dextran , dextrin , pullulan , starch , chitin , chitosan , and cyclodextrin . These polysaccharide ethers were ineffective ( S1 Table ) , suggesting that the cellulose backbone is essential for effective protection against prion diseases . The effects of CEs were also investigated in C57BL/6 mice intracerebrally infected with mouse-adapted prion strains ( RML scrapie prion and Fukuoka-1 human prion disease prion in Fig 8 , and 22L scrapie prion in S9a Fig ) . The effects of CEs were significantly observed in all of the disease animal models , but were less remarkable than those observed in the 263K prion-infected Tg7 mice . Because it is inferable that animals with shorter incubation periods , such as Tg7 mice and Syrian hamsters , might show more remarkable CE effects than animals with longer incubation periods , we examined the effects of CEs in Tga20 mice , which have substantially shorter incubation periods to mouse-adapted prion strains [22] . The effects of CEs in Tga20 mice were significant but less remarkable ( S9b Fig ) . Therefore , prion disease animal models influenced the effects of CEs , and prion strain-associated factors or animal genetic backgrounds might contribute to the variation in CE efficacy . One example of the influence of the animal genetic background was demonstrated in the comparison between ddY and ICR mice . Both mice are outbred strains similarly used in drug toxicity and pharmacokinetic studies , but obvious differences in CE efficacy were observed between these mice ( S10 Fig ) . In prion diseases , normal PrP ( PrPC ) is conformationally converted to an abnormal protease-resistant PrP ( PrPSc ) as the main component of the prion [1] . However , administration of CEs did not modify the protein or gene expression level of PrP in the brain or spleen ( Fig 9a and 9b ) . On the other hand , administration of CEs inhibited 263K prion amplification in the protein misfolding cyclic amplification reaction , which is a method to amplify PrPSc in vitro [23] , whereas a control compound , hydroxypropyl methyl dextran ( 70 kDa ) , did not inhibit amplification ( Fig 9c ) . Similarly , in persistently RML prion-infected cells [24] , CEs inhibited PrPSc formation in accordance with their in-vivo potencies , although higher concentrations of CEs were needed ( Fig 9d ) . CE administration did not affect the expression levels of total PrPC or cell surface PrPC of the cells ( Fig 9e and 9f ) . These results suggest that CEs inhibit PrPC–PrPSc conversion without affecting PrPC metabolism .
The results of the present study revealed that CEs , as new types of anti-prion compounds , can effectively extend the life span of animals infected with prion not only peripherally but also intracerebrally , even though CEs are macromolecules that are hardly capable of reaching the brain parenchyma . CEs share no similarities in their structures or chemical properties with previously reported anti-prion polymers , such as sulfated glycans [25 , 26] , polyamines [27–31] , and cationic dendrimers [32–35] . Unlike these anionic and cationic polymers , CEs are non-ionic but hydrophilic . The long-lasting efficacy of CEs is an astonishing , distinct feature from any other compounds previously reported [3–6 , 36–38]; a single post-infection subcutaneous injection of CEs extended the life spans of peripherally infected mice nearly to natural life spans and extended the life spans of intracerebrally infected mice by 2–3 fold . More astonishing is the pre-exposure prophylactic effects of CEs , as no significant difference in efficacy was observed in the most effective CE administered at an immediate post-infection or at one year pre-infection . No other compounds or biological materials exogenously administered have been reported to achieve these levels of post-infection and pre-infection prophylactic effects in peripherally or intracerebrally prion-infected animals . CE molecules were distributed throughout the body within days after a single subcutaneous injection , and larger-sized portions of the molecules were retained in the body for months . The ability of CE residues to remain in the body is associated with the long-lasting protective effects of CEs . Chemically , the long-lasting protective efficacies of CEs were associated with the molecular size , but not the degree of modification to the methyl or hydroxypropyl group . Biologically , long-lasting protective efficacies were significantly associated with macrophage uptake ratios: CEs less phagocytized by macrophages were more effective . These data appear to be consistent with the structure-activity data , which shown that the efficacies of CEs were abolished by hydrophobic , but not hydrophilic , modifications . This can be explained by the findings of Tabata and Ikada who reported that microspheres with hydrophobic surfaces are more readily phagocytized than those with hydrophilic surfaces [39] . Therefore , it is presumable that macrophages play a crucial role in the efficacies of CEs and that phagocytosis facilitates the decomposition or excretion of CEs . CEs are unlikely to affect the metabolism or turnover of PrPC because the expression levels of PrPC were not modified in tissues of TC-5RW-treated mice or TC-5RW-treated culture cells . However , CEs might directly inhibit the conversion of PrPC to PrPSc ( namely prion formation ) in prion-infected animals because of the following findings: TC-5RW inhibited prion formation in the protein misfolding cyclic amplification reaction; CEs were remarkably effective when infused into the cerebroventricular system; and radioactivity of TC-5RW was observed in the brain parenchyma at an amount of less than 10 μg/g tissue equivalent and was eliminated very slowly in the brain parenchyma at a half-life of about one year . On the other hand , there was a gap in the CE concentration required for inhibition of prion formation among the assay systems . CE concentration of less than 10 μg/g tissue equivalent was needed in the mouse brain , and this concentration appeared to be similar to that of the protein misfolding cyclic amplification reaction ( ~10 μg/mL ) , whereas it was different from that of the prion-infected cells ( ~1 mg/mL ) . Because the prion strain differed among these assay systems , the CE concentration gap might reflect the prion strain dependency of CE action: significantly effective against the 263K prion , but much less effective against the RML prion . However , it is possible that the mechanism of action of CEs differs among the assay systems , and the possibility cannot be ruled out that other factors , such as CE-metabolites or CE-induced host factors , are responsible for the anti-prion activities of CEs in animals . Although CE effects were significantly observed in all prion disease animal models tested in the present study ( except for the ICR mouse model ) , CE effects in animals infected with mouse-adapted prions were not as remarkable as those of animals infected with the 263K hamster-adapted prion . In addition , CE effects were not necessarily remarkable in animal models with shorter incubation periods . Thus , these findings imply that CE effects may be influenced by the prion strain or animal genetic background . Because no animals with an identical genetic background are available for comparison of CE efficacies against hamster-adapted prions vs . mouse-adapted prions , it is not possible at the present time to verify the influence associated with prion strains . Regarding the animal genetic background , Tg7 mice have a mixed background with 129/Ola and C57BL/10 [13–15] . Thus , the genetic background of Tg7 mice is very different from that of C57BL/6 , whereas Tga20 mice have a genetic background close to C57BL/6 [22] . Accordingly , the animal genetic background might influence the effects of CEs . Although this inference remains to be elucidated , the data of the comparison between ddY and ICR mice are suggestive of inference . Tremendous efforts have been made to conduct clinical trials or experimental treatments of several compounds [40–45] . However , there have been no meaningful outcomes in regard to patient benefit . One of the reasons clinical trials commonly fail in terms of survival is supposed to be delayed intervention . In prion-infected animals , the larger delay in intervention , the less effective anti-prion compounds are at prolonging survival [12 , 21] . The most opportune time for therapeutic intervention of prion diseases is very early in the preclinical stage because exponentially accumulated amounts of the prion almost reach a plateau in the brain around the stage of symptomatic disease [46 , 47] . Because the effectiveness of CEs administered after disease onset were also very limited , despite being statistically significant , therapeutic effects are hardly expected for intervention after disease onset . However , significantly beneficial effectiveness of CEs might be expected by immediate post-infection or pre-exposure prophylactic intervention . Especially at peripheral infection , a few or several injections of CEs might be sufficiently preventive to keep infected individuals healthy for the expected lifetime . However , the safety properties of CEs remain to be evaluated and drug availability to target tissues must be improved before the dosing regimen can be optimized . In conclusion , it is not yet clear how polymers , such as CEs , peripherally administered suppress the disease process in the brain and extend survival . It is also unclear how CE efficacy is influenced by prion strains or host genetic factors . These enigmas await further elucidation . However , the findings of this study suggest that CEs may be something in daily life that modify disease onset and could be useful for the development of preventive measures against prion diseases .
All animal experiments were performed in accordance with protocols reviewed and approved by the Institutional Animal Care and Use Committee of Tohoku University ( approval numbers 20MdA-54 , 21MdA-192 , 22MdA-247 , 2011MdA-347 , 2012MdA-272 , 2013MdA-194 , and 2016MdA-139 ) . The animal care and use protocols adhered to the Fundamental Guidelines for Proper Conduct of Animal Experiment and Related Activities in Academic Research Institutions by the Ministry of Education , Culture , Sports , Science and Technology ( Notice No . 71 issued on June 1 , 2006 ) , the Standards Relating to the Care and Management of Laboratory Animals and Relief of Pain by the Ministry of the Environment ( Notice No . 84 issued on August 30 , 2013 ) , and the Act on Welfare and Management of Animals ( revised on September 5 , 2012 ) in Japan . All HPMC compounds were kindly provided by Shin-Etsu Chemical Co . , Ltd . ( Tokyo , Japan ) . Compound properties are listed in Fig 1a . Methyl cellulose ( SM-4 ) was also provided by Shin-Etsu Chemical Co . , Ltd . All SM-4 derivatives were synthesized from SM-4 by Meito Sangyo Co . , Ltd . ( Nagoya , Japan ) . A chemical summary of SM-4 and its derivatives is presented in Fig 7a . Tg7 mice , kindly provided by Dr . Bruce Chesebro of the Laboratory of Persistent Viral Diseases of NIAID’s Rocky Mountain Laboratories ( Hamilton , MT , USA ) , were mainly used in the study because they have substantially shorter incubation times than Syrian hamsters when intracerebrally infected with the hamster-adapted 263K scrapie prion [13–15] . Tg7 mice are derived from transgenic Tg10 mice [13] and are crossed onto a mouse PrP-null background [48] . Thus , Tg7 mice lack endogenous mouse PrPC expression but express hamster PrPC at about 4 times the level of that expressed by wild-type mice in the brain and at a level similar to that expressed by wild-type mice in the spleen ( S11 Fig ) . Six- to 10-week-old male mice were used for all experiments , unless otherwise stated . Intracerebral or intraperitoneal infection was performed by inoculation with 20 or 100 μL , respectively , of a 1% ( w/v ) brain homogenate obtained from a terminally ill 263K prion-infected hamster . In case of continuous intracerebroventricular infusion , continuous infusion into the cerebral third ventricle was performed using an osmotic minipump and brain infusion kit , as previously described [49] . Mice were monitored every day until the time of terminal disease , at which time the mice were akinetic ( with a lack of grooming behavior , coordination , and parachute reaction ) or exhibited a rigid tail , an arched back , and weight loss of approximately 10% within one week . The mice were killed at this stage and disease was confirmed by immunoblotting and immunohistochemical analyses of abnormal PrP deposition in the brain , as previously described [12 , 49] . Because it was difficult to determine the time of symptom onset in the animal model used in this study , survival time was defined as the time from prion infection to terminal disease . Experiments with Syrian hamsters and other mice were performed in a similar manner , as described above . Syrian hamsters and C57BL/6 mice were purchased from Japan SLC , Inc . ( Hamamatsu , Japan ) . In the case of post-infection CE administration into intraperitoneally prion-infected hamsters , hamsters in all experimental groups were given a single subcutaneous injection of CEs in such a manner that all intraperitoneal prion infections were performed with animals of the same age . 14C-TC-5RW was synthesized by the condensation of NaOH-treated TC-5RW with 14C-methyl iodide , and a pharmacokinetic study of 14C-TC-5RW in Tg7 mice was performed at Sekisui Medical Co . , Ltd . ( Tsukuba , Japan ) as follows . A designated amount of 14C-TC-5RW in saline was subcutaneously injected into the backs of mice . After a designated interval , mice under deep anesthesia were frozen and embedded in 4% carboxymethyl cellulose-Na . Whole-body 30-μm-thick sections were cut with a cryomicrotome and dried . Sections accompanied by radioactive standards were exposed to imaging plates and radioluminograms were analyzed with a BAS2500 bio-imaging analyzer ( Fuji Film , Tokyo , Japan ) . Considering both the standard calibration curve data and the 14C-TC-5RW specific radioactivity , radioactivity levels in each tissue or fluid sample were calculated from the radioluminograms . Elimination half-life was calculated using the following formula: elimination half-life ( days ) = –ln2/β , where β is the slope obtained from the simple linear regression of the natural logarithm of radioactivity levels on post-injection days . To measure the molecular sizes of 14C-TC-5RW residues in tissues , tissue samples were homogenized with five volumes of 0 . 1 N NaOH on ice , and the supernatants after centrifugation at 12 , 000×g were subjected to GPC analysis . Samples were separated on an OHpak SB-804 HQ column ( Showa Denko , Tokyo , Japan ) and eluted with 0 . 1 M NaCl at 1 mL/min and 35°C . Each 0 . 5-min fraction was mixed with the scintillation cocktail and radioactivity was assayed by liquid scintillation counting . Fluorescein-labeled HPMCs were produced as follows . HPMC in dimethylformamide ( 0 . 3 g/30 mL ) was mixed with fluorescein-5-carbonyl azide diacetate ( 1 . 5 mg ) . The mixture was purged with N2 gas and agitated at 90°C for 3 h . Labeled HPMC was recovered and then purified using repeated precipitation–solubilization steps . Residual solids were dissolved in NaHCO3 solution ( 100 mM , pH 8 . 0 ) at room temperature for 8 h to remove the acetyl-protecting groups and subsequently dialyzed against deionized water . The solution was filtered through a 0 . 45-μm pore size filter ( EMD Millipore , Billerica , MA , USA ) and then lyophilized . Fluorescein-labeled HPMCs showed no fluorescence signals in the low-molecular-weight fractions on a GPC instrument equipped with a fluorescence detector ( column , OHpak SB-804 HQ; detection , excitation at 494 nm and recording at 520 nm ) . Peritoneal macrophages were obtained from Tg7 mice by conventional thioglycollate induction . Cells ( 3 × 105 ) were incubated with fluorescein-labeled HPMC ( 1 mg/mL ) in culture medium for 1 day and then rinsed twice and lysed in a lysis buffer ( 0 . 5% sodium deoxycholate , 0 . 5% Nonidet P-40 , phosphate-buffered saline ( PBS ) , pH 7 . 4 ) . The amount of fluorescein-labeled HPMC in the cell lysate was determined by GPC analysis . Brains were homogenized in two volumes of TN buffer ( 50 mM Tris HCl , 0 . 1 M NaCl , pH 7 . 5 ) supplemented with a protease inhibitor cocktail . Spleens were homogenized and sonicated in 13 volumes of TN buffer supplemented with 0 . 5% sodium deoxycholate , 0 . 5% Nonidet P-40 , and the protease inhibitor cocktail . After low-speed centrifugation , aliquots of supernatant containing the same protein amount were analyzed for PrPC protein levels by immunoblotting with the anti-PrP monoclonal antibody 3F4 ( BioLegend , Inc . , San Diego , CA , USA ) , as previously described [19] . To analyze PrP mRNA expression , the brains and spleens of Tg7 mice were lysed using an RNA extraction reagent . Total RNA was extracted and cDNA was synthesized using a first-strand cDNA synthesis kit ( Takara Bio , Inc . , Kyoto , Japan ) . The PrP mRNA level was measured by real-time polymerase chain reaction , as previously described [49] . According to a previously described method [50] , a reaction mixture containing 0 . 1% 263K prion-infected hamster brain homogenate and 10% normal hamster brain homogenate underwent 96 cycles of sonication and incubation with an automatic cross-ultrasonic apparatus ( ELESTEIN 070-GOTW; Elekon Science Corp . , Chiba , Japan ) . TC-5RW or hydroxypropyl methyl dextran ( 70 kDa ) was added to the reaction mixture before starting the reactions at concentrations ranging 10 μg/mL to 1 mg/mL . After the reactions , the samples were digested with 100 μg/mL of proteinase K at 37°C for 1 h and levels of protease-resistant PrPSc were detected by immunoblotting with 3F4 . Mouse neuroblastoma cells either uninfected ( N2a cells ) or persistently infected with the RML prion ( ScN2a cells [24] ) were kindly provided by Dr . Byron Caughey of the Laboratory of Persistent Viral Diseases of NIAID’s Rocky Mountain Laboratories ( Hamilton , MT , USA ) and used as previously described [21 , 51 , 52] . Briefly , cells were cultured in the presence of test compounds for 3 days . Cells grown to confluency were washed with PBS and lysed with lysis buffer ( 0 . 5% sodium deoxycholate , 0 . 5% Nonidet P-40 , PBS , pH 7 . 4 ) . For the detection of PrPSc , cell lysate was treated with 10 μg/mL of proteinase K at 37°C for 30 min and subsequently with 1 mM phenylmethylsulfonyl fluoride . Then , PrPSc were precipitated by centrifugation at 10 , 000 × g and suspended in a sample loading buffer . To detect PrPC and β-actin , cell lysate was used without further treatments and mixed with a concentrated loading buffer . Immunoblotting analysis was performed using the anti-PrP monoclonal antibody SAF83 ( SPI-Bio , Massy , France ) and anti-β-actin monoclonal antibody , as described previously [49] The cell surface of PrPC was analyzed by flow cytometry , as described in previous reports [21 , 49 , 52] . Briefly , N2a cells incubated in the presence of test compounds for 3 days were dispersed using 0 . 1% collagenase and washed with ice-cold 0 . 5% fetal calf serum in PBS . Then , the cells were immunoreacted with SAF83 or isotype control IgG1 for 30 min on ice , and subsequently with goat F ( ab’ ) 2 fragment anti-mouse IgG ( H+L ) -FITC ( Beckman Coulter , Inc . , Brea , CA , USA ) for 30 min on ice . Then , the cells were analyzed using an EPICS XL-ADC flow cytometer ( Beckman Coulter , Inc . ) . Survival rates were calculated using the Kaplan–Meier method and significance was evaluated using the log-rank method . Statistical linear correlations were evaluated by the Pearson’s correlation coefficient . All analyses were performed using Excel Toukei , a statistical analysis software ( SSRI Co . , Ltd . , Tokyo , Japan ) .
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Prion diseases are progressive , fatal , neurodegenerative transmissible illnesses in humans and animals caused by prion accumulation in the brain and lymphoreticular system . Because they are prevalent in nature , with atypical forms continuing to emerge , prion diseases are potential threats to both public health and the economy . However , there are no effective methods to prevent these diseases . Here we report that cellulose ethers ( CEs ) , which are non-digestible water-soluble polysaccharides that are commonly used as inactive ingredients in foods and pharmaceuticals , show prophylactic efficacy in prion-infected animals . CEs persist in various tissues and confer sustained preventive efficacy for years , suggesting that they help to prevent prion diseases . Although the enteral absorption of CEs is limited , we found that a portion of the absorbed CEs influences disease progression . Therefore , CEs may be useful to assess disease susceptibility and prevent disease occurrence .
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2016
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A Single Subcutaneous Injection of Cellulose Ethers Administered Long before Infection Confers Sustained Protection against Prion Diseases in Rodents
|
The geometric and subcellular organization of axon arbors distributes and regulates electrical signaling in neurons and networks , but the underlying mechanisms have remained elusive . In rodent cerebellar cortex , stellate interneurons elaborate characteristic axon arbors that selectively innervate Purkinje cell dendrites and likely regulate dendritic integration . We used GFP BAC transgenic reporter mice to examine the cellular processes and molecular mechanisms underlying the development of stellate cell axons and their innervation pattern . We show that stellate axons are organized and guided towards Purkinje cell dendrites by an intermediate scaffold of Bergmann glial ( BG ) fibers . The L1 family immunoglobulin protein Close Homologue of L1 ( CHL1 ) is localized to apical BG fibers and stellate cells during the development of stellate axon arbors . In the absence of CHL1 , stellate axons deviate from BG fibers and show aberrant branching and orientation . Furthermore , synapse formation between aberrant stellate axons and Purkinje dendrites is reduced and cannot be maintained , leading to progressive atrophy of axon terminals . These results establish BG fibers as a guiding scaffold and CHL1 a molecular signal in the organization of stellate axon arbors and in directing their dendritic innervation .
Neurons are often characterized by striking polarity and extensive subcellular specialization . For example , large principal neurons in many vertebrate neural circuits consist of distinct anatomical and physiological compartments [1] , which allow distributed and compartmentalized signaling [2–4] , and may greatly increase the computation power of single neurons [5] . Indeed , the biophysical and signaling machineries of principal neurons are organized into discrete subcellular domains [6] , best exemplified by the highly restricted distribution of all major classes of ion channels along the axon–dendritic surface [7] . Superimposed upon the intrinsic compartmental architecture of principal neurons is the subcellular organization of synaptic inputs [8 , 9] , which exert further control over the biophysical properties , not only within a neuron , but also within a neural ensemble [10] . Subcellular synapse organization is a prominent feature of neuronal wiring specificity , but the underlying cellular and molecular mechanisms are not well understood . A prime example of subcellular synapse organization is the Purkinje neurons of the cerebellum . The cerebellar cortex is organized as a near lattice-like circuit architecture along the two axes of the cerebellar lobules , the translobular and parlobular planes [11] . At the focal position in the cerebellar cortex and as its sole output , Purkinje neurons are restricted in the translobular plane and receive at least four sets of subcellularly targeted excitatory and inhibitory inputs [11] . The glutamatergic parallel fibers synapse onto the slender spines of the more distal dendrites , whereas the climbing fibers prefer the stubby spines of the proximal dendrite . In addition , the GABAergic basket interneurons target Purkinje cell soma and axon initial segment ( AIS ) , whereas the stellate interneurons innervate the dendritic shafts . The mechanisms underlying subcellular synapse organization along Purkinje neurons are only beginning to be understood [12] . There is evidence that the innervation of Purkinje AIS by basket interneurons is guided by a subcellular gradient of neurofascin186 , an L1 family immunoglobulin cell adhesion molecule , recruited by the ankyrinG membrane adaptor protein [13] . On the other hand , the mechanisms that direct the innervation of Purkinje dendrites by stellate interneurons are unknown . Stellate cells mainly occupy the upper half of the molecular layer ( ML ) and are the only cell type of the upper third of the ML . Like the basket cells , stellate cells extend their axons within the translobular ( e . g . , parasagittal ) plane of the cerebellar cortex [11] . Although these axon arbors range from relatively simple to fairly complex , the most characteristic feature is their largely vertically oriented ascending and descending collaterals , which innervate multiple Purkinje dendrites along their path [11] . Unlike climbing fibers , which have been well documented to grow along and eventually innervate single Purkinje dendrites , the cellular and developmental process by which stellate axon approach and innervate Purkinje dendrites have not been described . Bergmann glia ( BG ) cells are highly polarized astrocytes , whose radial fibers dominate the cerebellar cortex [11 , 14 , 15] . During postnatal cerebellar development , the apical BG fibers form the earliest radial structures across the cerebellar cortex [14]; BG fibers subsequently undergo dramatic differentiation and are transformed into a highly elaborate meshwork , dominated by a scaffold of radial fibers [16–18] . The Bergmann glia cells are positioned to interact with multiple neuronal components and likely contribute to multiple aspects of cerebellar circuit assembly at different developmental stages . Whether BG fibers play a role in axon guidance and organization at later stages , in addition to guiding granule cell migration [19] , has not been explored . By using a genetic strategy to simultaneously label stellate axons and BG fibers at high resolution , here we provide evidence that BG fibers constitute an intermediate template in the organization of stellate axon arbors into characteristic trajectories , and in their guidance to innervate Purkinje dendrites . The L1 family immunoglobulin cell adhesion molecules ( L1CAMs ) have been implicated in axon growth , guidance [20] , and the subcellular organization of GABAergic synapses [12] . Given the role of NF186 in the targeting of basket axon and pinceau synapses to Purkinje AIS [13] , here we explored whether other members of the L1CAMs might contribute to the organization of stellate axons and innervation of Purkinje dendrites . We found that each member of the L1 family is localized to subcellular domains in neurons and glia in the developing and mature cerebellar cortex . In particular , CHL1 ( Close Homologue of L1 ) is prominently expressed on BG fibers during the development of stellate axons and their innervation . In addition , we demonstrate a crucial and highly specific role of CHL1 in the patterning of stellate axons and in targeting their innervation to Purkinje cell dendrites .
To investigate the cellular mechanisms underlying development of the stellate axon arbor and innervation pattern , it is necessary to visualize stellate axons together with their postsynaptic targets at high resolution and during the developmental process . We generated several lines of bacterial artificial chromosome ( BAC ) transgenic reporter mice to achieve such visualization . The calcium binding protein parvalbumin ( Pv ) is normally expressed in all Purkinje , basket , and stellate neurons in the postnatal cerebellar cortex . In our Pv-GFP BAC transgenic mice ( Figure 1A ) , different fractions of Purkinje , basket , and stellate neurons express green fluorescent protein ( GFP ) among different stable lines ( from a few percent to near 100%; unpublished data ) , likely due to different genomic integration sites of the transgene . In the B20 line , sparse GFP expression allowed visualization of single Purkinje , basket , and stellate cells with synaptic resolution ( Figure 1B–1E ) . Combined with generic Purkinje cell markers ( e . g . , calbindin ) , we were able to examine the precise trajectory of stellate and basket axons , and compare how they approach and innervate postsynaptic Purkinje neurons . Stellate and basket cells occupy mainly the upper or lower half of the ML , respectively . Consistent with previous Golgi studies [11] , GFP labeling revealed distinct features of stellate and basket axons in their morphology and subcellular innervation pattern , even when they are found at the same location in the mid-lower ML ( Figure 1F–1H ) . For example , basket axons were smooth , whereas stellate axons were beaded . Although basket axons extended terminal branches along Purkinje cell proximal dendrites , soma , and towards AISs ( Figure 1H ) , stellate axons clearly did not extend along the distinct contours of Purkinje dendrites . Instead , stellate axon arbors were often characterized by rather straight ascending and descending collaterals ( also described in [11] ) that crossed Purkinje cell dendrites at rather sharp angles ( Figure 1F and 1G ) . Interestingly , the axon tips of stellate cells in the lower ML often reached the Purkinje cell layer ( PCL ) , as the basket axons . However , these descending collaterals never extended along Purkinje dendrite-soma-AIS , but always had rather straight paths that terminated abruptly at the PCL ( Figure 1G ) . These contrasting features suggest that basket and stellate axons approach and innervate Purkinje neurons via profoundly different cellular and developmental mechanisms . Furthermore , the arborization and innervation patterns of stellate axons also contrast those of a dendrite-targeting climbing fiber , which grows along and “monopolizes” an entire Purkinje dendrite [11] . These comparisons raise an obvious question: how do stellate axons approach and innervate segments of multiple Purkinje dendrites without growing along any single target ? To better understand the developmental process by which stellate axons innervate Purkinje dendrites , we used our reporter mice expressing GFP from the GAD67 promoter elements ( GAD67-GFP BAC reporter mice , Figure 2A and [13] ) , which label Purkinje , basket , and stellate cells from embryonic stage to adulthood . In the G42 line , both interneurons and Purkinje cells were labeled; this line was mainly used to characterize the migration of stellate cells in the first two postnatal weeks ( summarized in Figure 2C ) . In the G1 line , GFP was mainly expressed by basket and stellate cells; this line was used to characterize the development of stellate axons . Basket and stellate cells are derived from dividing progenitors in the postnatal cerebellar white matter ( WM; [21] ) . These progenitors migrate into the cerebellar cortex in the first two postnatal weeks as simple unipolar cells until arriving in the ML . They then undergo a series of morphological transformations that culminate in formation of mature interneurons during the third and fourth postnatal week . However , the morphological maturation of stellate axons has not been well described . Compared to basket cells , stellate cell precursors migrate into the ML a few days later , peaking between postnatal day 8 and 11 ( P8–P11 ) but continue to arrive as late as P14 ( Figure 2B–2D; also see [22] ) . Using our G1 reporter mice , we found that upon reaching their positions in the ML , stellate cells first appeared bipolar and extended largely horizontally oriented neurites ( Figure 2B; also see [21] ) . Between P16–18 , stellate axons sent ascending and descending collaterals ( Figure 2E ) , which further gave rise to plexus of more elaborate branches in the subsequent 2 wk ( Figures 2F ) . Mature stellate axon arbors range from relatively simple to fairly complex; the most characteristic feature is their largely vertically oriented ascending and descending collaterals [11] . Our GFP labeling is highly consistent with these previous descriptions using Golgi methods ( Figure 2E and 2F , and unpublished data ) . The stereotyped morphology and development of stellate axons pose an obvious question: how are they organized into characteristic trajectories , presumably by mechanisms other than Purkinje cell dendrites ? Besides Purkinje dendrites , an equally prominent cellular component of the cerebellar cortex are the BG fibers [15] ( Figures 2D–2F and S1 ) . In rodents , BG are present during embryonic stages [23]; they migrate to the cerebellar cortex before birth , and their radial fibers reach the pia to form characteristic endfeet by late embryonic stages [14] . BG fibers thus represent the earliest radial structures across the cerebellar cortex , before the arrival of Purkinje neurons [14] . During the first postnatal week , BG fibers are thin , smooth , and unbranched . The glia-specific cytoskeleton protein GFAP can be detected by P4 [24] . The simple BG fibers subsequently undergo profound morphological differentiation and maturation [16 , 18 , 25] . During the second week , when Purkinje dendrites extend , BG fibers differentiate in a deep to superficial gradient: whereas BG fibers transversing the external granule layer ( EGL ) remain smooth , they extend coarse lateral appendages in the underlying ML [26] . During the third and fourth week , BG fibers further branch , extend lateral varicoses and fine processes , eventually forming an extensive reticular meshwork [16 , 18 , 25] . Consistent with these results , using single-cell electroporation to label BG with GFP , we found that BG fibers project highly irregular lateral branches during the third postnatal week ( Figure S4A ) . Furthermore , using transgenic mice expressing GFP under the control of a mouse GFAP promoter [27] , we were able to visualize the extensive meshwork of the BG system in the ML , and found that GFAP was largely concentrated in the radial BG fibers , but not the finer lateral appendages and processes ( Figure S4B ) . In addition to the apical radial fibers in the ML , BG cell bodies also give off numerous lamellar processes that enwrap Purkinje cell soma and AIS after the third postnatal week [11 , 14] , although the more precise timing of this process is unclear . Mature BG cells are thus highly polarized astrocytes with distinct subcellular specializations . The vertical bias of the orientation of stellate axon collaterals prompted us to examine their relationship with BG fibers during the development of dendritic innervation . As expected , when stellate cell precursors were migrating across the PCL in the second postnatal week , GFAP-positive BG fibers were prominent throughout the ML ( e . g . , P8 , Figure 2D ) . Upon reaching their destination in the ML , stellate cells began to extend neurites . Although their axons extended in different directions , many of their descending/ascending branches were strictly associated with GFAP-labeled BG fibers ( Figure 2E ) . This association was particularly prominent in the upper ML , where stellate axons often perfectly followed the curving BG fibers for tens of microns , and remained so in subsequence weeks ( Figure 2F ) . Such extensive association with BG fibers contrasts the rather patchy and “en passant–type” interaction between Purkinje dendrites and BG fibers [14 , 16 , 28] . Our detection of association between stellate axons and Bergmann glia was probably an underestimate , since the finer lateral BG appendages were not well labeled by GFAP . Importantly , there was no association between basket axons and BG fibers ( Figure 2G ) , consistent with the finding that basket terminals grow along the proximal dendrite-soma-AIS of Purkinje cells ( Figure 1H ) . To substantiate this finding , we further examined the association of GABAergic synaptic markers with BG fibers . GAD65 , an isoform of glutamic acid decarboxylase , is localized to GABAergic presynaptic terminals and physically coupled to synaptic vesicles ( [29] ) . The onset of GAD65 expression has been shown to coincide with GABAergic synaptogenesis in the cerebellum [30] . We focused our analysis to the upper ML , where most , if not all , GAD65 signals are derived from stellate cell axons . At P16 , shortly after stellate neurons begin to send their axons and made synaptic contacts , double labeling revealed a 52% colocalization between GAD65 and GFAP ( Figure 3A ) . This colocalization increased to 65% in the more mature ML ( Figure 3B and 3C ) . To rule out the possibility that these levels of colocalization can be reached by chance , we artificially shifted the confocal image stacks of GFAP horizontally relative to that of GAD65 by 5 μm , and then reanalyzed GAD65 and GFAP colocalization ( since BG fibers were arranged vertically with an average gap of approximately 5 μm between neighboring fibers; see Materials and Methods ) . This shift analysis revealed a highly significant 30% decrease in GAD65-GFAP association ( p ≤ 0 . 01 , n = 20 different sections in 3 different mice ) , indicating that the organization of GAD65 along BG fibers was not due to chance . This analysis is likely an underestimate of GAD65–BG association since GFAP antibodies did not label well the finer BG processes ( Figure S4B and S4E ) . In addition to the statistical association , strings of GAD65 puncta , indicative of an underlying stellate axon branch , were frequently seen to perfectly align with GFAP fibers ( Figure 3B and 3C ) . The combined observations suggest that BG fibers in the cerebellar cortex provide a growth template , which may organize stellate axons into characteristic orientations and trajectories . These results are consistent with ultrastructural observations that stellate cell axons and presynaptic terminals are surrounded by glial processes during the third postnatal week [14] . Since Purkinje dendrites are the major postsynaptic targets of stellate axons , our results raise the question of whether and how BG fibers guide stellate axons to Purkinje dendrites . Mature Purkinje dendrites bear large numbers of synaptic boutons , but much of their surface is ensheathed by a thin BG process [14] . The glial sheath of a dendritic segment is thought to consist of processes derived from several neighboring BG cells [14]; and it has been recognized since Cajal that the BG fibers are intercalated between the dendritic trees of successive Purkinje cells [11] . Using our Pv-GFP reporter mice , which label individual Purkinje dendrites , and GFAP antibody , we found that BG fibers most often intersected dendritic shafts at sharp angles and did not extend along dendrite at significant length ( Figures 3D and S1A ) . Furthermore , in GFAP-GFP transgenic mice , which occasionally gave sparse labeling of BG cells , double labeling with calbindin antibody showed that a single BG fiber most likely encounters several intercalated Purkinje dendrites ( Figure S1B ) . Therefore , BG fibers impinge upon and enwrap multiple Purkinje dendritic segments in a patchy , en passant pattern . To examine the precise relationship among stellate cell presynaptic terminals , BG fibers , and Purkinje dendrites , we performed triple labeling with GAD65 and GFAP antibodies in our Pv-GFP mice . As expected , GAD65 puncta colocalized with the shafts of Purkinje dendrites , occasionally aligned in a “beads along a string” pattern , indicative of a stellate axon branch ( Figure 3D1 ) . Importantly , the same GAD65 puncta and clusters were also precisely aligned along a GFAP fiber ( Figure 3D2 ) , indicating that stellate axon boutons are formed at the intersection between BG fibers and Purkinje dendrites ( Figure 3D3 ) . Together , these results suggest that BG fibers in the ML represent an “intermediate scaffold , ” which may guide stellate axons to approach Purkinje dendrites in defined orientation and trajectories , and form synaptic contacts at the intersection between BG fibers and Purkinje dendrites ( Figure 3G ) . To explore the molecular mechanisms underlying the GABAergic innervation of Purkinje dendrites , we took a candidate gene approach and focused on the L1CAMs . The L1CAM subfamily consists of L1 , CHL1 , NrCAM , and neurofascin [20] . We have previously shown that a Purkinje cell–specific splice variant of neurofascin ( NF186 ) directs the innervation of axon initial segment by basket cell axons [13] . We therefore systematically examined the expression pattern of every L1CAM during the postnatal development of the cerebellar cortex . Interestingly , each member was localized to distinct subcellular compartments in neurons and glia cells ( Figure S2 ) . During the third postnatal week ( e . g . , P16 ) , whereas NF186 was highly restricted to AIS-soma of Purkinje cells [13] , L1 was abundantly expressed in parallel fibers and other unmyelinated and premyelinated axons ( Figure S2D and S2G ) . NrCAM was more diffusely ( but certainly not ubiquitously ) expressed in the ML , although the precise cellular and subcellular locations could not be ascertained ( Figure S2E ) . Interestingly , in the PCL , NrCAM appeared to localize to the basal lamellae of BG that wrapped around Purkinje soma and AIS ( Figure S2E ) . Finally , using an antibody to a peptide epitope in the FNIII domain of CHL1 ( Figure 3 ) , we found that CHL1 was distributed in a prominent radial stripe pattern that resembled BG fibers along with diffuse labeling in the ML ( Figure 4A–4D ) . Indeed , CHL1 closely colocalized with GFAP ( Figure 4E ) , but not the Purkinje dendrite marker calbindin ( Figure S2F ) . Such colocalization with GFAP was detected throughout postnatal development ( unpublished data ) . We further characterized the postnatal developmental expression of CHL1 . At P8 , when stellate cells were just migrating across the PCL , CHL1 was already prominent along BG fibers ( Figure 4A1; colocalization with GFAP not shown ) . CHL1 was subsequently also detected along the lateral appendages during the second and third week ( P14–20 , Figure 4C1 and 4E ) . Importantly , along the polarized BG cells , CHL1 was mainly localized to the apical radial fibers and processes , but not to the basal lamellae that extend towards Purkinje cell AIS ( Figure 4F ) . This pattern in the PCL was clearly distinct from that of NrCAM ( Figure S2E ) . CHL1 expression subsequently diminished in the BG fibers and became more diffuse , yet prominent , in the molecular layer ( Figure 4D1 ) . In situ hybridization indicates that CHL1 is also expressed in stellate interneurons and granule cells at P14 , but not in mature Purkinje neurons [31] . Consistent with these data , CHL1 immunofluorescence appeared in stellate cell somata as early as P14 , and remained at P18 and P40 ( Figure 4A2–D2 ) . It was difficult to determine whether CHL1 was also distributed along stellate axons and/or dendrites because of the more diffuse labeling in the ML . Lower levels of CHL1 expression in the ML remained in adulthood ( in 1-y-old mice , unpublished data ) . To investigate whether CHL1 plays a role in the GABAergic innervation of Purkinje dendrites , we first examined the expression of the presynaptic marker GAD65 in the ML of CHL1 knockout mice ( Figure 5A and 5C ) . As a control , we also surveyed all the viable L1CAM mutant mice using the same assay ( Figure 5E–5H ) . The vast majority of GABAergic terminals in the ML are derived from stellate axons; Purkinje collaterals and basket axons only contribute to a small minority near the PCL [11] . Purkinje dendrites are the predominant targets of stellate axons , although the dendrites of stellate , basket , and Golgi cells are also innervated [11] . In the adult cerebellar cortex ( >P40 ) , we found a profound reduction of GAD65 labeling in CHL1−/− mice , but not in L1−/− and NrCAM−/− mice ( Figure 5E–5H ) . This reduction was specific to the ML layer: GAD65 labeling at Purkinje AIS in CHL1−/− mice was identical to that of wild-type ( WT ) littermates , L1−/− mice , and NrCAM−/− mice ( Figure 5A and 5C , and unpublished data ) . We took advantage of this result to quantify GAD65 signals in the upper ML as a ratio to those at the Purkinje cell AIS . Such quantification revealed an approximately 60% reduction ( p ≤ 0 . 01 , n = 4 mice ) of GAD65 in CHL1−/− mice compared to their WT littermates ( Figure 5I ) . This significant reduction was not due to a defect in the migration of stellate cells , since stellate cell density and distribution in the ML assayed by Pv immunofluorescence were the same as those in WT mice ( Figure 5B and 5D ) . Furthermore , calbindin staining did not reveal any discernable defects of Purkinje dendrites . We also examined glutamatergic innervation of Purkinje dendrites . The density of parallel fiber synapses and climbing fiber synapses detected by vGluT1 and vGluT2 [32] immunofluorescence , respectively , showed no differences between CHL1−/− and WT mice ( Figure S5A–S5F ) . The ultrastructures of parallel fiber and climbing synapses also appeared normal ( Figure S5G–S5K ) . These results suggest that , among the L1CAMs , CHL1 appears to play a highly specific role in the GABAergic innervation of Purkinje dendrites . The GAD65 assay itself does not rule out the possibility that stellate innervation of other cell types may also be affected . Although CHL1 has been shown to modulate radial migration of certain populations of pyramidal neurons in sensory areas of developing neocortex [33] , we did not find notable defects in density and position of Purkinje neurons in the cerebellar cortex , although subtle defects cannot be ruled out . We did notice occasional mispositioning of BG cell soma in the granule cell layer ( Figure S1C ) . BG fibers labeled by GFAP were also largely normal , except that they occasionally appeared somewhat less well organized ( Figure S1 ) . It is not clear whether these are due to a direct effect of CHL1 deficiency in BG or an indirect consequence of their disrupted association with stellate axons . To investigate the role of CHL1 in the development of stellate axons , we examined the morphology of single stellate axon arbors using our Pv-GFP ( B20 ) mice . In the ML of mature WT B20 mice ( P44 ) , stellate axons display complex arbors with characteristic orientations ( Figure 6A ) ; a majority of these axon branches displayed a predominantly vertical orientation and were associated with GFAP-labeled BG fibers ( Figure 6C–6E ) . Quantification of the orientation of stellate axon branches relative to the pia surface revealed that they followed a Gaussian distribution , with a peak between 80° and 100° ( Figure 6C ) . In addition , 70% of these vertically oriented axon branches were associated with GFAP-positive fibers ( Figure 6D and 6E ) . Even when axons branched and turned , they often switched between neighboring BG fibers ( Figure 6A3; indicated by arrowheads and stars ) . Mature stellate axons bore distinct boutons , and more than 90% of these boutons contained the synaptic marker GAD65 ( Figure 7A and 7B ) . In PV-GFP ( B20 ) ::CHL1−/− littermates , most stellate axons still were able to develop fairly complex arbors at this age , but appeared thinner , more wavy , with significantly altered orientation and trajectories ( Figure 6B ) . When double labeled with GFAP , the notable defects were their reduced association with BG fibers and the reduction of vertically oriented branches . Indeed , the orientation of axon branches was much more evenly distributed ( Figure 6C ) , and many of these more horizontally oriented axons often simply crossed over the BG fibers ( Figure 6B3 ) . Quantification revealed that less than 30% of stellate axon branches were associated with GFAP fibers , regardless of their orientation , indicating a significant reduction compared to that in WT mice ( Figure 6D and 6E ) . The altered arbor morphology of stellate axons and their reduced association with GFAP fibers was apparent at P16 and P20 ( compare Figure S6A and S6B with Figure 2 ) . In several extreme cases in P44 CHL1−/− mice , stellate axons were grossly abnormal , with much-reduced branching and simpler arbors . These axons extended rather randomly , twisted , tangled , and even circled around ( Figure S6C ) , with apparently a complete loss of orientation preference . The failure to interact with GFAP fibers may have profoundly altered stellate axonal organization and trajectory in CHL1−/− mice . These axons also bore smaller boutons ( Figure 7C and 7D ) , and only 50% of these boutons contained detectable GAD65 , a 43% reduction compared to WT mice ( p ≤ 0 . 001; Figure 7E and 7F ) . Importantly , these defects were highly specific to stellate axon , basket axons and their innervation of Purkinje AISs appeared entirely normal in CHL1−/− mice both at single-cell resolution ( Figures 7C2 and S7 ) and when assayed with GAD65 ( Figure 5C ) . We used electron microscopy to directly examine stellate synapses on Purkinje dendrites . We restricted our analysis on the upper third of the ML , where all symmetric synapses are derived from stellate axons . In WT mice at P44 , stellate terminals exhibiting symmetric synapses were identified along the Purkinje dendritic shafts as clear varicosities containing densely studded , flattened vesicles ( Figure 7G ) . The density of stellate terminal boutons with symmetric synapses was quantified against Purkinje dendritic surface area from serial ultrathin sections to avoid overlooking stellate terminal profiles . In CHL1−/− littermates , morphologically normal terminal boutons with symmetric synapses were clearly present along Purkinje dendrites ( Figure 7H ) , with diameters ranging from 0 . 4–0 . 7 μm , and an active zone length of 0 . 15–0 . 26 μm . However , the density of symmetric synapses was reduced by 60% ( p ≤ 0 . 001 ) . At P30 , there was also a significant reduction in the density of symmetric synapses by approximately 40% ( p < 0 . 03 ) . On the other hand , basket axon synapses on Purkinje somata , parallel fiber synapses on dendritic spines , and climbing fiber synapses on dendritic shafts were all indistinguishable between P44 WT and CHL1−/− mice ( Figures S5G–S5K , S7C , and S7D ) . Much more severe defects of stellate axon terminals in CHL1−/− mice were detected at older ages . In 3-mo-old mutants , degenerating axon profiles were frequently seen in the upper ML , exhibiting electron-dense membrane accumulations and electron-lucent empty spaces ( Figure 7J ) . On the other hand , nearby climbing fiber terminal profiles along the same Purkinje dendrites were perfectly normal . Together , these ultrastructural results suggest that in the absence of CHL1 , aberrantly organized and oriented stellate axons can still manage to contact Purkinje dendrites and form synapses , but at significantly reduced efficiency and density . In addition , these synapses cannot be maintained , leading to atrophy of stellate axon terminals . Besides BG , CHL1 is also expressed in other cell types , such as stellate cells , granule cells , and their parallel fibers in the developing cerebellum [31] . To further investigate the role of CHL1 in BG , we bred a conditional CHL1 mutant strain ( CHL1flx ) ( see Materials and Methods ) with a transgenic lines expressing CRE recombinase under the control of GFAP [34] . At P14 , P20 , and P40 in GFAP-Cre::CHL1flx/flx mice , CHL1 expression was undectable along BG fibers but was clearly present in stellate cells ( Figure 8A–8C ) . At P40 , there was a significant reduction of GAD65 density in GFAP-Cre::CHL1flx/flx mice compared to CHL1flx/flx controls ( Figure 8D , 8F , and 8H; 27 ± 7%; p ≤ 0 . 05 ) . We also deleted CHL1 in Purkinje cells by breeding CHL1flx mice with the L7-Cre transgenic mice [35]; there was no reduction of GAD65 density at P40 ( Figure 8G and 8H ) , suggesting that CHL1 in Purkinje cells , if any , was not involved in the development of stellate synapses . These results suggest that CHL1 expression in BG contributes to the development of stellate cell synaptic innervation in the ML . Compared with germline CHL1−/− mice ( Figure 5E and 5H ) , the intermediate reduction of GAD65 in the ML of GFAP-Cre::CHL1flx/flx may be due to two reasons . First , the association between stellate axon and BG fibers may be mediated by CHL1 homophilic as well as heterophilic interactions; absence of CHL1 in BG fibers thus partially impairs the association of stellate axons with BG fibers and the innervation of Purkinje dendrites . CHL1 expression in stellate cells likely also plays a significant role . Second , it is possible that only the GABAergic innervation of Purkinje dendrites ( but not stellate dendrites , for example ) is guided by CHL1 expression on BG fibers; absence of CHL1 in BG fibers thus only partially reduced the GAD65 signal in the ML .
In mature cerebellar cortex , each BG cell gives rise to several ascending BG fibers , which extend approximately 40–50 μm in the translobular plane and 15–20 μm in the parlobular plane [14 , 15] . Interestingly , these largely radial fibers from neighboring BG cells are further aligned as thin walls , or palisades , in the parlobular plane perpendicular to a Purkinje dendrite , which extends approximately 300–400 μm in the translobular plane and 15–20 μm in the longitudinal plane [14 , 15] . The consequence of these arrangements is that several BG palisades cut across a single Purkinje dendrite [14 , 15] . Although this striking spatial organization of BG fibers has long been recognized and postulated to contribute to the architecture of the cerebellum , no specific neuronal elements and developmental process have been identified that rely on such fine arrangement . By high-resolution labeling of stellate axons superimposed upon BG and Purkinje cells , we realized that BG fibers may be an ideal intermediate scaffold to “presort” a stellate axon into characteristic trajectories and distribute them towards multiple Purkinje dendrites . During cerebellar development , BG fibers represent the earliest radial structures across the cerebellar cortex , even before the arrival of Purkinje neurons [14 , 23] . The initially simple BG fibers undergo dramatic differentiation and maturation in the second to fourth postnatal week and are transformed into a highly elaborate meshwork , dominated by the vertical palisades [14 , 16 , 18 , 25 , 26] . Although the elaborate BG fibers appear to be positioned to interact with multiple neuronal components , such as migrating granule cells [19 , 36] , and likely contribute to multiple aspects of cerebellar circuit assembly at different developmental stages , our discovery of their close association with the developing stellate axons is particularly compelling . First , the association was apparent as soon as stellate cells begin to extend axons during the second postnatal week . Second , stellate axons often strictly followed the curving contours of BG fibers for tens of microns , as well as the lateral appendages of BG fiber . Finally , the association between BG fibers and stellate axons was specifically disrupted by the loss of an immunoglobulin family cell adhesion molecule expressed in both BG fibers and stellate cells . It is thus likely that BG fibers mainly serve as a growth template for stellate axons , and additional molecular and/or activity-dependent mechanisms may regulate the size and exuberance of axon arbors . Interestingly , BG processes also express GABAA receptors that enwrap inhibitory synapses [37]; it is thus possible that BG fibers may respond to GABA signaling from developing stellate cell axons . Mature stellate axons extend characteristic ascending and descending collaterals as well as plexus of finer branches and terminals [11] . Our GFAP labeling of BG likely underestimated their association with stellate axons . It is possible that the GFAP-positive BG fibers may represent “highways” for stellate axon collaterals , and that the lateral appendages and processes may serve as “local roads” for axon terminals to approach and innervate Purkinje dendrites . In both invertebrates and vertebrates , the crucial role of glia cells in axon guidance has been well recognized [38 , 39] . Glial cells can function as guideposts to attract [40–42] , repel [43–45] , or stop [46] growth cones of projection neurons [38 , 47] , and can also serve as intermediate targets to coordinate pre- and postsynaptic interactions [46 , 48] . In the developing rodent olfactory bulb , radial glial cells interact with olfactory receptor neuron axons [49] and have been postulated to contribute to the formation of glomeruli [50] . At hippocampal excitatory synapses , astrocytes form tripartite complexes with pre- and postsynaptic structures , and regulate synapse morphogenesis and maturation [51 , 52] . Here , we provide the first evidence to our knowledge that the characteristic astroglial processes organize the axon trajectory of GABAergic interneurons and contribute to the establishment of precise patterns of connectivity in complex local circuits , including subcellular synapse targeting . In many areas of the vertebrate brain ( e . g . , neocortex and hippocampus ) , highly abundant and morphologically elaborate astrocytes mature during postnatal development along with the assembly of local circuits . It is thus possible that an astroglial intermediate scaffold might be a more general mechanism for directing the trajectory of axon extension , pre- and postsynaptic target interaction , and complex patterns of innervation . Like other members of the L1CAM [20] , CHL1 is expressed in both neurons and glia [31 , 53] . Although there is evidence that CHL1 promotes and inhibits neurite outgrowth in vitro through both heterophilic and homophilic interactions , respectively [54 , 55] , and may regulate hippocampal axon projection and organization [56 , 57] , the cellular interactions involved and the logic of CHL1′s action have been unclear . The well-defined architecture and connectivity in cerebellar cortex present an advantage in defining the cellular and subcellular expression of CHL1 and in dissecting its role in axonal and synapse development . CHL1 is prominently localized to apical BG fibers since the first postnatal week , and subsequently extend to the lateral appendages during the second and third postnatal week . We cannot ascertain whether CHL1 is also expressed in the fine BG fiber processes ( due to the presence of CHL1 in parallel fibers and possibly other neural elements in the ML ) . Importantly , CHL1 is not localized to the basal lamellae of BG cells , which extend to Purkinje soma and AIS . Such polarized distribution of CHL1 in BG cells may present a permissive substrate for the growth and patterning of stellate axons and for their restriction to the ML to innervate Purkinje dendrites . In addition , CHL1 is expressed in stellate cells , but not in Purkinje neurons [31] . CHL1 immunoreactivity could be clearly detected in stellate cell somata by P14 ( Figure 4 ) , although its subcellular distribution ( on axons and dendrites ) was difficult to discern . In our analysis of CHL1−/− mice , the trajectory and orientation of stellate axons and their innervation of Purkinje dendrites were profoundly aberrant . In contrast , basket axons and their innervation of the Purkinje soma-AIS were entirely normal . In addition , Purkinje dendrites and their glutamatergic innervation by climbing fibers and parallel fibers also appeared intact , even though CHL1 is known to be expressed in granule cells and parallel fibers [31 , 53] . These results reveal a highly specific role for CHL1 in the patterning of stellate cell axon arbors . The significant reduction of GAD65 puncta in the ML may result from a reduction in the number of stellate synapses , deficient synapses , or both . Whereas double labeling and confocal microscopy detected a reduced localization of GAD65 to stellate boutons , ultrastructural analysis confirmed a significant reduction of stellate synapses along Purkinje dendrites . Interestingly , a recent study shows that CHL1 is localized at presynaptic terminals of glutamatergic and GABAergic axons in dissociated hippocampal cultures [58]; CHL1 appears to be targeted to synaptic vesicles by endocytosis in response to synapse activation and regulates the uncoating of clathrin-coated synaptic vesicles [58] . It is thus conceivable that the absence of CHL1 in stellate cell axons may impair GABAergic vesicle endocytosis and GAD65 synaptic localization . We suggest that CHL1 deficiency results in dissociation of stellate axons from their normal BG fiber “tracks , ” aberrant axon orientation and trajectory , which contribute to subsequent deficiency in synapse formation and stability . Our current analysis cannot distinguish whether the decreased number of GABAergic synapses from stellate onto Purkinje cells in CHL1−/− mice results from the inability of the stellate axon to engage in synapse assembly , deficient cell adhesion prior to synapse assembly , or deficient synapse maintenance . The reduction of GAD65 signals in the ML of BG-restricted CHL1 knockouts further pinpoints a specific role of CHL1 in BG fibers . On the other hand , the intermediate phenotype in these mice compared to that in germline CHL1−/− mice implies that CHL1 in other cell types , e . g . , stellate and granule cells , may also contribute to their axon and synapse development . It is possible that CHL1 may localize to stellate axons and contribute to arbor patterning through homophilic interaction with CHL1 distributed on BG fibers . On the other hand , unknown CHL1 ligands in stellate cells and BG fibers may mediate heterophilic interactions during stellate axon development . Indeed , CHL1 can act as a coreceptor for neuropilin-1 to mediate axon guidance by semaphorin3A during development of the thalamocortical projection [59] . During the third postnatal week , CHL1 expression in stellate cells might also promote the maturation and stability of synaptic innervation through heterophilic interactions with Purkinje dendrites and hetero- or homophilic interaction with BG fibers . Finally , CHL1 might also be localized to stellate dendrites , which are innervated by other stellate axons . Deficiencies in stellate axon arbor and synaptic innervation in CHL1−/− mice may contribute to the impairment in their motor behaviors , such as the ability to maintain balance on an accelerated Rota-Rod [60] . Although it was once debated whether basket cells and stellate cells were variants of the same class of cerebellar interneurons , it is now established that they constitute distinct cell types , likely with distinct genetic origins [61] , and a fundamental difference is their subcellular target innervation . In both cell types , the final axon arbor and innervation pattern is achieved through sequential developmental processes , which may involve: the pattern and order of their migration into the ML , the elaboration of axon arbors along defined cellular substrates and adhesion mechanisms , and the formation–stabilization of synaptic contacts along different compartments of Purkinje neurons . Here , we demonstrate that stellate and basket cells deploy different cellular and molecular mechanisms to achieve their distinct axon arborization and innervation patterns . The basket cells make synaptic contacts along the soma-AIS of a Purkinje cell , a highly restricted synaptic target area . It is perhaps not surprising that basket axons arrive at their destination , in part , by growing along the Purkinje proximal dendrite-soma-AIS , guided by a subcellular gradient of neurofascin [13] . The stellate cells , on the other hand , face a rather different task when innervating Purkinje dendrites: even though each Purkinje dendrite is a largely 2-dimensional , flat target , it expands hundreds of microns in the translobular plane . Unlike a climbing fiber , which adheres to and monopolizes a single Purkinje dendrite , a stellate axon innervates segments of multiple dendrites , often with characteristic descending and ascending collaterals . It is thus not obvious how stellate axons can ever achieve such a distinct innervation pattern by direct and strong adhesion to Purkinje dendrites . The BG fibers seem to provide a useful solution to this problem . As an extensive and largely radial scaffold in the ML , the BG fibers are well suited to organize and deliver stellate axons to Purkinje dendrites , with defined orientations and trajectories . In addition , by relying on a glial instead of neuronal substrate , stellate axons may reduce the risk of making ectopic and unnecessary synaptic contacts . Furthermore , the BG fibers appear to direct both the patterning of axon arbor and subcellular innervation . It remains to be investigated whether such an intermediate glial scaffold is a more general strategy to sculpt precise neuronal connections in other brain areas . We present evidence that , CHL1 , a close homolog of neurofascin186 , is involved in the development of stellate axons and their dendritic innervation . Our results suggest that different members of the L1 family may contribute to axon patterning and subcellular synapse organization in different cell types , and may act in glia as well as in neurons . The subcellular recruitment of NF186 is achieved by the ankyrinG membrane adaptor protein at the Purkinje AIS [13] . It is tempting to speculate that another form of ankyrin in BG cells may organize CHL1 subcellular localization . In addition to permissive/attractive signals , such as NF186 to basket axons and CHL1 to stellate axons , repulsive or bifunctional signals ( depending on different axon types ) at distinct subcellular sites may also contribute to topographically precise synapse organization . The identification of physiological ligands for NF186 and CHL1 in basket and stellate axons will further our understanding of the underlying molecular mechanisms .
BAC clones containing the mouse parvalbumin ( PV ) genes were identified from the RPCI-23 library ( CHORI ) . A BAC clone containing the entire PV gene and approximately 150 kb of upstream and 25 kb downstream regions was used for BAC modifications . A GFP expression cassette was inserted in the first coding exon at the translation initiation site using a procedure developed by Yang et al . [62] . Circular BAC DNAs were injected into the fertilized eggs of the C57BL/6 strain at a concentration of 0 . 5 ng/μl in microinjection buffer ( 10 mM Tris [pH 7 . 4] , 0 . 15 mM EDTA [pH 8 . 0] ) using standard procedures and as described previously ( Ango et al . , 2004 [13] ) . Five transgenic founders were identified by PCR and confirmed by southern blotting . All founder lines resulted in germline transmission . GFP expression was first analyzed in fixed brain sections immunolabeled with antibodies to various GABAergic interneuron markers: Pv , somatostatin , calretinin , and VIP . In the cerebellum , different fractions of Purkinje , basket , and stellate neurons expressed GFP among different transgenic lines , from a few percent ( the B20 line ) to near 100% ( the B13 line , and unpublished data ) , likely due to different genomic integration sites of the transgene . The onset of GFP usually started in the late second postnatal week and increased to higher levels by the fourth week . The GAD67-GFP reporter mice were described in Ango et al . , 2004 [13] . The CHL1−/− mice were described in [56] . L1−/− and NrCAM−/− mice were provided by Drs . Dan Felsonfeld and Dr . Martin Grumet , respectively . The CHL1 conditional mutant will be published elsewhere ( Kolata et al . , unpublished data ) . The L7-cre mice [34] were obtained from Mutant Mouse Regional Resource Centers ( MMRRC ) and the GFAP-cre mice [33] from JAX Mice . Mice were anesthetized ( sodium pentobarbitone , 6 mg/100 g of body weight ) and transcardially perfused with 4% paraformaldehyde in phosphate buffer ( pH 7 . 4 ) . Sagittal sections ( 80-μm thick ) were cut from the cerebellum using a vibratome ( Leica VT100 ) . Brain sections were blocked in 5% NGS and 0 . 1% Triton X-100 , and immunostained with antibodies against GAD65 ( monoclonal antibody , 1:1 , 000; Boehringer ) , GFP ( rabbit or chicken polyclonal antibody , 1:500; Chemicon ) , Pv ( monoclonal antibody , 1:1 , 000; Sigma ) , CHL1 ( chicken polyclonal antibody , 1:500 ) , calbindin ( rabbit polyclonal antibody , 1:1 , 000; Swant ) , and GFAP ( rabbit polyclonal; Geko ) . Sections were incubated with either Alexa594-conjugated goat anti-mouse or anti-rabbit IgG and Alexa488-conjugated goat anti-rabbit or anti-chicken IgG ( 1:500; Molecular Probes ) and mounted . Sections were imaged using a 63× water immersion objective ( Zeiss ) using a confocal microscope ( Zeiss LSM510 ) under the same conditions . Scans from each channel were collected in multiple-tracks mode and subsequently merged . Care was taken to use the lowest laser power , and no bleedthrough was visible between the Alexa594 and Alexa488 channels . SHIFT analysis . All confocal images were acquired using the same microscope setting . Confocal stacks were first merged using maximum transparency setting . The maximum Z stack used was 2 μm . Using the ImageJ software , the green ( GFAP ) and the red ( GAD65 ) channels were then separated and transformed into grey-level 8-bit images before being thresholded . The minimum size of GAD65 puncta was set to between 12 to 750 pixels ( signals smaller or larger would not count it ) . The total number of GAD65 puncta ( X ) was measured using the dot counting function of ImageJ . The grey color images of GFAP and GAD65 were then remerged . Since both images were grey , those GAD65 puncta that colocalized with GFAP were fused into the GFAP signals ( as “bubbles along fiber”-like patterns ) and would be excluded from the counting procedure set above . Thus in the remerged image , only the GAD65 puncta that were not colocalized with GFAP ( Y ) were counted . With this approach , we were able to count the number of GAD65 puncta in a nonbiased way using the counting function of ImageJ . We then obtained the percentage of GAD65 puncta that colocalized with GFAP as ( X − Y ) / X * 100 . The same procedure was used before and after shifting the GFAP image relative to that of GAD65 by ±5 μm . The Wilcoxon signed rank test was used for paired comparisons of GAD65 puncta density and colocalization with GFAP . Significance was set at p < 0 . 05 , and values are means ± standard deviation ( s . d . ) Analysis of stellate axon orientation and their association with GFAP . All analyses were done blind to the genotype . All ascending and descending axonal branches with a length greater that 4 μm was included in our analysis . Axonal branches of individual neurons were visualized with GFP in our PV-GFP ( B20 ) mice ( eight neurons in at least five different mice in each genotype ) . From each selected axonal branch , its length ( X ) was first measured with the LSM confocal software ( Zeiss ) . The axonal length that colocalized with GFAP ( Y ) was then measured; and the proportion of the branch that colocolized with GFAP was obtained as Y / X * 100 . We measured the angle of each axon branch in relation to the pia surface , which was defined as a horizontal line in our projected image at the 0° angle . An axon branch that was perfectly perpendicular ( ascending or descending axonal branches ) to the pia would be at the 90° angle . We set a virtual horizontal line ( the closest to the pia surface orientation ) for each branch and measured its angle in relation to the virtual horizontal line . We took into account only branches with angles between 50° to 130°; and these angles of axon branches were grouped into 10° bins . Values in each bin were pooled together and analyzed with Kaleidagraph ( Synergy Software ) or Excel ( Microsoft ) software . Paired comparisons of GAD65 density and colocalization with GFAP used the Wilcoxon signed rank test . Significance was set at p < 0 . 05 . Parameter values are means ± s . d . Antibodies against CHL1 ( CS1123 ) were raised in chicken against a peptide with the sequence SLLDGRTHPKEVNILR corresponding to the region within the third FNIII domain of the protein plus an N-terminal cysteine for coupling . The specificity of the CHL1 antibodies was confirmed using CHL1−/− mice , and COS cells transfected a CHL1 expression construct ( Figure S2 ) . Production and IGY purification was done by Covance Immunology Service . Similar staining patterns , but higher intensity , were seen with a polyclonal antibody from R&D Systems . Brains were perfusion fixed according to routine procedures as described earlier [63] . Briefly , deeply anaesthetized mice were transcardially perfused with a brief rinse in phosphate buffer , 0 . 1 M ( pH 7 . 4 ) , followed by a solution of 4% freshly depolymerized paraformaldehyde and 0 . 1% glutaraldehyde in phosphate buffer , supplemented with 2% PVP and 0 . 4% NaNO2 . The brains were removed from the skull and left in the same fixative for at least several days . Sagittal vibratome sections of 50–60 μm were postfixed in 1% osmium tetroxide with 1% sodium ferricyanide in 0 . 1 M cacodylate buffer for 20 min , dehydrated in series of ethanol , and then flat embedded in epoxy resin . Semithin sections ( 1 μm ) were cut and stained with toluidine blue and used for orientation purposes . Ultrathin sections of selected areas of the cerebellar cortex with reference to the ML were cut , using an ultratome LKB IV ( Reichert-Jung ) . and collected on single-slot grids or 75-mesh grids coated with Formvar ( Electron Microscopy Sciences ) Ultrathin sections were contrasted with uranyl acetate and lead citrate , and analyzed in a Philips CM 100 transmission electron microscope ( FEI Electron Optics ) . Morphological analysis . Synapses were defined by the presence of a clear postsynaptic density facing a number of synaptic vesicles . By means of a goniometer , sections could be tilted in the beam , thereby determining the symmetry or asymmetry of the synaptic profiles . Measurements of profile length and diameter were made using a morphometric program ( Soft imaging system SIS; Olympus ) . P3–P5 pups were anesthetized with ketamine ( 0 . 56 mg/g; xylazine , 0 . 03 mg/gm body weight ) . After incision of the skin overlying the skull , a small hole was made directly over the left hemisphere of the cerebellum . A patch pipette filled with 1–2 μl of GFP DNA construct ( endotoxin-free preparation ) were injected directly into the tissue ( 1 μg/μl DNA ) , and mouse pups were subjected to electric pulses ( four to six pulses at 200 mv/cm for 50 ms with intervals of 950 ms ) by gold-plated electrode ( BTX ) placed directly on the skull . The skin was then sutured . After recovery from anesthesia , pups were returned to mother under standard housing . Mice were then sacrifice at P16 and analyzed .
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Large principal neurons in vertebrate neural circuits often consist of distinct anatomical and physiological compartments , which allow distributed and compartmentalized signaling and greatly increase the computational power of single neurons . Superimposed upon this intrinsic compartmental architecture is the subcellular organization of synaptic inputs , which exert local control over the biophysical properties and differentially regulate the input , integration , and output of principal neurons . In the cerebellar cortex , Purkinje neurons are innervated by GABA inhibitory synapses from the stellate and basket cells at dendrites and soma-axon initial ( AIS ) segments , respectively . Previous studies have shown that an L1 family immunoglobulin cell adhesion molecule ( neurofascin186 ) is distributed as a subcellular gradient and directs basket cell axons to innervate Purkinje cell AIS . Here , we examine the mechanisms underlying the innervation of Purkinje cell dendrites by stellate axons . We found that stellate axons are organized into characteristic trajectories and guided towards Purkinje dendrites by an intermediate scaffold of astroglia—the Bergmann glial ( BG ) fibers . Another member of L1 family , Close Homologue of L1 ( CHL1 ) , is localized to BG fibers and stellate cells , and contributes to the organization of stellate axons along BG fibers and to the innervation of Purkinje cell dendrites .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"neuroscience",
"cell",
"biology"
] |
2008
|
Bergmann Glia and the Recognition Molecule CHL1 Organize GABAergic Axons and Direct Innervation of Purkinje Cell Dendrites
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Infection of macrophages by Yersinia species results in YopJ-dependent apoptosis , and naïve macrophages are highly susceptible to this form of cell death . Previous studies have demonstrated that macrophages activated with lipopolysaccharide ( LPS ) prior to infection are resistant to YopJ-dependent cell death; we found this simultaneously renders macrophages susceptible to killing by YopJ− Yersinia pseudotuberculosis ( Yptb ) . YopJ− Yptb-induced macrophage death was dependent on caspase-1 activation , resulting in rapid permeability to small molecules , followed by membrane breakdown and DNA damage , and accompanied by cleavage and release of proinflammatory interleukin-18 . Induction of caspase-1-dependent death , or pyroptosis , required the bacterial type III translocon but none of its known translocated proteins . Wild-type Yptb infection also triggered pyroptosis: YopJ-dependent activation of proapoptotic caspase-3 was significantly delayed in activated macrophages and resulted in caspase-1-dependent pyroptosis . The transition to susceptibility was not limited to LPS activation; it was also seen in macrophages activated with other Toll-like receptor ( TLR ) ligands and intact nonviable bacteria . Yptb infection triggered macrophage activation and activation of caspase-1 in vivo . Y . pestis infection of activated macrophages also stimulated caspase-1 activation . These results indicate that host signaling triggered by TLR and other activating ligands during the course of Yersinia infection redirects both the mechanism of host cell death and the downstream consequences of death by shifting from noninflammatory apoptosis to inflammatory pyroptosis .
The genus Yersinia includes three species pathogenic for humans: Yersinia pestis , the causative agent of plague , and Y . entercolitica and Y . pseudotuberculosis , which cause gastroenteritis and lymphadenitis and occasionally systemic infection . All pathogenic Yersinia species harbor a 70 kb virulence plasmid , which encodes a type III secretion system ( T3SS ) and the effector proteins translocated by this system [1] . The structural components of the T3SS include the needle complex and the secreted proteins YopB and YopD , which form a conduit through the host cell membrane to allow entry of bacterial effector proteins directly into the host cytosol . Once the effector proteins ( Yops E , H , O , M , and J ) reach the cytosol , they function primarily to inhibit phagocytosis and suppress the host inflammatory response triggered upon bacterial interaction [2] . In addition , all three pathogenic Yersinia species are able to induce cell death in naïve macrophages , and this requires the translocated effector YopJ [3–5] . Two signals are required for maximal induction of cell death in Yersinia-infected naïve macrophages , YopJ and signaling through host Toll-like receptor 4 ( TLR4 ) [6 , 7] . Upon contact with a macrophage , Yersinia lipopolysaccharide ( LPS ) recognized by host TLR4 simultaneously initiates apoptotic signaling through the adapter protein TRIF [8 , 9] as well as mitogen-activated protein kinase ( MAPK ) - and nuclear factor kappa B ( NF-κB ) -dependent up-regulation of inflammatory cytokine production and cell survival genes [10–12] . However , YopJ inhibits the activation of NF-κB and MAPKs [13–15] , allowing apoptotic signaling to predominate . TRIF-dependent signaling leads to cleavage of the apoptotic initiator caspase-8 [9] and release of cytochrome c from the mitochondria [16] . This leads to activation of downstream executioner caspases-9 , −7 , and −3 and apoptosis of Yersinia-infected naïve macrophages [16] . Although inducing cell death via apoptosis could potentially suppress inflammation and eliminate macrophages , a host cell type hypothesized to play an important role in combating Yersinia infection [5 , 17] , the relative importance of these YopJ-dependent processes during Yersinia infection is somewhat controversial . Some groups report no change in virulence of YopJ mutant bacteria [18–20] and others observe varying degrees of attenuation [21 , 22] . In vivo , Yersinia delays inflammation in a T3SS-dependent manner , allowing the bacteria to proliferate [23] . However , the pathology resulting from infection is strikingly biphasic: as infection progresses , Yersinia no longer controls the inflammatory host response resulting in the influx of neutrophils and macrophages , increased inflammatory cytokine production , and tissue necrosis [24–28] . The presence of both host inflammatory mediators and/or bacterial products during infection could result in macrophage activation [29] , which is thought to play a critical role in the resolution of Yersinia infection [5 , 17] . Pretreatment of mice with the macrophage-activating cytokines tumor necrosis factor alpha and interferon gamma confers protection to lethal challenge [23] , and dysregulation of the normal LPS modifications made by Yersinia increases their stimulation of macrophages and allows the host to control infection [30] . This suggests that a greater understanding of the differing responses of naïve and activated macrophages to Yersinia infection will provide insight into the immunopathogenesis involved in establishing an ongoing infection , as well as generating protective host immune responses . Activation of macrophages alters their adhesion , migration , and cytokine production , and increases antigen endocytosis , antigen presentation , and activation of effector functions [29] . Importantly , macrophage activation alters the cellular response to death inducing stimuli [10 , 12 , 31 , 32] . Previous studies indicate the toxic effects of YopJ are altered in activated macrophages: LPS pretreated macrophages activate NF-κB , a process inhibited by YopJ in naïve macrophages , and YopJ-dependent apoptosis is correspondingly reduced [33] . In this study we examined the response of activated macrophages to Y . pseudotuberculosis ( Yptb ) infection in vitro and in vivo . TLR-mediated suppression of apoptosis leads to Yptb-induced macrophage cell death being redirected to a caspase-1-dependent inflammatory pathway called pyroptosis [34] , and this process depends upon an intact Yptb T3SS . We also observed the characteristics of this mechanistic shift in host cell execution , macrophage activation and activation of caspase-1 , occurring during Yptb infection in vivo . Together our observations suggest modulation of host cell death pathways is an important response to infection .
Infection of macrophages with Yptb results in the induction of apoptosis that is dependent on the effector YopJ [3 , 4 , 35] . Treatment of macrophages with LPS prior to infection with Yersinia has been shown to decrease YopJ-dependent apoptosis [33] . We confirmed that LPS pretreatment of macrophages ( macrophage activation ) [29] prior to infection with wild-type Yptb reduced macrophage cell death by approximately 50% as measured by release of cytosolic lactate dehydrogenase ( LDH ) ( Figure 1A ) . In addition , macrophage activation increased LDH release from background levels to 30% during infection with a yopJ mutant . Both phenotypes were observed at LPS concentrations as low as 1 ng/ml ( Figure 1A ) . Altered sensitivity of activated macrophages to cell death induced by Yptb infection may result from a change in Yptb:macrophage interactions; therefore , the ability of Yptb to interact with naïve and activated macrophages was compared . Naïve and LPS-activated macrophages were infected with green fluorescent protein ( GFP ) -expressing wild-type or YopJ− Yptb and examined by microscopy . For all conditions , greater than 98% of macrophages had one or more associated bacteria immediately after infection ( Figure 1B ) . At 2 h postinfection , over 94% of macrophages were associated with multiple bacteria ( Figure 1B and 1C ) . Additionally , translocation of effector proteins into the cytosol of naïve and activated macrophages was measured during infection with Yptb expressing YopE fused to the Bordetella pertussis calmodulin-dependent adenylate cyclase ( Cya ) , resulting in accumulation of cAMP when YopE-Cya reaches the host cell cytosol [36] . Activation of macrophages did not reduce the level of effector translocation ( unpublished data ) . These results demonstrated that activation of macrophages did not affect the ability of Yptb to associate with macrophages or translocate effectors , but appeared to alter the cellular response to infection . The similar levels of LDH release observed with wild-type and YopJ− Yptb infection of activated macrophages ( Figure 1A ) led us to hypothesize that the same process occurred during infection with both strains . We therefore assessed the kinetics of two nonspecific markers of cell death , membrane damage and DNA damage [37] , during infection of activated macrophages with wild-type and YopJ− Yptb . Using uptake of a small membrane impermeant dye , ethidium bromide ( EtBr , MW = 394 Da ) , allowed us to quantitatively examine membrane damage in individual cells during infection . EtBr uptake in uninfected macrophages was less than 2% ( Figure 2A and 2C ) . Infection with wild-type or YopJ− Yptb resulted in very similar kinetics of EtBr uptake: 10%–15% cells were EtBr+ cells at 60 min postinfection , and this increased to 40%–45% EtBr+ cells by 120 min , and did not increase in the next 120 min of infection ( Figure 2C ) . We used terminal deoxynucleotidyl transferase-nick end labeling ( TUNEL ) to examine DNA damage , and again , the kinetics were nearly identical during infection with both strains ( Figure 2B and 2D ) . The percent of TUNEL-positive cells remained low until 180 min after infection; 15% of infected macrophages were TUNEL-positive at this time point . This increased to greater than 40% by 240 min , compared to less than 2% in uninfected macrophages ( Figure 2B and 2D ) . Similar kinetics of wild-type and YopJ− Yptb stimulated membrane and DNA damage during infection of activated macrophages is consistent with our hypothesis that both strains activate the same process . Importantly , membrane damage significantly preceded DNA damage ( Figure 2 ) . This observation is in contradistinction to YopJ-dependent apoptosis induced during wild-type Yptb infection of naïve macrophages , which has been previously described [3 , 4 , 11 , 16 , 35] . DNA damage began before membrane damage during wild-type Yptb induction of apoptosis in naïve macrophages ( Figure S1A–S1D ) , and as shown in Figure 1A , YopJ− Yptb was unable to kill naïve macrophages . As expected , induction of apoptosis by wild-type Yptb activates apoptotic caspases-3 and −8 [9 , 16] , a caspase-3 inhibitor correspondingly inhibits DNA damage , and also as shown previously [6 , 7] , TLR4 signaling facilitates apoptosis during wild-type Yptb infection of naïve macrophages ( Figure S1E–S1G ) . Finally , infection of naïve macrophages with wild-type Yptb results in the typical nuclear condensation characteristic of apoptosis ( Figure S2A ) [3 , 4 , 35] , in contrast to the diffuse distribution of TUNEL-positive DNA observed in activated macrophages infected with wild-type or YopJ− Yptb ( Figure S2B ) . Thus , the features of wild-type and YopJ− Yptb-induced cell death in activated macrophages , which include membrane permeability preceding DNA damage with morphological features excluding apoptosis [38] , suggest an alternative mechanism of cell death . LPS activation renders macrophages susceptible to cell death induced by ATP treatment [32 , 39] or Francisella tularensis infection [40] , and both processes involve caspase-1 . The features of YopJ− Yptb-induced cell death , rapid membrane permeability preceding DNA damage , and the lack of nuclear condensation , also suggest caspase-1-dependent cell death or pyroptosis [38 , 41] . We therefore hypothesized that YopJ− Yptb-induced cell death was dependent on caspase-1 . EtBr uptake by YopJ− Yptb infected macrophages was reduced by the specific caspase-1 inhibitor YVAD [42] , but not by the negative control peptide zFA ( Figure 3A ) , indicating caspase-1 is required for increased membrane permeability during infection . Additionally , the downstream events of membrane breakdown and release of LDH were inhibited by YVAD ( unpublished data ) . DNA damage was caspase-1-dependent; the percentage of TUNEL positive cells was reduced in the presence of YVAD and unchanged by zFA ( Figure 3B ) . Features of wild-type Yptb-induced apoptosis in naïve macrophages were not inhibited by YVAD ( unpublished data ) , indicating YVAD was not nonspecifically inhibiting Yptb or apoptotic caspases . Finally , we examined supernatants collected from activated macrophages infected with YopJ− Yptb for the presence of the inflammatory cytokine interleukin ( IL ) -18 , which is specifically cleaved and activated by caspase-1 [43] . Cleaved IL-18 was present in supernatants from macrophages infected with YopJ− Yptb , but not uninfected macrophages , and IL-18 processing was blocked by YVAD ( Figure 3C ) . This demonstrated that the features of YopJ− Yptb induced cell death are caspase-1-dependent and accompanied by cleavage and release of the caspase-1 substrate IL-18 . Pyroptosis induced by several other bacteria requires a functional T3SS [38 , 44–47] . YopB and YopD are structural components of the Yersinia type III translocon , and both are required for translocation of effector proteins into host cells [2] . To examine the requirement for the T3SS in Yptb-induced pyroptosis , activated macrophages were infected with YopB− Yptb; this mutant was unable to alter host membrane permeability ( Figure 4A ) . In addition to YopJ , Yersinia translocates several other effectors into the macrophage cytosol ( Yops E , H , O , and M ) [2] , and we examined the role of these effector proteins in inducing pyroptosis . Infection of activated macrophages with YopEHJKOM− Yptb , a mutant lacking all of the known translocated effectors but competent for type III translocation ( YopBD+ ) , increased macrophage membrane permeability and uptake of EtBr ( Figure 4A ) . Furthermore , infection by YopEHJKOM− Yptb , but not YopB− Yptb , resulted in release of cleaved IL-18 ( Figure 4B ) . Infection with Yersinia mutants lacking multiple effectors , but competent for type III translocation ( YopBD+ ) , results in pore formation in the host cell membrane and uptake of small molecules similar to EtBr in size [48 , 49] . This pore was thought to be the type III translocon composed of YopB and YopD . However , caspase-1 activation can lead to formation of membrane pores [41] , and we hypothesized pore formation by YopEHJKOM− Yptb was instead a host-mediated process dependent upon caspase-1 . Consistent with this idea , YVAD inhibited EtBr uptake by activated macrophages infected with YopEHJKOM− Yptb ( Figure 4C ) . Importantly , we demonstrated the YopB/D translocation pore is formed and functional in the presence and absence of YVAD; a YopE-Cya fusion protein is translocated equally in both conditions ( Figure 4D ) . Additionally , membrane breakdown and LDH release was completely inhibited by YVAD , but not zFA ( Figure 4E ) . These data indicate pyroptosis induced by Yptb requires the T3SS , but none of its known translocated effector proteins , and host cell membrane damage and EtBr uptake are caspase-1-mediated processes stimulated by Yptb infection . We observed pyroptosis in activated macrophages infected with Yptb that lack YopJ but contain a functional T3SS . During infection of naïve macrophages with wild-type Yptb , YopJ and TLR4 signaling are required for maximal activation of caspase-3 and apoptosis [6 , 7 , 9] . However , macrophage activation can dampen future TLR4-mediated signaling events [50 , 51] , and result in synthesis of gene products that inhibit the activation/activity of apoptotic caspases , including caspase-3 [10–12] . We therefore hypothesized that macrophage activation would decrease YopJ-dependent caspase-3 activation and apoptosis during subsequent infection with wild-type Yptb , and simultaneously stimulate pyroptosis . As expected , wild-type Yptb infection of naïve macrophages resulted in rapid caspase-3 activation ( Figure 5A ) and cleavage of the caspase-3 substrate inhibitor of caspase-activated DNase ( ICAD ) [52] ( Figure 5B , left ) . Infection with YopJ− Yptb did not result in caspase-3 activity ( Figure 5A ) or degradation of ICAD ( Figure 5B ) , regardless of the activation state of the macrophages . However , in activated macrophages infected with wild-type Yptb , caspase-3 activity was undetectable until 150 min postinfection ( Figure 5A ) and no ICAD degradation was detected ( Figure 5B , right ) , which together confirm the lack of caspase-3 activity in these infected cells ( Figure 5A ) . An early feature of pyroptosis is permeability to EtBr ( Figure 2A and 2B ) , and activated macrophages infected with wild-type or YopJ− Yptb became permeable to EtBr with identical kinetics ( Figure 6A ) . Importantly , wild-type Yptb infection of activated macrophages resulted in EtBr uptake prior to any detectable increase in caspase-3 activity ( Figure 5A ) , unlike infection of naïve macrophages , where caspase-3 activity precedes EtBr uptake ( unpublished data ) . Activation of caspase-1 was examined by infecting macrophages in the presence of a fluorescently labeled inhibitor that irreversibly binds active caspase-1 ( FAM-YVAD ) [53] . Both wild-type and YopJ− Yptb infection resulted in FAM-YVAD staining ( Figure 6B ) , and wild-type Yptb infection of activated macrophages also induced cleavage and release of the caspase-1 substrate IL-18 into the supernatant ( Figure 6C ) . These data confirmed that activation of macrophages prior to infection alters host cell responses to wild-type Yptb , suppressing YopJ-dependent apoptosis and simultaneously enhancing pyroptosis , resulting in caspase-1 activation , increased membrane permeability , and release of bioactive IL-18 prior to any detectable caspase-3 activation . Activation of macrophages in vitro alters susceptibility to cell death , and redirects infected macrophages to utilize the inflammatory pyroptosis pathway . In addition to LPS , other TLR ligands are present during Yptb infection in vivo , and may activate macrophages and increase their sensitivity to pyroptosis . Activation of macrophages with a TLR2 ligand ( Pam3CSK ) prior to infection with YopJ− Yptb increased pyroptosis to levels equivalent to LPS activation ( Figure 7A ) . Pretreatment with whole heat-killed Yptb , which contain both TLR2 and TLR4 ligands [33] , at ratios as low as one Yptb per macrophage also enhanced pyroptosis ( Figure 7B ) . The TLR3 ligand poly ( I:C ) had a similar effect ( unpublished data ) ; although signaling through TLR3 may not be relevant in the context of Yptb infection , it supports the hypothesis that the redirection of macrophage death is a generalized host response to TLR stimulation . We hypothesized that the abundance of activating ligands during Yptb infection would result in macrophage activation in vivo . Macrophages activated in vitro with LPS or Pam3CSK express increased levels of surface ICAM-1 ( Figure 7C ) , which was used to monitor activation of F4/80+ macrophages and their susceptibility to pyroptosis in vivo . In mice infected orally with wild-type Yptb , splenic macrophages express increased surface ICAM-1 ( Figure 7D ) , and this was observed in six of 14 infected mice ( Figure S3 ) . This was also observed in the mesenteric lymph nodes ( MLNs ) ; 16 of 18 mice with colonized MLNs contained macrophages with increased surface ICAM-1 expression ( Figure S3 ) . The activation state of macrophages from wild-type Yptb infected mice suggested that these macrophages would be susceptible to pyroptosis; therefore , caspase-1 activation was examined by FAM-YVAD staining of splenocytes directly ex vivo . We observed an increase in the percentage of F4/80+ macrophages that were caspase-1hi ( Figures 7E and S4; Table S1 ) from 12 . 2% ( ± 1 . 86% ) in uninfected mice to 29 . 0% ( ± 5 . 76% ) in infected mice with activated macrophages ( p = 0 . 0009 ) . Additionally , macrophages from Yptb-infected mice that had no detectable increase in surface ICAM-1 expression had caspase-1 activity similar to macrophages from uninfected mice ( Figure S4; Table S1 ) . Macrophages with high levels of active caspase-1 ( caspase-1hi , Figure 7E ) expressed greater surface ICAM-1 when compared to macrophages with lower levels of active caspase-1 from the same infected tissue ( Figure 7F ) . This confirms the activation of macrophages during wild-type Yptb infection and demonstrates that macrophage activation is necessary for increased activation of caspase-1 , and correlates with our in vitro data demonstrating that wild-type Yptb infection of activated macrophages results in caspase-1-dependent pyroptosis . To address the T3SS dependence of caspase-1 activation in vivo , mice were infected with Yptb lacking the T3SS-encoding pIB1 virulence plasmid . pIB1− Yptb do not induce pyroptosis in vitro ( unpublished data ) , but colonize the MLNs of infected mice as well as wild-type Yptb ( Figure 7G ) [28 , 54] , and cause macrophage activation in vivo as measured by the increased expression of ICAM-1 ( Figure 7H , wild-type; Figure 7I , pIB1− ) . However , the percentage of caspase-1int+hi macrophages from pIB1− Yptb-infected mice is significantly less than in wild-type Yptb infected mice ( 27 . 6% ± 4 . 57% versus 42 . 2% ± 2 . 18% , p < 0 . 003; Figure 7J ) , and macrophages from pIB1− Yptb-infected mice had levels of active caspase-1 similar to uninfected mice ( 27 . 6% ± 4 . 57% versus 23 . 0% ± 8 . 49% , p = 0 . 32 ) . These results confirm the activation of caspase-1 during Yptb infection in vivo , and the requirement for the T3SS-encoding virulence plasmid to activate caspase-1 , thereby implicating the bacterial T3SS in this process in vivo . Yptb is closely related to Y . pestis , the causative agent of plague , and Yersinia spp . share several features including the plasmid encoded type III secretion apparatus [2]; therefore , we hypothesized that Y . pestis infection of activated macrophages would also result in pyroptosis . Activated macrophages were infected with a Y . pestis mutant competent for type III translocation , but lacking all translocated effectors ( Δ1234 ) [55] . Like Yptb , Y . pestis causes activation of caspase-1 as demonstrated by staining with FAM-YVAD ( Figure 8A , top ) . Y . pestis lacking the T3SS-encoding virulence plasmid ( pCD1− ) failed to induce FAM-YVAD staining in activated macrophages ( Figure 8A , bottom ) , suggesting caspase-1 activation induced by Y . pestis also requires the T3SS . Infection of activated macrophages with Y . pestis also resulted in LDH release that was blocked by the caspase-1 inhibitor YVAD ( Figure 8B ) ; indicating Y . pestis contains the ligand responsible for caspase-1 activation , and this leads to caspase-1-dependent lysis of activated macrophages .
Our results demonstrate the ability of macrophage activation to fundamentally alter the host response to Yptb infection . In naïve macrophages , the YopJ-mediated inhibition of proinflammatory signaling [13–15] and induction of apoptosis [3 , 4 , 35] have been well described . However , in activated macrophages YopJ no longer functions in this capacity , and activation of the apoptotic executioner , caspase-3 , is suppressed such that activation of macrophages results in susceptibility to caspase-1-dependent pyroptosis . The features of pyroptosis in Yptb-infected macrophages included early membrane permeabilization followed by DNA damage , and inflammatory cytokine processing and release . Macrophage activation may enhance sensitivity to pyroptosis by increasing synthesis of host proteins involved in triggering the activation of caspase-1 in response to Yersinia; pyroptosis is not observed during infection of naïve macrophages with YopJ− Yptb . Alternatively , macrophage activation may overcome the ability of translocated Yersinia effector proteins to inhibit the activation of caspase-1 [56] . This is the first report of proinflammatory pyroptosis induced by wild-type Yersinia , bacteria previously thought to neutralize macrophages exclusively by noninflammatory apoptosis . In vitro , Yersinia species are capable of suppressing inflammatory cytokine production in response to bacterial products [13–15] , and during the early phase of infection in vivo , there is a marked lack of inflammation and inflammatory cytokine production [23 , 24] . This suggests that the majority of macrophages interacting with Yersinia in vivo would have a naïve phenotype , and this is consistent with the YopJ-dependent macrophage death observed [19 , 21] , and the lack of caspase-1 activation when the bacterial burden is low and macrophages are not activated ( Figure S4; Table S1 ) . However , as infection progresses , histological examination of Yersinia-infected tissues reveals extensive inflammation and inflammatory cytokine production [24–28] . We have demonstrated that the inflammatory nature of Yptb infection leads to macrophage activation and up-regulation of surface ICAM-1 , indicating that macrophages become resistant to YopJ and sensitive to pyroptosis . This result was confirmed by the finding that activated macrophages from Yptb-infected mice also contain active caspase-1 , and this process required the T3SS-encoding virulence plasmid , and therefore was likely dependent on the T3SS . In vivo , we have not formally excluded the involvement of plasmid-encoded gene products that are not part of the T3SS in caspase-1 activation; however , we feel this is unlikely considering our results confirming the T3SS-dependence of pyroptosis in vitro . T3SS-dependent pyroptosis and inflammatory cytokine production may help explain the ability of T3SS+ Yptb to induce greater levels of tissue necrosis than T3SS− Yptb [28] , even in the presence of type III effectors capable of suppressing inflammation [2] . Our results suggest that during Yersinia infection in vivo macrophages encounter TLR or other activating ligands that trigger a host-mediated switch from YopJ-dependent apoptosis to pyroptosis . In addition , we predict macrophage populations that are continuously encountering bacterial products , like those in the Peyer's patches ( PPs ) , would be refractory to the effects of YopJ . Consistent with this hypothesis , YopJ does not confer a replicative advantage in the PPs; YopJ− Yptb replicate as well as wild-type in the PPs of infected mice [19 , 21] . PP macrophages may also be inherently susceptible to pyroptosis; unfortunately , we were unable to analyze caspase-1 activation in the PPs due to the low numbers of cells present . Superficially , Yersinia infection of activated or naïve macrophages simply results in host cell death; however , the responses of other host cells to apoptosis and pyroptosis are quite different . Apoptotic cells often display surface markers that facilitate their uptake by neighboring cells [57] and prevent release of inflammatory intracellular contents from dying cells . Phagocytes that encounter apoptotic cells produce anti-inflammatory cytokines TGF-β and IL-10 and produce lower levels of several inflammatory cytokines [58 , 59] and costimulatory molecules [60] . This potent anti-inflammatory response is able to modulate the adaptive immune response by reducing the ability of antigen-presenting cells to stimulate T cells [61] . The anti-inflammatory nature of apoptosis is consistent with the ability of YopP ( functionally equivalent to YopJ ) to delay priming of T cells during Y . entercolitica infection [62] . In contrast , pyroptosis is intrinsically inflammatory , as the cell death process is linked to maturation and release of inflammatory cytokines . Pyroptosis also results in rapid lysis and release of intracellular contents [38 , 41] that can act as “danger signals” and promote the immune response [61 , 63] . Yersinia-induced macrophage death could result in drastically different outcomes depending on the activation state of the macrophage , even though the immediate consequence in both naïve and activated macrophages is simply cell death . The role of IL-18 and IL-1β in enhancing immune responsiveness has been thoroughly demonstrated . Both induce inflammatory cytokine production and increased expression of adhesion molecules , recruiting neutrophils and lymphocytes to sites of infection [64] . Correspondingly , Yersinia-infected mice have increased numbers of neutrophils in colonized tissues [26 , 28] . IL-18 also plays a major role , in conjunction with IL-12 , in stimulating interferon gamma production [43] . Depending on the cytokine milieu , IL-18 can stimulate CD4+ T cell differentiation to Th1 or Th2 phenotype [65] . Both IL-18 and T cell responses are critical in controlling Yersinia infection in vivo , as IL-18–deficient mice [66] and mice lacking T cells [67] are unable to resolve the infection , and adoptive transfer of Yersinia-specific T cells confers partial protection against challenge [68] . Thus , redirecting macrophages to undergo pyroptosis appears to play an important role in generating an appropriate and effective immune response to Yersinia . The activation of caspase-1 is initiated by recognition of cytosolic ligands by members of the NOD-leucine-rich repeat family of proteins . This recognition triggers formation of a multiprotein complex called the inflammasome , which then acts as a platform for the activation of caspase-1 [69] . Induction of pyroptosis by Yptb requires the bacterial T3SS but none of its known effectors . We hypothesized that the Yersinia T3SS actively or passively transports a caspase-1–activating ligand into the macrophage cytosol . Recent studies with Salmonella and Legionella have implicated cytosolic flagellin in activating caspase-1 through the NOD-like receptor family member Ipaf [70–73] . Y . pestis strains have a mutation inactivating flhD [74] that results in suppression of flagellin subunit production , and the observed lack of motility and flagella [75] . Our observation that Y . pestis also induces caspase-1 activation suggests the delivery of an alternative caspase-1 activating ligand to the host cytosol , and experiments to identify the ligand ( s ) produced by Yersinia species are ongoing . Bacterial pathogens are often capable of modulating host cell processes , including cell death . Pathogens prevent cell death to maintain a protective intracellular environment or replicative niche [76 , 77] , or induce cell death to eliminate host cells and suppress immune function [5 , 78] . In addition , activation of caspase-1-dependent inflammatory programmed cell death , or pyroptosis , in response to cytosolic bacterial ligands may serve as a host defense mechanism [70–73] . This study demonstrates host-mediated redirection of Yersinia-induced cell death; recognition of host inflammatory mediators and bacterial products results in inhibition of apoptosis , a noninflammatory process thought to benefit the bacteria , and primes macrophages to die by pyroptosis , potentially benefiting the host by shifting host cell responses toward inflammation .
Yptb strains used in the present study were wild-type ( YPIII ) and the following mutants derived from this strain: YP26 YopJ− [15] , YP18 YopB− [15] , and YP37 YopJOEHKM− [79] ( a gift from Dr . James Bliska ) . A plasmid expressing green fluorescent protein was generated by inserting the LacZ promoter ( bases 246–575 ) from pBluescriptSK− into the EcoRI and BamHI sites of pDW1 [80] . A yopE::cyaA fusion was constructed as described [36] and inserted into the HindIII and BamHI sites of pBR322 . pIB1− Yptb were generated as described [81] and screened by PCR to confirm loss of multiple yop genes . Bacteria were routinely cultured in LB at room temperature . For macrophage infections , overnight cultures were back-diluted 1:40 into LB containing 20 mM sodium oxalate and 20 mM magnesium chloride and grown at room temperature with shaking for 1 h followed by incubation at 37 °C with shaking for 2 h . Bacteria were harvested and resuspended in PBS for infection . Yersinia pestis strains used in the present study were KIM8 Δ1234 [55] and pCD1− plasmid-cured ( a gift from Dr . Greg Plano ) . Y . pestis was grown as described for Yptb and sonicated briefly prior to infection to reduce clumping . Heat-killed YPIII were prepared by growing the bacteria as for infection , washing cells and resuspending in PBS , and incubating at 65 °C for 1 h . Bone marrow-derived macrophages ( BMDMs ) were isolated from the femur exudates of C57BL/6 mice ( Jackson Laboratories ) and cultured at 37 °C in 5% CO2 in Dulbecco's minimal essential medium ( DMEM , Invitrogen ) supplemented with 10% FCS , 5 mM HEPES , 0 . 2 mg/ml L-glutamine , 0 . 05 mM β-mercaptoethanol , 50 mg/ml gentamicin sulfate , and 10 , 000 U/ml penicillin and streptomycin with 30% L-cell-conditioned medium [82] . After 6–7 d of incubation , macrophages were collected by washing with ice-cold PBS containing 1 mM EDTA , resuspended in supplemented antibiotic-free DMEM containing 5% FCS , and allowed to adhere for 18–24 h before infection . Macrophages were activated with ultrapure LPS from Salmonella minnesota ( List Biologicals ) at a final concentration of 100 ng/ml unless otherwise indicated , 100 ng/ml Pam3CSK ( EMC microcollections ) , or heat-killed wild-type YPIII for 18 h prior to infection . Medium was replaced 1 h before infection , and contained 200 μM YVAD . cmk and zFA . fmk ( Calbiochem ) when indicated . Bacteria were added at a multiplicity of infection of 20 and spun briefly at 200 g to bring bacteria into contact with macrophages . Gentamicin sulfate was added to 100 μg/ml at 2 h . Efficiency of infection was confirmed by infection with GFP-expressing Yptb followed by incubation for 5 min or 2 h . Macrophages were stained using Texas Red-phalloidin or Alexa 633-phalloidin per the manufacturers instructions and examined by confocal microscopy using the BioRad MRC-600 or Leica SL confocal microscope in the W . M . Keck Center for Advanced Studies in Neural Signaling ( University of Washington , Seattle , WA ) . The number of macrophages with associated bacteria was determined from multiple fields . Macrophages grown in 96-well plates were infected with Yptb , and supernatants were evaluated for the presence of the cytoplasmic enzyme LDH using the Cytotox 96 kit ( Promega ) as directed by the manufacturer's instructions . Percentage cytotoxicity was calculated as 100 × ( experimental LDH − spontaneous LDH ) ÷ ( maximum LDH release − spontaneous LDH ) . Macrophages were infected with Yptb containing pYopE::cyaA at an MOI of 20 for 1–2 h . 2 × 104 macrophages were lysed in 0 . 1 M HCl , and cAMP levels were determined by using the Direct cAMP Correlate-EIA Kit ( Assay Designs ) and normalized for protein content determined by the Bradford Protein Assay ( Bio-Rad ) . Macrophages were infected with Yptb for the indicated length of time and the Caspase-3/7 Glo Assay ( Promega ) was performed according to the manufacturers instructions . Briefly , 60 μl of Caspase-3/7 Glo reagent was added to 1 × 104 macrophages in 60 μl of medium and incubated at room temperature for 1 h . Luminescence was measured using a TECAN GENios Pro . Caspase-3/7 activity is reported as relative light units ( RLU ) of infected samples minus uninfected control . For ICAD immunobloting , 1 . 5 × 106 macrophages were harvested at 2 h postinfection and lysed in sample buffer . Proteins were separated by 15% SDS-PAGE and transferred to nitrocellulose membranes . ICAD cleavage was assessed by Western blotting using anti-ICAD antibodies and peroxidase conjugated secondary antibodies ( BDPharMingen ) . Immunoblots were developed with and enhanced chemiluminescence system ( Amersham Biosciences ) . Anti-p44/p42 antibodies were used to confirm equal loading . Macrophages grown on glass coverslips were infected with Yptb for the indicated length of times . Media was removed and adherent cells were stained with SYTO 10 ( Molecular Probes ) and ethidium bromide at 25 μg/ml ( Sigma-Aldrich ) in HBSS for 5 min . Coverslips were analyzed using a BioRad MRC-600 or Leica SL confocal microscope in the W . M . Keck Center for Advanced Studies in Neural Signaling . The means and standard deviations ( SDs ) were derived from counting three fields for uninfected samples and six fields for infected samples . Macrophages grown on glass coverslips were infected with Yptb , and DNA strand breaks were detected using terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling ( TUNEL ) using the In Situ Cell Death Detection Kit as directed by the manufacturer's instructions ( Roche Applied Science ) . Coverslips were mounted using ProLong antifade ( Molecular Probes ) and analyzed using a BioRad MRC-600 or Leica SL confocal microscope in the W . M . Keck Center for Advanced Studies in Neural Signaling . The means and SDs were derived from counting three fields for uninfected samples and six fields for infected samples . Macrophages grown on glass coverslips were infected with Yptb for 90 min total and carboxyfluorescein-YVAD-fluoromethyl ketone ( FAM-YVAD; Immunochemistry Technologies ) was added to 1× at 30 min postinfection . Macrophages were washed thoroughly to remove unbound FAM-YVAD and then stained with Alexa 633 phalloidin ( Molecular Probes ) per the manufacturers instructions . Bacteria were labeled using anti-Yptb and anti-rabbit PE ( Abcam ) antibodies . Coverslips were mounted using ProLong antifade ( Molecular Probes ) and analyzed using Leica SL confocal microscope in the W . M . Keck Center for Advanced Studies in Neural Signaling . Macrophages were infected in serum-free media , and at the indicated time points the supernatant was removed , sterilized using a 0 . 22 μm filter , and concentrated using a 10 , 000 MWCO Centricon Plus-20 centrifugal filter device ( Millipore ) . Supernatant from 2 . 4 × 106 macrophages was separated by 15% SDS-PAGE , transferred to nitrocellulose membranes , and cytokine processing and release was analyzed by western blot using anti-IL-18 M19 and peroxidase-conjugated secondary antibodies ( Santa Cruz Biotechnology ) . Immunoblots were developed with an enhanced chemiluminescence system ( Amersham Biosciences ) . Female C57BL/6 mice aged 6–8 wk ( Jackson Laboratories ) were infected orogastrically with 6−8 × 108 wild-type or pIB1− Yptb in 100μl of PBS . Mice were sacrificed on days 4 , 5 , and 6 postinfection , and spleen and MLNs were removed and placed in cold PBS . Organs were homogenized between frosted glass slides . An aliquot was removed and lysed in 1% triton for CFU determination by plating dilutions on cefulosodin-irgasan-novobiocin ( CIN ) agar . The remaining cells were processed for staining: red blood cells were lysed in 17 μM Tris ( pH 7 . 4 ) , 140 μM NH4Cl for 5 min at room temperature , washed once in cold PBS , and passed through a 70 μM filter to create a single cell suspension . Cell numbers were determined by Trypan blue exclusion . To identify activated macrophages , 2 × 106 cells were stained with anti-F4/80-PE antibodies ( Caltag ) , anti-ICAM1-biotin antibodies , and streptavidin-APC ( BD Pharmingen ) on ice for 30 min . Cells were fixed and analyzed by flow cytometry using a BD LSR 6 color analyzer . Isotype control antibodies resulted in an MFI equivalent to that of unstained cells . To identify macrophages with active caspase-1 , 2 × 106 cells were incubated for 30 min at 37 °C with 5% CO2 with 1× FAM-YVAD in PBS supplemented with 5 mM glycine to reduce cell breakdown [41] . Cells were then washed thoroughly to remove unbound FAM-YVAD and labeled with anti-F4/80-PE antibodies , fixed , and analyzed by flow cytometry . Increased FAM-YVAD staining was not due to cross reactivity with caspases activated during Yptb-induced apoptosis; naïve macrophages infected with wild-type Yptb did not have increased FAM-YVAD staining . Animal experiments were approved by the University of Washington Institutional Animal Care and Use Committee , Seattle , WA .
The GenBank ( http://www . ncbi . nlm . nih . gov/Genbank/ ) GI numbers for the genes and gene products discussed in this paper are: Yptb YopJ ( 56405330 ) ; Yptb YopB ( 549791 ) ; caspase-1 ( 86198305 ) ; TLR4 ( 10946594 ) ; IL-18 ( 6680413 ) ; caspase-3 ( 118129865 ) ; ICAD ( 141802948 ) ; ICAM-1 ( 30172560 ) .
|
Pathogenic Yersinia are bacteria capable of interacting with host immune cells and inhibiting their function . Macrophages are potent antimicrobial immune cells that eliminate invading microbes , and represent a major target for Yersinia during infection . Yersinia triggers death of resting macrophages by apoptosis , a process thought to be advantageous for Yersinia growth during early stages of infection because important host cells are eliminated without perturbing the surrounding tissue . However , activated macrophages with enhanced antimicrobial activity play a crucial role in controlling Yersinia infection . To elucidate the mechanisms involved in successful defense against infection , the authors investigated the response of activated macrophages to Yersinia , which revealed induction of a proinflammatory cell death pathway termed pyroptosis . Unlike apoptosis , pyroptosis unleashes inflammatory mediators capable of enhancing immune responses and clearing bacteria . Macrophage activation and pyroptosis was observed in infected host tissue . Thus , regulating the mechanism of cell death is important for effective responses to Yersinia infection: activated macrophages resisting apoptosis are redirected to utilize pyroptosis , an inflammatory process facilitating host resistance .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Supporting",
"Information"
] |
[
"infectious",
"diseases",
"in",
"vitro",
"immunology",
"mus",
"(mouse)",
"animals",
"eubacteria"
] |
2007
|
Macrophage Activation Redirects Yersinia-Infected Host Cell Death from Apoptosis to Caspase-1-Dependent Pyroptosis
|
To develop an oral formulation of amphotericin B ( AmB ) that is stable at the temperatures of WHO Climatic Zones 3 and 4 ( 30–43°C ) and to evaluate its efficacy in a murine model of visceral leishmaniasis ( VL ) . The stability testing of four novel oral lipid AmB formulations composed of mono- and di-glycerides and pegylated esters ( iCo-010 to iCo-013 ) was performed over 60 d and analyzed by HPLC-UV . In addition , the four formulations were incubated 4 h in fasted-state simulated intestinal fluid . AmB concentration was measured spectrophotometrically and emulsion droplet diameter was assessed by dynamic light scattering . Antileishmanial activity of iCo-010 was evaluated at increasing oral doses ( 2 . 5 to 10 mg/kg ) in a murine model of VL . AmB stability in the lipid formulation ( iCo-010 ) was >75% over 60 days . After 4 h in fasted-state simulated intestinal fluid , AmB concentration was >95% . iCo-010 demonstrated significant efficacy when orally administered to VL-infected mice bid for five days ( inhibition of 99% , 98% , and 83% at 10 , 5 and 2 . 5 mg/kg compared to the vehicle control ) . In addition , the qd dose of 20 mg/kg provided 96% inhibition compared to the vehicle control . The oral AmB formulation iCo-010 is stable at the temperatures of WHO Climatic Zones 3 and 4 ( 30–43°C ) . iCo-010 showed excellent antileishmanial activity at both 10 mg/kg po bid for 5 days ( <99% reduction in parasitic infection ) and 20 mg/kg po qd for 5 days ( 95% inhibition when compared to control ) .
Visceral leishmaniasis ( VL ) is a systemic form of a vector-borne parasitic disease caused by obligate intra-macrophage protozoa of the genus Leishmania . VL is transmitted via the bite of an infected sand fly [1] , [2] . The parasites are then disseminated through the vascular and lymphatic systems , infecting monocytes and macrophages of the reticulo-endothelial system and accumulating in the liver and spleen [1] . VL is always fatal in humans if left untreated [3] . Unfortunately , the treatment options for VL are limited . Amphotericin B ( AmB ) , a polyene antibiotic , is the most active antileishmanial agent that currently exists . Liposomal AmB ( AmBisome ) is used as first-line treatment in developed countries [1] , [7] , [8] , [9] , [10]; however , the requisite parenteral administration and the high cost of the liposomal formulation prevents this treatment from reaching the majority of patients in developing nations [3] . A stable , efficacious oral treatment for VL that is able to withstand the rigors of tropical climates would overcome many of the current barriers to treatment that exist in countries with large VL-infected patient populations . An oral lipid-based formulation of AmB ( iCo-009 ) was recently developed and evaluated in animal models of systemic fungal infections and VL [4] , [5] , [6] . iCo-009 demonstrated significant antifungal and antiparasitic activity as well as an excellent drug stability profile at 4°C [4] , [5] , [6] . The goal of the current study was to develop potential oral formulations of AmB that are a ) stable at the temperatures of WHO Climatic Zones 3 and 4 ( 30–43°C ) ; b ) retain AmB stability in simulated gastric and intestinal fluids and c ) exhibit significant antileishmanial activity in a VL-infected murine model . We have now developed a number of lipid-based self-emulsifying formulations which exhibit AmB chemical stability in FaSSIF and temperature stability at 43°C . The temperature stability of AmB at 30 and 43°C in a series of lipid formulations ( iCo-010-013 ) are described , which indicate that formulations based on mono- and di-glycerides and Vitamin E-TPGS provide excellent temperature stability for AmB . Furthermore , these formulations show good stability in simulated intestinal fluids , which mimic the degradative stress of oral administration . A nanoemulsion ( with droplet diameters <1 µm ) forms in these fluids upon mixing at 37°C , facilitating absorption of these AmB-lipid compositions . In addition , we provide data that demonstrate the significant antileishmanial activity of one of these tropically stable , novel lipid-based oral AmB formulations ( iCo-010 ) .
Studies in Leishmania donovani-infected BALB/c mice were carried out according to a protocol approved by The Ohio State University Institutional Animal Care and Use Committee ( National Institutes of Health Office of Laboratory Animal Welfare Assurance Number A3261-01 ) . The study was conducted adhering to the Ohio State University's guidelines for animal husbandry and appropriate steps were taken to avoid or minimize pain and suffering . Amphotericin B ( AmB; 80% purity ) was purchased from Sigma Chemical Co . ( St . Louis , MO ) and used as received . Ethanol ( 100% ) was purchased from Commercial Alcohols ( Vancouver , BC ) . Mono- and di-glycerides were a gift from Gattefossé Canada ( Toronto , ON , Canada ) . D-alpha-tocopheryl polyethylene glycol succinate ( Vitamin E-TPGS; NF grade ) was bought from Eastman Chemical Co . ( Kingsport , TN ) . Methanol , HPLC water , acetonitrile and acetic acid were purchased from Fisher Scientific ( Ottawa , ON Canada ) and were of HPLC grade . Sodium chloride , hydrochloric acid , sodium hydroxide , dibasic potassium phosphate , sodium taurocholate and porcine pancreatin were bought from Sigma Chemical Co . Egg phosphatidylcholine ( lecithin ) was purchased from Avanti Polar Lipids ( Alabaster , AL ) . Chromatography conditions: The HPLC column was a BDS Hypersil C18 , 5 µm , 250×4 . 6 mm ( Thermo Scientific , Waltham , MA ) , with a C18 guard column from Phenomenex ( Torrance , CA ) . During sample runs , the column incubator was set to 40°C . The mobile phase consisted of acetonitrile: acetic acid: water in a ratio of 57∶4 . 3∶38 . 7 ( v/v/v ) . The injection volume was 90 µL and the flow rate was 0 . 8 mL/min with a run time of 20 min . The retention time of AmB under these conditions was 15 min . Six triplicate standards of AmB in methanol: water ( 50∶50 v/v ) were used for external calibration , with a linear range of 31 . 25–1000 ng/mL by linear regression analysis ( r2>0 . 999 ) . For analysis of AmB in lipid formulations , the samples were warmed in a 48°C waterbath to melt the lipids , followed by vigorous vortexing for 2 min . A double dilution was then used . With a micropipettor , 100 µL were transferred to a glass vial followed by the addition of 9 . 9 mL methanol and vortexing for 1 min . From this dilution , 100 µL was aliquoted to another glass vial , followed by addition of 9 . 9 mL of methanol:water ( 50∶50 v/v ) and vortexed for 1 min , thereby making 1∶10 , 000 dilutions of the original samples . These final dilutions were analyzed by HPLC as described above and compared to the standard curve for quantification of AmB concentration . The stability testing of AmB in each of the four oral lipid formulations ( AmB in mono- and di-glycerides with or without Vitamin E-TPGS; iCo 010-013 ) was performed at 30°C and 43°C at ambient humidity ( >85% ) . The base compositions of the formulations are composed of mono- and diglycerides with a mixture of glycerol and PEG1500 esters of long fatty acids with or without Vitamin E-TPGS . iCo 010 contains 60/40 ( v/v ) mono- and diglycerides with Vitamin E-TPGS; iCo 011 contains 50/50 ( v/v ) mono- and diglycerides with Vitamin E-TPGS; iCo 012 contains 50/50 ( v/v ) mono- and diglycerides without Vitamin E-TPGS; and iCo 013 contains 60/40 ( v/v ) mono- and diglycerides without Vitamin E-TPGS . For stability analysis at 30°C and 43°C , multiple time points covering a 60 day period were chosen as part of the accelerated temperature studies set out by the WHO to mimic tropical climate Zone 3 and 4 conditions . Four independent replicate samples were prepared for each time point by melting the batch of AmB in lipids at 48°C and stirring to homogeneity , followed by quickly aliquoting 0 . 5 mL of the AmpB/lipid mixture into individual polypropylene microcentrifuge tubes . The tubes were then sealed with parafilm . Samples were protected from light with foil and stored in incubators at 30° or 48°C . The starting concentration of AmB in the lipids was measured by HPLC ( 3–4 mg/mL depending on batch concentration ) . All subsequent measurements of AmB during the course of the stability study were performed by HPLC as described above and are reported as “% of original concentration” as measured on the day the sample was aliquoted ( day 0 ) . The rate of loss of AmB per day was calculated as: ( [AmB]day 0−[AmB]day 60 ) /60 days . = µg/mL⋅day loss . These data are reported as mean ±SD for 4 independent replicates . Statistical differences were assessed pair-wise by Student's t test ( paired , 2-tailed ) ( SigmaStat v . 3 . 5 ) with significance set at p<0 . 05 . Preparation of Fasted-State Simulated Intestinal Fluid without enzymes was also prepared according to the USP V . 28 and was composed of 3 . 9 g/L dibasic potassium phosphate , 1 . 613 g/L sodium taurocholate ( = 3 mM ) , lecithin ( egg phosphatidylcholine ) 0 . 57 g/L ( = 0 . 75 mM ) , potassium chloride 7 . 7 g/L dissolved in water and with sufficient hydrochloric acid to adjust the pH to 6 . 5 . AmB formulations in mono- and di-glycerides with or without Vitamin E-TPGS and the corresponding drug-free vehicle controls were melted at 48°C in a water bath followed by vigorous vortexing for 2 min . FaSSIF was warmed to 37°C in 3 foil-wrapped 500 mL beakers on stirring hotplates . For incubation in FaSSIF , samples ( 0 . 5 mL ) were added to 249 . 5 mL FaSSIF to achieve a dilution of 1∶500 v/v . The samples were mixed vigorously at 37°C over over 4 h for FaSSIF incubation , producing an emulsified mixture . At 0 , 10 , 30 , 45 , 60 , 90 , 120 and 240 min in FaSSIF , triplicate 1 mL samples were withdrawn from the beakers while the mixing continued . The 1 mL samples were diluted with 9 mL methanol and vortexed to clarity . Quantification of AmB concentration was performed by ultraviolet spectroscopy ( λ = 407 ) on a Carey Bio-300 UV-visible spectrophotometer ( Varian Canada , Mississauga , Ontario ) by comparison to an external standard curve consisting of UV measurements of AmB in methanol containing the same dilution of the corresponding vehicle control for each formulation type . The linear range by regression analysis was 0 . 5–1 . 75 µg/mL ( r2>0 . 999 ) . The translucent emulsion formed during incubation of AmB in oral lipids in simulated gastric or intestinal fluid tends to cream ( oil to the top of the aqueous phase ) if not continuously mixed . Therefore , 1 mL samples were obtained mid-beaker depth at 2 h and 4 h for FaSSIF incubations during vigorous mixing and transferred to a plastic cuvette . Samples were mixed again by vortexing prior to placement in the sizing instrument . The emulsion droplet size was measured by dynamic light scattering ( Malvern Zetasizer , Malvern Instruments , Worchestershire , UK ) operating with an argon laser ( λ = 633 nm ) and with the sample holder kept at 37°C for 3 runs of 1 minute each , during which time the measurements were stable . Intensity weighting was used . Data are reported as the mean droplet diameter ± standard deviation ( SD ) from mean of 3 separate samples , where three runs were averaged for each sample . To determine the antileishmanial activity of our oral AmB formulation , the following studies were completed . BALB/c mice were intravenously infected with 5×107 Leishmania donovani LV82 promastigotes ( obtained by culturing amastigotes taken directly from the spleen of an infected hamster ) seven days prior to treatment . Following the seven days , mice were either administered five daily doses of miltefosine at 3 mg/kg po , or iCo-010 at 2 . 5 , 5 , and 10 mg/kg po bid for five consecutive days or 20 mg/kg po qd for five consecutive days . Appropriate vehicle controls were also assessed . Animals were sacrificed 14 days post infection and Leishman-Donovan units ( LDU ) were assessed in livers of mice post mortem via microscopic enumeration of Giemsa-stained liver smears .
The results in Fig . 1 show that the stability of AmB in the lipid formulations is >75% for all formulations over 60 days at 30°C and Fig . 2 shows a similar pattern at 43°C with a slightly lower concentration in all formulations by 60 days . After 60 days at 30°C , AmB concentrations were comparable with and without Vitamin E-TPGS ( ∼85% of the original concentration ) , but when different proportions of mono- and di-glycerides were employed , samples without Vitamin E-TPGS ( iCo-013 ) contained only 75% of the original AmB concentration compared to 91% when Vitamin E-TPGS was included ( iCo-011 ) . The addition of Vitamin E-TPGS did not significantly change the decomposition rate for AmB in iCo-010 at 43°C , although there was a trend to greater retention of AmB when Vitamin E-TPGS was included . The rate of decomposition ( µg/mL . day ) of AmB in all the lipid formulations at both temperatures is slow , as indicated in Table 1 . There was a significant decrease ( p<0 . 01 ) in the rate at which the AmB was lost in iCo-011 compared to iCo-013 . This resulted in AmB concentrations after 60 days at 43°C that were 83 . 4% of the original concentration when Vitamin E-TPGS was included but only 69 . 7% when it was not present . It should be noted that no phase separation of the lipids or changes in particle size were observed after 60 days of incubation at 43°C for iCo 010 . In simulated fasted-state intestinal fluid ( FaSSIF ) , after 4 h of mixing at 37°C , iCo-010 retains >95% of its original drug concentration ( Fig . 3 ) . Assessment of the stability of AmB in iCo-011 , iCo-012 and iCo-013 in FaSSIF shows very similar stability of formulations containing VitE-TPGS to those without it . Assessment of emulsification in FaSSIF of AmB formulations composed of Peceol/Gelucire 44/14 shows that the presence of VitE-TPGS in the Peceol/Gelucire 44/14 mixture , such as in iCo-010 and iCo-011 , reduces the mean diameter and creates a more monodisperse nanoemulsion . Emulsion droplet sizing of AmB in iCo-013 ( no VitE-TPGS ) following 2 and 4 h mixing in FaSSIF at 37°C revealed the largest droplet size of approximately 700–850 nm , whereas AmpB in iCo-010 ( with VitE-TPGS ) had a relatively smaller mean diameter closer to 200 nm . ( Fig 4 ) . Considering the similar stability data for the four formulations tested ( both at elevated temperature and in simulated gastrointestinal fluids ) and more desirable self-emulsification properties of iCo-010 , this formulation was chosen for in vivo studies of AmpB efficacy in an animal model of VL , as described below . When given in five daily doses at 3 mg/kg po , miltefosine resulted in 47 . 5±7 . 0% inhibition of liver parasites , consistent with literature reports [6] . LDU values were not significantly different between groups of animals receiving oral doses of a lipid-based vehicle control bid for five days versus those receiving a single IV saline injection . ( Fig . 5 ) . Dose response data from treatment of L . donovani- infected BALB/c mice with 2 . 5 , 5 and 10 mg/kg iCo-010 bid for five days is reported in Fig . 5 . iCo-010 demonstrated significant efficacy when orally administered to VL-infected mice bid for five days ( inhibition of 99% , 98% , and 83% at 10 , 5 and 2 . 5 mg/kg compared to the vehicle control ) . In addition , the qd dose of 20 mg/kg provided 96% inhibition compared to the vehicle control . Based on data from our antifungal studies indicating no renal toxicity ( data not shown ) and the level of antileishmanial activity ( Fig . 5 ) , we are now confident that a self-administered tropically stable oral formulation of AmB is attainable .
The lipid formulations of AmB based on mono- and diglycerides ± Vitamin E-TPGS were developed as an alternative to the less temperature-stable monoglyceride formulation . Lipids with a melting point above ambient temperature and with good suspending properties , surfactant and self-emulsifying properties were chosen as alternatives . The ratio of mono- and di-glycerides and pegylated esters was selected based on preliminary studies of AmB temperature stability , component miscibility and maintenance of a stable suspension without phase separation . Furthermore , preliminary studies indicated that Vitamin E-TPGS in combination with mono- and di-glycerides and pegylated esters was tolerable in terms of maintaining a physically stable suspension of AmB at 5 mg/mL . The temperature stability of AmB in all the lipid formulations was excellent , exceeding approximately 80% after 60 days at 30°C ( Fig . 1 ) and 75% at 43°C ( Fig . 2 ) , and exhibiting no clear differences in the pattern of concentration loss vs . time amongst the four preparations . Upon examining the rate of drug loss as a function of excipient composition ( Table 1 ) , iCo-011 was slightly more stable than iCo-10 or iCo-013 at 30°C . As expected , addition of Vitamin E-TPGS significantly decreased the rate of drug loss at 43°C . At 43°C , the ratio of mono- and di-glycerides and pegylated esters appears less important than the presence of Vitamin E-TPGS , as formulations containing it showing a slower rate of AmB loss . However , the complex and likely temperature-dependent mechanism of interaction between AmB and the various lipids at the molecular level has not yet been explored . Nevertheless , these are very small differences and the biological properties of these formulations ( bioavailability , tissue drug distribution and efficacy ) would clearly be more important parameters to govern selection of a lead candidate from this set of formulations . Regarding the properties of these lipid formulations in conditions mimicking those of the gastrointestinal tract , studies of the stability of the lipid formulations in FaSSIF demonstrate that AmB concentration is well-maintained when incorporated into all of the formulations , as shown in Fig . 3 . The self-emulsifying properties of these lipid formulations are deemed important because the formation of a nanoemulsion in the gastrointestinal tract may facilitate intestinal absorption , particularly through the lymphatic transport pathway . Furthermore , a major precipitation of the drug in gastrointestinal fluids would be undesirable and lead to unpredictable absorption patterns . The emulsification of the drug-lipid mixture also promotes interaction with bile salts , which can further enhance solubilization and absorption of the drug in the intestine . iCo-010 in FaSSIF , which contains sodium taurocholate as the bile salt , produced a slightly larger nanoemulsion of greater polydispersity . The emulsification behavior of the lipid formulations of AmB containing Vitamin E-TPGS in FaSSIF are an ongoing study which should allow for the further discernment of the role of Vitamin E-TPGS in the physical properties of these suspensions . Considering the similar stability data for the 4 formulations tested ( both at elevated temperature and in simulated gastrointestinal fluids ) and more desirable self-emulsification properties of iCo-010 , this formulation was chosen for in vivo studies of AmpB efficacy in an animal model of VL . The demonstrated efficacy of this formulation is likely due to a combination of increased solubility , improved gastrointestinal stability and enhanced membrane permeability . In addition , oral administration of a lipid-based formulation favors lymphatic transport . As VL parasites disseminate through the lymphatic and vascular system , infecting macrophages and infiltrating the bone marrow , liver and spleen , the lipid carrier may assist in delivering the drug to the site of greatest infection . Taking into consideration the short treatment course in this study , it is conceivable that longer treatment would completely eradicate VL in all treated animals . To the best of our knowledge , these data represent the first tropically stable oral AmB formulations to exhibit significant efficacy against Leishmania donovani ( the parasite responsible for VL ) in an infected mouse model .
|
Visceral leishmaniasis ( VL ) is a systemic form of a vector-borne parasitic disease caused by obligate intra-macrophage protozoa of the genus Leishmania . VL is always fatal in humans if left untreated and treatment options are limited . Amphotericin B ( AmB ) , a polyene antibiotic , is the most active antileishmanial agent that currently exists . Liposomal AmB ( AmBisome ) is used as first-line treatment in developed countries [1] , [7] , [8] , [9] , [10]; however , the requisite parenteral administration and the high cost of the liposomal formulation prevents this treatment from reaching the majority of patients in developing nations [3] . A stable , efficacious oral treatment for VL that is able to withstand the rigors of tropical climates would overcome many of the current barriers to treatment that exist in countries with large VL-infected patient populations . In this study we have developed an oral formulation of AmB that is stable in tropical conditions and exhibits significant antileshimanial activity in mice .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"pharmacology/drug",
"development"
] |
2010
|
A Novel Tropically Stable Oral Amphotericin B Formulation (iCo-010) Exhibits Efficacy against Visceral Leishmaniasis in a Murine Model
|
The suprachiasmatic nucleus ( SCN ) acts as the central clock to coordinate circadian oscillations in mammalian behavior , physiology and gene expression . Despite our knowledge of the circadian transcriptome of the SCN , how it impacts genome-wide protein expression is not well understood . Here , we interrogated the murine SCN proteome across the circadian cycle using SILAC-based quantitative mass spectrometry . Of the 2112 proteins that were accurately quantified , 20% ( 421 proteins ) displayed a time-of-day-dependent expression profile . Within this time-of-day proteome , 11% ( 48 proteins ) were further defined as circadian based on a sinusoidal expression pattern with a ∼24 h period . Nine circadianly expressed proteins exhibited 24 h rhythms at the transcript level , with an average time lag that exceeded 8 h . A substantial proportion of the time-of-day proteome exhibited abrupt fluctuations at the anticipated light-to-dark and dark-to-light transitions , and was enriched for proteins involved in several key biological pathways , most notably , mitochondrial oxidative phosphorylation . Additionally , predicted targets of miR-133ab were enriched in specific hierarchical clusters and were inversely correlated with miR133ab expression in the SCN . These insights into the proteomic landscape of the SCN will facilitate a more integrative understanding of cellular control within the SCN clock .
Proper temporal organization of behavioral , physiological and biochemical processes and their synchronization with the environmental light/dark cycle are fundamental features of most organisms [1] . In mammals , the central pacemaker that coordinates this adaptive response to temporal cues resides in the suprachiasmatic nucleus ( SCN ) of the anterior hypothalamus [2] , [3] . The SCN is uniquely positioned to receive light signals from the retina and to relay the time information to peripheral clocks via synaptic and humoral mechanisms . Both central and peripheral clocks use a series of autoregulatory transcription-translation feedback loops to drive cell-autonomous , circadian ( ∼24 h ) rhythms of gene expression of core clock components as well as tissue-specific , clock-controlled outputs [1] . In order to gain a bird's eye view of circadian regulation , a number of gene expression profiling studies using microarrays have been done to examine the circadian transcriptome of the murine SCN and liver [4] , [5] . However , numerous studies have shown that transcript levels are not necessarily reliable predictors of protein abundance , and thus of functional outcome [6] . A previous attempt at elucidating the circadian proteome , using two-dimensional differential gel electrophoresis ( 2D-DIGE ) combined with mass spectrometry ( MS ) , identified 34 rhythmically expressed proteins within the SCN [7] . Until now , the small size of the SCN , and the limited amounts of protein that can be extracted from it , has posed a significant challenge to acquiring accurate and comprehensive quantitative proteomics data . However , recent technological advances in MS-based quantitation , and our growing awareness of the importance of post-transcriptional regulation of circadian rhythms [8] , encouraged us to re-evaluate SCN functions from a proteomic perspective . In our previous study , we employed the AutoProteome system in conjunction with spectral counting to identify 2131 unique proteins in the SCN , of which 387 were acutely up- or down-regulated following nocturnal light exposure [9] . In this report , we performed an unbiased interrogation of the SCN proteome over a 24 h cycle using an alternative MS approach: a centrifugal proteomic reactor ( CPR ) coupled with stable isotope labeling by amino acids in cell culture ( SILAC ) -based quantitation . Neuro2A murine neuroblastoma cells were used as the SILAC-labeled internal reference standard for murine SCN tissues , based on reports that numerous core clock genes are expressed in this cell line , and that serum shock can induce robust circadian oscillations of their transcripts [10] , [11] . Furthermore , a previous study indicated >97% overlap between the proteomes of mouse whole brain and Neuro2A cells [12] . Our proteomics screen identified a total of 3275 unique proteins in the murine SCN , 421 of which displayed time-of-day-dependent expression profiles . Within this smaller subset , 48 proteins fluctuated in a circadian manner . Bioinformatics analyses of these 421 proteins highlight the potentially important role that post-transcriptional mechanisms such as miRNAs may play in shaping the final profile of the time-of-day proteome , and the orchestrated expression of multiple proteins involved in neurosecretory processes and mitochondrial oxidative phosphorylation within the SCN .
To examine the murine SCN proteome , we stably entrained male C57Bl/6J mice to a 12 h light∶12 h dark ( LD ) cycle , and transferred them to constant darkness ( DD ) for two days . Starting at circadian time ( CT ) 2 on the third day of DD , we collected SCN tissues from four mice at 4 h intervals for a full circadian cycle ( Figure 1A ) . SCN samples were processed individually to yield four independent biological replicates for each time point ( 4 mice per CT , n = 24 total mice ) . SCN protein lysates ( 30 µg ) were mixed with equal quantities of lysates prepared from Neuro2A cells that had previously been cultured for >10 passages in heavy SILAC medium . Under these conditions , the Neuro2A proteome is estimated to be >98% heavy SILAC-labeled and thus useful as a spike-in reference standard . The CPR , with its superior recovery of hydrophobic membrane proteins compared with other approaches [13] , was used for rapid protein preconcentration , derivatization , enzymatic digestion , and fractionation of the samples . Peptides were eluted from the CPR in ten fractions and analyzed by high performance liquid chromatography-electrospray tandem mass spectrometry ( HPLC-ESI-MS/MS ) in a total of 240 runs . From the raw mass spectrometric data , Maxquant and Andromeda identified 3275 protein groups with a false discovery rate ( FDR ) of 1% ( Table S1 ) . Out of these 3275 proteins , only 7 lacked a corresponding SILAC-labeled peak , indicating that these proteins are expressed in the SCN but not in Neuro2A cells ( Table S1 ) . As expected from recent proteomic studies [14] , [15] , our MS screen failed to detect any core clock proteins , likely due to their low abundance relative to the many cytoplasmic proteins which were detected . The raw dataset was further filtered for proteins that were identified by a minimum of two peptide ratio counts and where accurate quantification values were obtained in a minimum of 12 out of 24 independent samples . Downstream bioinformatics and statistical analyses were performed on this stringently filtered dataset of 2112 proteins ( 64 . 5% of total identified proteins ) , hereafter referred to as the SCN proteome ( Table S2 ) . High r values ( between 0 . 83 and 0 . 97 , Table S3 ) were obtained for the pairwise Pearson's correlation analysis of 24 measurements , indicating excellent reproducibility within our SCN proteome data . To identify proteins whose expression significantly fluctuated as a function of time-of-day , we subjected the SCN proteome to an analysis of variance . ANOVA revealed that 421 proteins ( i . e . , 20% of the SCN proteome ) exhibited statistically significant ( p<0 . 05 ) alterations in abundance across the 24 h cycle . This significantly altered proteome , hereafter referred to as the time-of-day proteome , was evaluated for reproducibility using pairwise Pearson's correlation analysis of the 24 samples ( Table S4 ) . The r values between biological replicates at a specific CT were extremely high ( Figures 1B and 1C ) compared with the lower r values observed between samples of different CTs ( Figure 1D ) , indicating a high degree of reproducibility within biological replicates . As a second independent measure of variability , we calculated the relative standard deviation ( RSD ) for all proteins at every CT . The median RSD for the time-of-day proteome was 16% , compared with 11% from a previous study of the circadian hepatic proteome [14] . Considering that their study [14] utilized single pooled tissue samples per CT per 24 h cycle ( 2 cycles were analyzed ) , while ours uses unpooled samples from 4 animals per CT , an RSD of 16% reflects an acceptable level of variability within our dataset . Lastly , the temporal profiles of 12 proteins ( Figure 2 ) with quantification values in all 24 samples also showed a higher degree of correlation within a CT than between CTs . The expression of five of these proteins—endophilin A1 ( SH3GL2 ) , synaptobrevin 2 ( VAMP2 ) , serine/threonine-protein kinase PAK 1 ( PAK1 ) , synaptotagmin 1 ( SYT1 ) , and synaptic vesicle glycoprotein 2A ( SV2A ) —was evaluated by Western blot ( WB ) analysis using independent batches of SCN tissues ( Figure 2 ) . In all cases , the WB results correlated well with our MS-based quantification ( Pearson's coefficients = 0 . 78 [SH3GL2] , 0 . 69 [VAMP2] , 0 . 75 [PAK1] , 0 . 77 [SYT1] , 0 . 66 [SV2A] ) . Next , the time-of-day proteome was subjected to Gene Ontology ( GO ) analysis by DAVID [16] in order to investigate its biological relevance . Relative to both the SCN proteome and the entire mouse genome ( by DAVID ) , the time-of-day proteome was significantly enriched for GO total cellular components that were classified as mitochondrion or mitochondrial membrane ( Fisher's exact test , p<0 . 05 ) ( Figure 1E ) . Additionally , several metabolic pathways including generation of precursor metabolites and energy , oxidation reduction , energy derivation by oxidation of organic compounds , and cellular respiration were significantly enriched in this dataset based on GO total biological process analysis ( Figure 1F ) . A more in-depth examination using GO FAT analysis , which filters out very broad GO terms based on a measured specificity of each term , confirmed that a significant portion of the time-of-day proteome was associated with the mitochondrion , energy generation and consumption , and hydrogen ion transmembrane transporter activity ( Figure S1 ) . Hierarchical clustering of the time-of-day proteome revealed segregation of proteins into six different expression clusters ( Figure 3A , Table S5 ) . Two dominant clusters emerged from the analysis: cluster D ( 118 proteins ) and cluster E ( 189 proteins ) . Closer examination of the protein levels within each cluster ( Figure 3B ) revealed that clusters D and E are mirror images of one another . A second interesting feature of clusters D and E is their bimodal expression profile . For instance , cluster E is characterized by an increase in expression from CT 2 to CT 10 , a sharp decrease from CT 10 to CT 14 ( the anticipated light-to-dark transition ) , a gradual increase through the night ( CT 14 to CT 22 ) , followed by an abrupt decrease from CT 22 to CT 2 ( the anticipated dark-to-light transition ) . Interestingly , when compared to the time-of-day proteome , cluster E was selectively enriched for several GO biological processes such as generation of precursor metabolites and energy , cellular respiration , and energy derivation by oxidation of organic compounds ( Figure 3C ) . Collectively , the data reveal that a substantial portion of the SCN proteome ( 20% ) exhibits significant changes in abundance as a function of time-of-day . Next , we sought to identify proteins that exhibited a strictly circadian pattern of expression , as well as those that were ultradian . To this end , we employed the JTK_CYCLE algorithm [17] , [18] to identify the subsets of proteins within the time-of-day proteome that oscillated with periods of 8 , 12 and 24 h . JTK_CYCLE was recently developed to detect rhythmic components within large genomic datasets , and is superior to other similar algorithms in its sensitivity , specificity and efficiency [17] . Recent studies have also used JTK_CYCLE to analyze the circadian acetylome and the diurnal transcriptome of the murine liver and heart , respectively [19] , [20] . Given that the observed free-running period of C57BL6 mice is ∼23 . 6 to 23 . 8 h , we used the nearest integer value ( 24 ) to approximate a circadian cycle using JTK_CYCLE . Based on a p-value cutoff of 0 . 05 [18] , 48 proteins were deemed to be circadian , with phase of peak expression distributed across the entire 24 h cycle ( Figure S2C , Table S6 ) . Surprisingly , a relatively large proportion of the time-of-day proteome exhibited ultradian periods of 8 h ( 25 proteins ) and 12 h ( 59 proteins ) ( p<0 . 05 , JTK_CYCLE , Figures S2A and S2B , Table S7 ) . Those 12 h rhythmic proteins tended to peak in expression at either the early day and early night , or late day and late night ( Figure S2B ) , mirroring the profiles of clusters D and E ( Figure 3B ) , respectively . Moreover , subjecting the larger dataset of the SCN proteome to JTK_CYCLE analysis resulted in the assignment of an additional 11 , 41 and 43 proteins as rhythmic with periods of 8 , 12 and 24 h , respectively . The fact that these proteins were identified as rhythmic by JTK_CYCLE but were not significantly altered based on ANOVA suggests that they might exhibit weak fluctuations that are mistaken as rhythmic . Thus , we focused subsequent downstream analyses on those circadian and ultradian proteins that were identified within the time-of-day proteome rather than the SCN proteome . Our results are somewhat reminiscent of the findings of Hughes et al . [18] , which identified clusters of transcripts that cycled at the second and third harmonics of circadian rhythmicity in the murine liver; however , in that study the transcripts exhibiting these subharmonics accounted for only a small fraction of the entire rhythmic transcriptome . To investigate the relationship between transcript levels and protein abundance , we compared our time-of-day , circadian and ultradian ( 8 h and 12 h ) proteomes with mRNA data extracted from two published microarray studies ( MAS4 Panda et al . and gcrma Panda et al . ) of the mouse SCN transcriptome from the CIRCA database ( http://bioinf . itmat . upenn . edu/circa/ ) using identical JTK_CYCLE filtering criteria ( p<0 . 05 , 0 to 40 h period rhythmicity ) ( Figures 4A–D ) . Notably , >40% of each proteome was encoded by non-rhythmic transcripts . Circadian transcripts were found to encode a smaller subset of proteins within the time-of-day , circadian and 12-h ultradian proteomes . Each proteome also consisted of a subset of proteins that were encoded by rhythmic ( non-24 h ) transcripts cycling at intervals of 16 , 20 , 28 or 32 h . Notably , none of the 8 h and 12 h rhythmic proteins were encoded by transcripts that oscillated with the same period . Moreover , there were only 9 genes that exhibited circadian rhythms at both the transcript and protein level , and even amongst most of these there was a significant time lag ( mean ∼8 h ) between the peak in expression of the mRNA and the protein ( Figure 4E ) . Collectively , our data indicate that transcript levels are a generally poor predictor of protein abundance in the murine SCN . By extension , this suggests that post-transcriptional mechanisms play a dominant role in shaping the ultimate landscape of the SCN proteome . Another key observation from our study is that , for a substantial portion of the time-of-day proteome , the anticipated light-to-dark and dark-to-light transitions trigger robust changes in protein abundance that are similar in direction ( either up- or down-regulated ) . microRNAs ( miRNAs ) are small ( ∼22–24 nt ) , noncoding RNAs that act as potent post-transcriptional modulators of gene expression . Various miRNAs have been implicated in the regulation of circadian rhythms in multiple model systems [21] , [22] . To examine a possible involvement of miRNAs in shaping the SCN proteome , we first asked whether predicted targets of known miRNAs were enriched within particular hierarchical clusters of our time-of-day proteome . To this end , we compared the time-of-day proteome with the predicted targets of 86 broadly conserved miRNA families extracted from the TargetScanMouse version 6 . 2 database ( http://www . targetscan . org/mmu_61/ ) . Out of 86 broadly conserved miRNA families examined , only miR-133ab showed a significant enrichment of its respective targets in at least one hierarchical cluster . Figure 5A illustrates the number of predicted miR-133ab target genes within each hierarchical cluster based on the presence of at least one conserved site within the annotated 3' untranslated region ( UTR ) of the transcript . Compared to other hierarchical clusters , cluster E had the largest number of , and was statistically enriched for , predicted miR-133ab targets ( Fisher's exact test , p<0 . 05; Figure 5A ) . As miR-133ab levels have been reported to be low in the brain [23] , we used an ultra-sensitive qRT-PCR approach to quantify levels of mature miR-133a and -133b in the murine SCN ( Figure 5B ) . miR-133b abundance was elevated throughout the subjective night , whereas miR-133a levels peaked sharply at CT 14 ( Figure 5B ) . Notably , the expression profile of miR-133ab showed an inverse trend when compared with the MS-quantified expression of their predicted target genes in cluster E from CT 10 to CT 22 ( Figure 5C ) . To provide functional evidence that these are authentic targets of miR-133ab , we selected three predicted targets within cluster E and examined their expression in Neuro2A cells in which levels of miR-133a or miR-133b have been enhanced using microRNA mimics , or suppressed by microRNA inhibitors . Either one or both mimics of miR-133a and miR-133b strongly suppressed the levels of SH3GL2 , SYT1 and SV2A proteins in transfected Neuro2A cells compared with controls ( Figures 5D–F ) . On the other hand , silencing of miR-133a or miR-133b robustly elevated the expression of SH3GL2 but not SYT1 or SV2A ( Figures 5D–F ) . These data are consistent with SH3GL2 , SYT1 and SV2A being authentic targets of miR-133ab . Collectively , our results raise the possibility that miRNAs , such as miR-133ab , are orchestrating the temporal profiles of multiple target genes as suggested previously [24] . Given the fact that predicted miR-133ab targets are not solely restricted to a single hierarchical cluster with a common temporal expression pattern , other miRNAs are likely to work in concert with miR-133ab to fine-tune the temporal expression profile of its targets . More generally , our data suggest that miRNAs may be key post-transcriptional regulators of time-of-day-dependent protein expression within the SCN . The concerted expression of a large number of proteins within each hierarchical cluster suggests that many of these proteins might interact directly with one another to modulate a shared set of biological responses . To test this hypothesis , we used the IPA software to perform a very restrictive interaction analysis using only interactions from public repositories and limiting the network to direct interactions between proteins within a single cluster ( i . e . , no neighbors ) . Proteins in cluster E exhibited a high degree of connectivity ( 35 out of 189 proteins , or 18 . 5% ) through direct protein-protein interactions ( Figure 6 ) . The top functions within this network were neurological disease and psychological disorders . Notably , this network included a relatively large number of proteins that are involved in neurotransmitter release ( i . e . , NSF , SV2A , SYT1 and VAMP2 ) and synaptic transmission ( i . e . , CNP , NSF , SV2A , SH3GL2 and SYT1 ) ( Figure 6 ) . A more comprehensive functional protein interaction network analysis of the entire time-of-day proteome ( 421 proteins ) revealed that one of the largest networks is driven from the interactions among proteins involved in protein trafficking and carbohydrate metabolism ( Figure S3 ) . This network cluster included 9 proteins that oscillated with 12-h rhythms . The larger protein interaction network also included proteins involved in more general cellular functions , such as cellular assembly and organization , cellular function and maintenance , and cell morphology ( Figure S3 ) . We further mapped the time-of-day proteome onto 192 known canonical pathways using IPA to identify pathways that might be significantly impacted ( Figure S4 ) . Three canonical pathways that had previously been implicated in the regulation of the SCN clock [25]–[27] were identified in our IPA analysis: Ca2+/cAMP response element binding protein ( CREB ) signaling in neurons ( p = 0 . 0031 ) ; extracellular signal-regulated kinase ( ERK ) /mitogen- activated protein kinase ( MAPK ) signaling pathway ( p = 0 . 0019 ) ; and synaptic long-term potentiation pathway ( p = 0 . 0035 ) . In agreement with our previous GO analysis , the top-ranked canonical pathway was the mitochondrial dysfunction pathway , with 29 out of 421 proteins mapped . To delve further into the potential implications of an apparent temporal regulation of the mitochondria , we performed a KEGG pathway enrichment analysis by DAVID to compare our time-of-day proteome against all 2112 quantified proteins in the SCN proteome . Our data reveal that the KEGG pathways for Huntington's disease , Parkinson's disease , oxidative phosphorylation , pyruvate metabolism , and arginine and proline metabolism were significantly enriched with at least 8 proteins mapped in each pathway ( Figure 7A ) . Indeed , many of the proteins within the Huntington's disease , Parkinson's disease , and oxidative phosphorylation ( OxPhos ) pathways overlapped and were mitochondrial in their localization . Particularly noteworthy was the OxPhos pathway , which accounted for 25 proteins within the time-of-day proteome . Of these 25 OxPhos-related proteins , 22 were present in cluster E and thus exhibited a similar trend in expression profile . Results from KEGG analysis mirrored those from canonical pathway analysis by IPA , which identified 19 OxPhos-related proteins ( a subset of the 25 ) , with 16 of these belonging in cluster E ( Figure 7B ) . One of these OxPhos proteins , NDUFA10 , a subunit of NADH∶ubiquinone oxidoreductase ( complex I ) , was selected for validation by IF . NDUFA10 immunoreactivity within the SCN exhibited a pronounced increase at the CT10-CT14 transition , in keeping with the MS results at these two time points ( Figure 7C ) . The time-of-day proteome is significantly enriched for mitochondrial proteins ( 111/421 , or 26 . 4% ) relative to the SCN proteome ( 2112 proteins ) . Further analysis revealed that 51 . 4% of these mitochondrial proteins belonged within Cluster E , although this “cluster bias” did not reach statistical significance ( Figure 7D ) . However , when we restricted our analysis to mitochondrial proteins that were involved in the OxPhos pathway , we found significant enrichment within cluster E . Our collective data point to a hitherto unappreciated temporal regulation of mitochondrial functions , particularly oxidative phosphorylation , within the central pacemaker .
Despite recent advances in quantitative proteomics and their application to the study of clock-controlled processes in the liver [14] , [15] , [19] , the SCN proteome has been challenging to characterize in a comprehensive manner due to its inherently low sample availability . A previous attempt , using 2-dimensional difference gel electrophoresis ( 2D-DIGE ) coupled with MS for protein identification , uncovered 115 proteins with time-of-day-dependent expression , of which 34 were circadian , out of 871 protein spots detected [7] . In our present study , we took advantage of the quantitative accuracy of SILAC , and combined it with the enhanced detection sensitivity that is achieved using the CPR , to provide a large-scale interrogation of the SCN proteome ( Figure 1A ) . The outcome was the identification of 421 and 48 proteins whose expression profiles were time-of-day-dependent and circadian , respectively , from a stringently quantified dataset of 2112 proteins . In contrast with recently published liver circadian proteome studies [14] , [15] , we used 4 independent biological replicates to represent each CT across one 24 h cycle , rather than a single ( pooled ) sample for each time point across two cycles . Despite these procedural differences , the percentage of the detected proteome that exhibited circadian ( 24 h ) rhythms was reasonably similar in all three studies ( 2 . 2% , our study; 6 . 0% Robles et al . [14]; 4 . 8% Mauvoisin et al . [15] ) . Furthermore , based on our proteomic analysis of the SCN , we were able to conclude that transcript expression is a relatively poor predictor of protein abundance , that ultradian rhythms in protein expression are prevalent in the SCN , and that the mitochondria , in particular oxidative phosphorylation , is a major target of temporal control in the central pacemaker . Additionally , our findings support the argument that post-transcriptional mechanisms , including miRNAs , may play a prominent role in shaping the ultimate landscape of the SCN proteome . Comparisons with the Deery et al . report revealed that our SCN proteome ( 2112 proteins ) included 30 of their 115 time-of-day-dependent proteins . Eleven out of these 30 were found within our time-of-day proteome and two belonged in our circadian proteome ( p<0 . 05 , JTK analysis ) . The higher frequency in sampling intervals in our study compared to theirs ( 4 h vs . 6 h ) along with different statistical algorithms employed may partially account for the differences between the two datasets . Nevertheless , both studies identified vesicular trafficking and neurosecretory processes as novel points of temporal regulation . Interestingly , a number of proteins involved in neurotransmitter release ( i . e . , NSF , SV2A , SYT1 and VAMP2 ) and synaptic transmission ( i . e . , CNP , NSF , SV2A , SH3GL2 and SYT1 ) shared similar expression trends ( cluster E ) , exemplifying how the SCN might coordinate the expression of proteins that act within the same biological pathway . One unexpected observation was the sharp , and parallel , changes in protein expression at the anticipated transitions from light-to-dark and dark-to-light . This pattern was prevalent not only in the 12 h ultradian proteome ( Figure S2B ) but also in the time-of-day proteome ( clusters D and E , Figure 3B ) . Hughes et al . [18] made similar observations in analyzing the 12 h cycling transcripts of the liver . They speculated that these dawn- and dusk-peaking transcripts took part in cellular mechanisms that anticipated the stress of daily transitions into light and darkness . Such an explanation might also be pertinent to our study . In particular , changes in levels of oxidative phosphorylation might constitute one such cellular response to light-dark/dark-light ( or rest-wake/wake-rest ) state transitions ( Figure 7B ) . The mechanisms that drive these bimodal expression profiles within the SCN are unknown , but could conceivably involve interactions between the molecular clock and systemic cues . Alternatively , as shown by Westermark and colleagues [28] , 12 h rhythms may arise theoretically through the actions of pairs of circadianly expressed transcription factors with defined phase relationships relative to each other . Our study adds to the growing body of evidence that post-transcriptional regulation is a key feature of central and peripheral clocks . Less than 60% of the circadian and ultradian proteomes were encoded by transcripts that were rhythmic . In the case of the 8 h and 12 h proteomes , none of those rhythmic transcripts exhibited the same period as the encoded protein . Furthermore , for the 9 genes that were circadian at both the mRNA and protein level , there was a great disparity between the phase of peak expression of the transcript vs . that of the protein ( mean time difference of ∼8 h ) . From these collective data , one can infer that post-transcriptional ( and post-translational ) regulation has a major influence on protein expression in the SCN . Specific post-transcriptional events , such as miRNA regulation , may intersect with circadian transcriptional rhythms ( or even constitutive gene transcription ) to establish the final time-course and profile of protein expression . Along these lines , we provide evidence that a microRNA , miR-133ab , has the ability to regulate the expression of various target proteins belonging to cluster E . Furthermore , we noted an inverse trend between miR-133ab levels and expression of their in silico targets in the SCN . Another interesting finding is the prevalence of ultradian proteins in the SCN . Hughes et al . [18] also discovered circadian harmonics within his rhythmic transcriptome , but they occurred with a much lower frequency relative to the circadian transcripts . The mechanisms that are driving a larger subset of proteins towards ultradian expression are unclear , but could conceivably involve one or several post-transcriptional mechanisms . Finally , our results strongly support the notion that mitochondrial energetics within the SCN is under strict temporal control ( Figure 7A ) . While recent studies emphasize the circadian control of mitochondrial metabolism in the liver [19] , [29] , a key organ for energy storage and mobilization , almost none have directly studied mitochondrial function in the SCN . However , recent observations that the NAD+-dependent deacetylase SiRT1 positively modulates the expression of CLOCK and BMAL1 in the SCN [10] , and that resveratrol activates SiRT1 through an increase in mitochondrial complex I-dependent NADH oxidation [30] , raise the possibility that mitochondrial metabolism , in particular oxidative phosphorylation , may play a prominent role in maintaining robustness of the SCN clock . Interestingly , others have noted that hepatic NAD+ levels exhibit a bimodal rhythm and attributed this entirely to its biosynthesis by the enzyme nicotinamide phosphoribosyltransferase [31] . Our proteomics data , which highlight the bimodal expression of a large number of OxPhos-related proteins , provide an additional mechanism by which NAD+ levels may be shaped in the SCN . In conclusion , our study provides a broader perspective on the temporal control of the SCN proteome . Our results underscore the significance of post-transcriptional regulation , the surprising prevalence of ultradian protein expression , and the functional implications on mitochondrial energy metabolism . Future investigations should help to clarify how each of these aspects contributes to the central pacemaker function of the SCN .
All animal handling and experimental procedures were conducted at the University of Toronto Mississauga animal facility , and were approved by the local animal care committee in compliance with institutional guidelines and the Canadian Council on Animal Care . Ammonium bicarbonate ( NH4HCO3 ) , dithiothreitol ( DTT ) , iodoacetamide ( IAA ) , citric acid , and urea were obtained from Sigma-Aldrich ( Saint Louis , MO ) . Acetonitrile , with 0 . 1% formic acid , and water , with 0 . 1% formic acid , were purchased from J . T . Baker ( Phillipsburg , NJ ) . Trypsin was purchased from Promega ( Madison , WI ) . Strong cation exchange ( SCX ) beads were obtained from Polymer Laboratories , Varian , Inc . ( Palo Alto , CA ) . CHAPS ( 3-[ ( 3-cholamidopropyl ) dimethylammonio]-1- propanesulfonate , BP 571 ) , ammonium hydroxide ( NH4OH ) , and methanol were purchased from Fisher Scientific ( Hampton , NH ) . Eight- to 12-week-old male C57BL6/J mice that were obtained from in-house breeding or purchase from The Jackson Laboratory ( Bar Harbor , ME ) were used for all experiments . Mice were group-housed in polycarbonate cages and given ad libitum access to rodent chow and water throughout the study . Mice were stably entrained for a minimum of 2 weeks to a 12 h light∶12 h dark ( LD ) schedule ( light intensity during the L phase was ∼200 lux ) prior to transfer to complete darkness ( DD ) for 2 full cycles . Dark adaptation was achieved by placing cages into light-tight ventilated cabinets . On day 3 of DD , mice were killed at 4-h intervals at circadian times ( CT ) 2 , 6 , 10 , 14 , 18 , and 22 , where CT corresponds to the Zeitgeber time ( ZT ) of the previous LD cycle . Mice were killed by cervical dislocation and decapitated , and eyes were covered with black electrical tape under dim red light . Brains were dissected and cut into 800-µm thick coronal sections containing the SCN in cooled oxygenated media using an oscillating tissue slicer [24] . SCN was isolated from the tissue slice using a razor blade , and frozen immediately on dry ice . For IF , the entire coronal slice was fixed in 4% ( w/v ) paraformaldehyde in phosphate-buffered saline ( PBS; 6 h , room temperature ) , cryoprotected in 30% ( w/v ) sucrose ( overnight , 4°C ) , and cut into thin sections ( 30-µm ) using a freezing microtome . Neuro2A cells ( American Type Culture Collection [ATCC] , Manassas , VA ) were grown in customized DMEM ( AthenaES , Baltimore , MD , USA ) and supplemented with [13C6 , 15N4]-L-Arginine ( Arg-10 ) , [13C6 , 15N2]-L-Lysine ( Lys-8 ) at Arg 42 mg/L , Lys 146 mg/L , Met 30 mg/L and supplemented with 10% ( v/v ) dialyzed FBS ( GIBCO-Invitrogen; Burlington , ON , Canada ) , 1 mM sodium pyruvate ( Gibco-Invitrogen ) and 28 µg/mL gentamicin ( Gibco-Invitrogen ) . Labeled amino acids are purchased from Sigma-Aldrich ( Oakville , ON , Canada ) . Cells were maintained in culture for at least 10 doubling times to allow for complete ( >98% ) incorporation of the isotope-labeled amino acids into the cells . SCN tissues of individual mice were homogenized in 80 µL lysis buffer ( 8M urea , 4% CHAPS , 100 mM NH4HCO3 with fresh proteinase inhibitor mixture ) in a 1 . 5 mL Pellet pestle , and sonicated 3 times for 10 s each with >30 s on ice between each pulse . Protein concentration was determined by the Bradford method . Proteins were processed in a centrifugal proteomic reactor device as previously described with some modifications [13] . Briefly , lysates from SCN tissues and heavy SILAC-labeled Neuro2A cells were mixed 1∶1 ( 30 µg protein each ) , and vortexed ( 1 min ) vigorously in the presence of 30 µL of SCX slurry and 1 . 2 mL of 5% formic acid . Samples were centrifuged ( 16 , 100×g , 3 min ) , and SCX bead pellets were washed twice with 1 . 2 mL 0 . 1% formic acid . Proteins were reduced by incubating samples in the presence of 20 µL of 150 mM NH4HCO3 , 20 mM DTT ( 1200 rpm , 56°C , 15 min ) , and were subsequently alkylated by the addition of 20 µL of 150 mM NH4HCO3 , 100 mM IAA ( room temperature , 15 min in darkness ) . The reaction was stopped by adding 1 . 2 mL of 0 . 1% formic acid supplemented with 6 µg trypsin . Following centrifugation , the SCX bead pellet was resuspended in 40 µL of 1 M NH4HCO3 and trypsin digested for 4 h ( 37°C , 1200 rpm ) . Finally , pH step elution of the peptides from the SCX beads was performed by adding: 1 . 2 ml of 0 . 1% formic acid pH 2 . 5 , followed by additional nine pH fractions ( pH 3 . 0 , 3 . 5 , 4 . 0 , 4 . 5 , 5 . 0 , 5 . 5 6 . 0 , 8 . 0 , 12 ) by subsequent additions of 400 µL 10 mM citric acid/NH4OH pH buffers . The fractionated samples were desalted using in-house-made C18 desalting cartridges , and dessicated using a Speed-Vac prior to LC-MS measurement . All resulting peptide fractions were analyzed by HPLC-ESI-MS/MS , which consists of an automated Agilent 1100 micro-HPLC system ( Agilent Technologies , Santa Clara , CA ) coupled with an LTQ-Orbitrap mass spectrometer ( ThermoFisher Scientific , San Jose , CA ) equipped with a nano-electrospray interface operated in positive ion mode . Each peptide mixture was reconstituted in 20 µL of 0 . 5% ( v/v ) formic acid , and 10 µl was loaded on a 200 µm×50 mm fritted fused silica pre-column packed in-house with reverse phase Magic C18AQ resins ( 5 µm; 200-Å pore size; Dr . Maisch GmbH , Ammerbuch , Germany ) . The separation of peptides was performed on an analytical column ( 75 µm×10 cm ) packed with reverse phase beads ( 3 µm; 120-Å pore size; Dr . Maisch GmbH , Ammerbuch , Germany ) . Gradient elution was performed over 75 min from 5–30% acetonitrile ( v/v ) containing 0 . 1% formic acid ( v/v ) at an eluent flow rate of 200 nL/min after in-line flow splitting . The spray voltage was set to +1 . 8 kV and the temperature of the heated capillary was 200°C . The instrument method consisted of one full MS scan from 400 to 2000 m/z followed by data-dependent MS/MS scan of the 10 most intense ions , a dynamic exclusion repeat count of 2 , and a repeat exclusion duration of 90 s . The full mass was scanned in the Orbitrap analyzer with R = 60 , 000 ( defined at m/z = 400 ) , and the subsequent MS/MS analysis was performed in the LTQ analyzer . To improve the mass accuracy , all measurements in the Orbitrap mass analyzer were performed with on-the-fly internal recalibration ( “Lock Mass” ) . The charge state rejection function was enabled , and single charge and unassigned charge ions were rejected . All data were recorded with the Xcalibur software ( ThermoFisher Scientific , San Jose , CA ) . Raw files were processed and analyzed by MaxQuant , Version 1 . 3 . 0 . 5 against the mouse International Protein Index protein sequence database ( IPI Mouse , version 3 . 75 ) , including commonly observed contaminants . The following parameters were used: cysteine carbamidomethylation was selected as a fixed modification; and the methionine oxidation and protein N-terminal acetylation were set variable modifications . Enzyme specificity was set to trypsin . Up to two missing cleavages of trypsin were allowed . SILAC double labeling ( light: K0R0; heavy: K8R10 ) was set as the search parameter in order to assess the conversion efficiency . The precursor ion mass tolerances were 6 ppm , and fragment ion mass tolerance was 0 . 8 Da for MS/MS spectra . The false discovery rate ( FDR ) for peptide and protein was set at 1% and a minimum length of six amino acids was used for peptide identification . The proteingroup file was imported into Perseus ( version 1 . 3 . 0 . 4 ) for statistical analysis of the data . The raw dataset ( 3275 proteins ) was filtered to include only proteins with a minimum peptide ratio count of 2 and with quantification values in a minimum of 12 of 24 MS measurements ( or 24 independent SCN samples ) , resulting in a stringently quantified dataset of 2112 proteins . One-way ANOVA was used to analyze this stringent dataset for temporal regulation , with p-values<0 . 05 indicating statistical significance . For the hierarchical clustering analysis , median value of logarithmized values for the normalized L/H ratio of each protein profile was performed after z-score normalization of the data within Euclidean distances . To identify the subset of 24-h rhythmic proteins , JTK_CYCLE algorithm [17] was used on the SCN proteomic ( 2112 proteins ) or the time-of-day proteomic ( 421 proteins ) dataset under R language . The JTK_CYCLE algorithm allows the user to input integer values when defining the ( non-statistical ) parameters of a search . The values for the ratio L/H normalized of each protein profile from 24 mice were used . Any missing values ( i . e . , not detected by MS ) were replaced with zero prior to JTK_CYCLE analysis , as per expert recommendation ( Dr . Michael Hughes , personal communication ) . Using a similar strategy as reported previously [32] to deal with missing values ( ie . , by replacing them with the minimum values observed for any given peptide ) yielded the same results as replacing the missing values with zero , affirming the validity of our approach . p-values ( ADJ . P ) less than 0 . 05 were considered significant , and the corresponding proteins were classified as displaying a circadian rhythm [14] . To find the 8-h or 12-h rhythmic proteins within the 421 protein dataset , another JTK_CYCLE analysis was separately performed with period lengths set at 8 and 12-h , respectively . Canonical pathways analyses and protein network of the time-of-day proteomic ( 421 proteins ) dataset were mapped and summarized by Ingenuity Pathways Analysis ( IPA ) , version 8 . 5 ( Ingenuity Systems , Redwood City , CA ) . Canonical pathways analyses were performed with p value of 0 . 05 and networks were displayed with minimum significant score of 16 . Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathway analysis was achieved using the DAVID Bioinformatics Resources ( http://david . abcc . ncifcrf . gov ) . DAVID statistical analyses are performed against the whole genome [12] . Proteomics has a tendency to oversample proteins from the cytosol while undersampling nuclear and membrane-associated proteins . To calculate exactly significant enrichment of time-of-day proteome in each GO term , we first calculated the amounts of matched proteins enriched either in the time-of-day proteome ( 421 proteins ) or the total SCN proteome ( 2112 proteins ) . Fisher's exact test was used to check that the GO results were significantly enriched in the time-of-day proteome relative to the total SCN proteome . This was done to avoid any pathway/GO enrichment biases that would result from comparing our time-of-day proteome against the whole mouse database . The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium ( http://www . proteomexchange . org ) via the PRIDE partner repository [33] with the dataset identifier PXD000778 . Total RNA was extracted from individual SCN tissues using the Trizol Reagent according to manufacturer's instructions . RNA concentration and purity were determined using the NanoPhotometer P-Class ( Implen GmbH , Germany ) , and RNA integrity was confirmed by agarose gel electrophoresis . cDNA synthesis was performed using the Universal cDNA Synthesis Kit II ( Exiqon ) and 20 ng of total RNA ( for miR-133b ) or 100 ng of total RNA ( for miR-133a ) . cDNA was diluted 1∶40 and real-time PCR was performed using the ExiLENT SYBR Green Master Mix ( Exiqon ) and hsa-miR-133a and hsa-miR-133b LNA™ PCR primer sets ( Exiqon ) , on the Stratagene Mx3000P qPCR System . Values were normalized to 18S ribosomal RNA abundance . Neuro2A cells were grown on 6-well plates in DMEM containing 5% FBS and 1% penicillin-streptomycin at 37°C and 5% CO2 until they reached 75–80% confluence . Cells were then transfected in duplicate using Lipofectamine 2000 ( Invitrogen ) according to manufacturer's instructions . Cells were transfected with one of the following: miRCURY LNA Power Inhibitor ( Exiqon ) targeted towards either miR-133a or miR-133b; miRCURY LNA microRNA Mimic for either miR-133a or miR-133b; or miRCURY LNA microRNA inhibitor negative control . Protein lysates were harvested 24 h post-transfection for Western blot analysis . SCN containing tissues were homogenized on ice in RIPA buffer containing protease inhibitors . Homogenized tissues were incubated on ice for 20 min and centrifuged at 4°C at 17 , 000× g for 20 min . The supernatant was collected and stored at −80°C for downstream analysis . Protein concentration was measured using the Bradford assay . Protein lysates were mixed with SDS loading buffer to 1× concentration , heated at 95°C for 5 min , and centrifuged for 1 min at 17 , 000× g . Lysates ( 20 µg/well ) were electrophoresed in a SDS polyacrylamide gel for approximately 2 h at 100 V at room temperature ( RT ) and electroblotted onto polyvinylidene fluoride ( Immobilon P; Millipore , Bedford , MA ) membrane for either 1 h at RT at 85 V , or overnight ( O/N ) at 4°C at 30 V . Protein transfer was confirmed using Ponceau S , followed by 3 washes for 5 min each in Tris Buffered Saline with 0 . 1% Triton X-100 ( TBS-T ) . Membranes were blocked in 5% skim milk in TBS-T for 1 h at RT , followed by O/N incubation at 4°C with one of the following primary antibodies in blocking solution: rabbit anti-SYT1 ( 1∶500; cat #3347; Cell Signaling Technologies ) ; rabbit anti-SV2A ( 1∶500; cat #ab32942; Abcam ) ; rabbit anti-VAMP2 ( 1∶2000; cat#13508; Cell Signaling Technologies ) ; rabbit anti-SH3GL2 ( 1∶2000; cat#ab169762; Abcam ) ; rabbit anti-PAK1 ( 1∶500; cat#40852; Abcam ) ; and rabbit anti-actin ( 1∶10 , 000; Sigma-Aldrich ) . The next day , membranes were washed in TBS-T and incubated for 2 h at RT with goat anti-rabbit horseradish peroxidase ( HRP ) conjugated secondary antibody ( 1∶250 , 000; ThermoFisher Scientific ) in blocking solution . Chemiluminescent signal was developed using the SuperSignal West Femto Maximum Sensitivity Substrate reagent ( ThermoFisher Scientific ) . Quantitation of western blots performed using the “measure” function in ImageJ ( http://rsbweb . nih . gov/ij/ ) yielded a “mean gray” value for each protein band , which were normalized to background “mean gray” values . Values are presented as median relative abundance of the protein examined normalized to relative abundance of actin from 3 mice per time point . Tissue sections were washed 5 times for 5 min each in Phosphate Buffered Saline with 0 . 1% Triton X-100 ( PBS-T ) . Sections were blocked in 10% horse serum in PBS-T for 1 h at RT and incubated O/N with one of the following primary antibodies in blocking solution: rabbit anti-NDUFA10 ( 1∶1000; cat #ab103026; Abcam ) . The next day tissues were washed 5×5 min in PBS-T , and incubated for 2 h at RT in the dark with Alexa Fluor 488 donkey anti-rabbit secondary antibodies ( 1∶1000; Invitrogen ) in blocking solution . Sections were washed 5×5 min in PBS-T , incubated with DAPI for 5 minutes , and washed with PBS . Sections were mounted on microscope slides , cover-slipped with fluorescence DAKO mounting medium and sealed with nail-polish . Slides were stored at 4°C . IF images were captured using a Zeiss Axio Observer Z1 inverted microscope equipped with a Laser Scanning Microscope ( LSM ) 700 module along with the ZEN 2010 software ( Zeiss , Oberkochen , Germany ) . Individual fluorochrome signals were collected sequentially using the multitrack setting along with appropriate barrier filters using the “smart set-up” option . IF images were acquired from a central focal plane of 2 . 3 µm optical thickness using the 10× , 20× or 40× objectives , or 1 . 0 um optical thickness using the 63× objective . Identical settings for gain , pinhole size , and brightness were used to acquire all images of the same magnification within each experiment . Adjustments to brightness and contrast were applied equally to all images within an experiment using Adobe Photoshop CS . For quantitative analysis , the bilateral SCN from the micrographs were outlined using the polygon tool in ImageJ . The “measure” function yielded a “mean gray” value for each of the two bilateral SCN , which were normalized to background “mean gray” values obtained from surrounding non-immunoreactive hypothalamalic regions . Values are presented as median relative abundance of the protein examined from 3 mice per time point .
|
The suprachiasmatic nucleus ( SCN ) serves as the master circadian pacemaker in mammals , coordinating the physiological responses of a myriad of peripheral clocks throughout the body and linking their rhythms to the environmental light-dark cycle . In this study , we interrogated the murine SCN proteome across the circadian cycle using stable isotope labeling by amino acids in cell culture ( SILAC ) -based quantitative mass spectrometry . Among 3275 identified proteins in the SCN , 421 displayed a time-of-day-dependent expression profile , 48 fit a circadian expression profile with a ∼24 h period , and a surprising number of proteins were ultradianly expressed . Nine circadianly expressed proteins were accompanied by transcripts that were also 24 h rhythmic , but with a significant time lag ( >8 h ) between the phases of peak mRNA vs . protein expression . A substantial proportion of the time-of-day proteome exhibited abrupt fluctuations at the anticipated dawn and dusk , and was involved in mitochondrial oxidative phosphorylation . Additionally , predicted targets of miR-133ab were enriched in specific hierarchical clusters and were inversely correlated with miR133ab expression in the SCN . Our study underscores the significance of post-transcriptional regulation , the surprising prevalence of ultradian protein expression , and the functional implications on mitochondrial energy metabolism .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"circadian",
"rhythms",
"chronobiology",
"biology",
"and",
"life",
"sciences",
"proteomics",
"circadian",
"oscillators",
"daylight"
] |
2014
|
The Proteomic Landscape of the Suprachiasmatic Nucleus Clock Reveals Large-Scale Coordination of Key Biological Processes
|
Rabies is a zoonotic infectious disease of the central nervous system ( CNS ) . In unvaccinated or untreated subjects , rabies virus infection causes severe neurological symptoms and is invariably fatal . Despite the long-standing existence of effective vaccines , vaccine availability remains insufficient , with high numbers of fatal infections mostly in developing countries . Nucleic acid based vaccines have proven convincingly as a new technology for the fast development of vaccines against newly emerging pathogens , diseases where no vaccine exists or for replacing already existing vaccines . We used an optimized non-replicating rabies virus glycoprotein ( RABV-G ) encoding messenger RNA ( mRNA ) to induce potent neutralizing antibodies ( VN titers ) in mice and domestic pigs . Functional antibody titers were followed in mice for up to one year and titers remained stable for the entire observation period in all dose groups . T cell analysis revealed the induction of both , specific CD4+ as well as CD8+ T cells by RABV-G mRNA , with the induced CD4+ T cells being higher than those induced by a licensed vaccine . Notably , RABV-G mRNA vaccinated mice were protected against lethal intracerebral challenge infection . Inhibition of viral replication by vaccination was verified by qRT-PCR . Furthermore , we demonstrate that CD4+ T cells are crucial for the generation of neutralizing antibodies . In domestic pigs we were able to induce VN titers that correlate with protection in adult and newborn pigs . This study demonstrates the feasibility of a non-replicating mRNA rabies vaccine in small and large animals and highlights the promises of mRNA vaccines for the prevention of infectious diseases .
Rabies is an invariably fatal neurological disease that affects different species of warm-blooded animals , including wild animals , pets , and humans . This infectious disease is caused by a strictly neurotropic virus . The rabies virus has a bullet-shaped , enveloped virion with a negative-sense single-stranded RNA genome that encodes five viral proteins: nucleoprotein , phosphoprotein , matrix protein , glycoprotein , and RNA-dependent RNA polymerase . Human rabies cases are almost exclusively caused by animal bites , in particular by dogs . After the incubation phase , humans first develop a flu-like illness and thereafter severe neurotropic symptoms caused by the ensuing progressive encephalomyelitis . While incubation phases vary , death commonly follows within an average survival time between 6 and 11 days after first symptomatic onset for furious or paralytic forms , respectively , thus leaving little time and extremely limited therapeutic options [1 , 2] . The virus also replicates in salivary glands of infected dogs and is thus commonly transmitted through bite wounds , licking of damaged skin , or direct mucosal contact . Enhanced aggressiveness of rabid animals results in an effective transmission strategy . The virus attaches to its cellular targets by the surface glycoprotein ( RABV-G ) , rapidly gains access to peripheral nerves , and then , after retrograde axonal transport and trans-synaptic spread , ultimately reaches the brain . Transport of the enveloped virus within nerve cells and neuronal transport vesicles impedes clearance by humoral or cellular immunity [3–6] . As a consequence , effective immunological defense against rabies must intercept virus before productive neuronal infection . This may require immediate neutralization by antibodies directed against the viral G protein upon entry of rabies virus into uninfected tissue and/or early elimination of infected cells by virus-specific cytotoxic T cells , when limited replication may take place in non-nervous tissue at the site of entry . This is most effective when the neutralizing antibodies and clearing T cells are already present in situ at the time of infection , which is the case after prophylactic vaccination . In contrast thereto , protection has first to be built up in case of initiation of vaccination after exposure to the rabies virus , which requires time , as it is done by PEP vaccination . That is the reason for the administration of rabies immunoglobulin ( RIG ) together with active PEP vaccination in the case of suspected rabies exposure in rabies naïve individuals . Rabies vaccines were introduced historically by Louis Pasteur and have been used for more than a century , mostly to control canine rabies that poses the highest risk for transmission to humans [7] . While vaccinating animals has greatly reduced human cases , transmission via stray dogs or other species , such as bats and raccoons , remains problematic in many countries [8 , 9] . Despite the availability of effective vaccines , rabies infection continues to claim at least 55 , 000 human lives per year ( WHO Weekly epidemiological record , No . 49/50 , 2007 ) , not counting the great excess of fatal infections in animals . In India , more human fatalities are caused by rabies than in any other country of the world with an estimated 16 , 000 deaths in the year 2010 alone [10] . Thus , the global provision of safe , effective , and affordable vaccines for use in humans remains important . A special challenge is the adequate supply of vaccine doses to impoverished persons in resource-poor settings . This medical need warrants continued development of alternative vaccine technologies to further reduce the prohibitive cost of currently available egg-based or cell-culture derived vaccines [11] , to prevent shortage of vaccine supply [12] , and to facilitate distribution . Early rabies vaccines were produced in mammalian neural tissue and have been replaced by vaccines manufactured in tissue culture and embryonated eggs over time . Novel vaccine formats such as subunit , DNA or viral vector vaccines have been assessed successfully for their protective capacity against rabies infection in preclinical settings [3 , 13] but none of these resulted in a licensed product for human use yet . In this study , we assessed the immunogenicity and protective capacity of rabies-specific mRNA vaccines . Messenger RNA ( mRNA ) vaccines are a genetic vaccine format that may address short-comings of current vaccine technologies . Benefits are the induction of balanced and enduring immunity as demonstrated for anti-tumor and prophylactic vaccination [14–16] , simple supply , and storage at elevated temperature , as reviewed elsewhere [17 , 18] . In addition , it is common view that production for mRNA vaccines is cost-effective [19–21] . The mRNA used here as a vaccine formulation ( RNActive ) includes optimization of coding and non-coding elements of the mRNA molecule , its purification after in vitro transcription and its formulation with protamine for enhanced adjuvanticity [15 , 17 , 22–24] . In mice , intradermally injected mRNA encoding RABV-G induced humoral and cellular immunity with a clear dose-response relationship . The format conferred full protection in a stringent murine challenge model of intracerebral inoculation with rabies virus . We show that protection is dependent on the presence of CD4+ T cells during immunization . Moreover , we demonstrate the early , efficient viral clearance and brain homeostasis by mRNA vaccination upon intracerebral infection . Finally , immunogenicity was shown in domestic pigs representing a relevant animal model with a skin highly similar in its architecture to the human skin [25 , 26] . Here virus neutralizing antibody responses were induced that are well above the WHO threshold of 0 . 5 IU/ml in adult as well as in newborn pigs . In the course of the clinical testing of this new substance class , the expert advisory panel of the WHO assigned the suffix “-MERAN” as international nonproprietary name ( INN ) to mRNA drug substances , and nadorameran to the drug substance of the mRNA rabies vaccine [27] .
Rabies virus CVS-11 was grown on BHK-21 cells and used throughout the experiments . All mRNA vaccines were based on the RNActive platform ( EP1857122 and WO2012019780A1 ) . mRNA vectors contained a 5’ cap structure , 5’ UTR , open reading frame ( ORF ) , 3’ UTR , polyA tail and did not include chemically modified nucleotides . In brief , optimization entailed GC-enrichment of the open reading frame ( EP 1392341 and EP 1800697 ) , inclusion of enhanced UTRs , and complexation with protamine ( Valeant Pharmaceuticals , Eschborn , Germany ) as described elsewhere [14 , 15] . The mRNA rabies vaccine encodes the glycoprotein ( RABV-G ) of the Pasteur strain ( GenBank accession number: AAA47218 . 1 ) . Two different optimized mRNA constructs were used for immunization ( RABV-G A and B ) containing identical ORFs but different UTRs . Except for the analysis of the longevity of the T cell response , mice were immunized with RABV-G mRNA A . Pigs where immunized with RABV-G mRNA B . In all immunization experiments , mRNA was complexed with protamine . Both mRNA sequences were product candidates and therefore both used for preclinical tests . The full sequence for both mRNA constructs is given in S1 Fig . The mRNA was produced by T7-polymerase-based in vitro run-off transcription [28 , 29] . The RABV-G mRNA vaccine encoded the full-length , structurally unaltered rabies virus glycoprotein . The licensed vaccines Rabipur ( Novartis ) and HDC ( human diploid cell vaccine ) are commercially available and were purchased from a local pharmacy . Either Rabipur or HDC were used as positive controls dependent on the availability . Mice ( BALB/c and C57BL/6 , 6–8 weeks of age ) were obtained from Janvier Laboratories ( Le Genest-Saint-Isle , France ) , Charles River Laboratory ( Sulzfeld , Germany ) or the animal breeding facilities at the Friedrich-Loeffler-Institute , Tübingen , Germany . Female pregnant pigs ( Sus scrofa domesticus ) and adult Hungarian large whites were purchased from local breeders . Studies with adult pigs were conducted at Aurigon-Toxicoop Research Center Ltd . , Dunakeszi , Hungary . All animal experiments were conducted according to German and Hungarian laws and guidelines for animal protection . Experiments in Germany were approved by the regional council Tübingen ( reference numbers FLI238/08 , FLI242/09 , FLI246/09 , CUR 4–13 ) . For protein expression analysis , HeLa cells were transfected with RABV-G mRNA or mRNA encoding hemagglutinin ( negative control; HA from A/Netherlands/602/2009 ) . 24 h after transfection , cells were stained with a monoclonal mouse anti-rabies antibody ( #3R7; HyTest Ltd , Turku , Finland ) and a FITC-labelled goat anti-mouse IgG ( Life technologies GmbH , Darmstadt , Germany ) . Expression was detected by analysis of FITC positive cells by flow cytometry . Before immunization , mice were anesthetized by i . p . application of ketamine ( Sanofi-Aventis , Frankfurt , Germany ) and rompun ( Bayer , Leverkusen , Germany ) . Intradermal injection of 100 μl ( distributed to two adjacent sites ) was performed into the skin in the middle of the back using syringe and forceps . Mice were treated with doses ranging from 1 . 25–80 μg mRNA . Pigs were immunized intradermally on the upper back with a volume of 100 μl ( 80μg ) or 2x150 μl ( 240μg ) using the “Mantoux” technique . Rabipur and HDC were injected i . m . For mice the i . m . applied injection volume of 100 μl was distributed to four injection sites in the hind limps . Pigs were treated with the full dose of Rabipur ( 1 ml ) . For negative control groups , Ringer-Lactate solution or mRNA encoding Ovalbumin was injected . Blood samples were taken by retro-orbital bleeding ( mice ) or vena cava superior ( pigs ) . Anti-rabies serum antibodies were analyzed by FAVN test by Eurovir Hygiene-Institut , Luckenwalde , Germany according to WHO protocol [30] . The induction of antigen-specific T cells was determined using intracellular cytokine staining ( ICS ) or ELISPOT assay . For ICS splenocytes from vaccinated and control mice were isolated and stimulated with the RABV-G peptide library ( JPT Peptide Technologies GmbH , Berlin , Germany ) and anti-CD28 antibody ( BD Biosciences , Heidelberg , Germany ) for 6 hours at 37°C in the presence of the mixture of GolgiPlug/GolgiStop ( Protein transport inhibitors containing Brefeldin A and Monensin , respectively; BD Biosciences , Heidelberg , Germany ) . After stimulation cells were washed and stained for intracellular cytokines using the Cytofix/Cytoperm reagent ( BD Biosciences , Heidelberg , Germany ) according to the manufacturer’s instructions . The following antibodies were used for staining: CD8-PECy7 ( 1:200 ) , CD3-FITC ( 1:200 ) , TNFα-PE ( 1:100 ) , IFN-γ-APC ( 1:100 ) ( eBioscience , Frankfurt , Germany ) , CD4-BD Horizon V450 ( 1:200 ) ( BD Biosciences , Heidelberg , Germany ) and incubated with FcγR-block diluted 1:100 . Aqua Dye was used to distinguish live/dead cells ( Invitrogen , Life Technologies GmbH , Darmstadt , Germany ) . Cells were collected using a Canto II flow cytometer ( Beckton Dickinson , Heidelberg , Germany ) . Flow cytometry data were analyzed using FlowJo software ( Tree Star , Inc , Ashland , USA . ) . For ELISPOT analysis mouse splenocytes were stimulated with 1:20 diluted Rabipur ( Novartis ) or 0 . 35 mg/ml bovine serum albumin ( Sigma-Aldrich ) . Secreted IFN-γ was detected using a standard ELISpot protocol and measured using a plate reader ( Immunospot Analyzer , CTL Analyzers LLC ) . BALB/c mice were treated by intraperitoneal injection with monoclonal antibodies ( YTS 191 [31] ) against the CD4+ T cell population one day before and after the vaccinations . During the first immunization phase , mice were treated with 200 μl ( 0 . 3 mg ) of 1:50 diluted ascites fluid of YTS 191 antibodies . During the second immunization phase , CD4+ T cells were depleted using a 1:10 dilution . To control efficacy of T cell depletion EDTA-blood probes were stained with fluorochrome conjugated antibodies for 30 min at 4°C using mAbs to mouse CD3 ( CD3ε chain ) , CD4 ( L3T4 ) and CD8a ( Ly-2 ) ( BD Bioscience , Heidelberg , Germany ) two days after each vaccination . After the incubation time , cells were washed and analyzed by the MACSQuant Analyzer and MACSQuantify software ( Miltenyi , Bergisch-Gladbach , Germany ) . Median lethal virus doses ( LD50 ) were determined in BALB/c mice by endpoint titration [32] . Challenge virus was applied by intracerebral ( i . c . ) injection with a volume of 20 μl and an infectious dose of 40-fold LD50 . Body weight and clinical signs of challenged mice were assessed daily over a period of two weeks after infection . Mice with less than 75% of initial body weight were sacrificed . Mice were sacrificed and perfused to wash out blood cells . Next , brains were harvested and divided into telencephalon and cerebellum . Organs were homogenized using the FastPrep-24 instrument ( MP Biomedicals , Eschwege , Germany ) . Total RNA was isolated from the organ homogenates using TRIZOL reagent ( Life Technologies , Darmstadt , Germany ) . For quantitative RT-PCR , 50 ng RNA was used to determine the expression of different mouse proteins utilizing the iScript one step RT-PCR Kit with SYBR Green ( Bio-Rad , Munich , Germany ) according to the manufacturer’s protocol and the CFX96 Touch Real-Time PCR Detection System and its software ( Bio-Rad ) . The following specific primers for qRT-PCR were used: Mm_Gapdh_3_SG ( NM_008084 ) , Mm_Tnf_1_SG ( NM_013693 ) and Mm_Ifng_1_SG ( NM_008337 ) ( Qiagen , Hilden , Germany ) . The protocol for qRT-PCR started with an incubation at 50°C for 10 min . After this first step , probes were heated to 95°C for 5 min , followed by 40 cycles of 95°C for 10s and 60°C for 30 s and plate reading for green fluorescence . Afterwards , melt curve data were collected from 60°C to 90°C at a ramping rate of 0 . 2°C per second . Relative expression values to uninfected controls were normalized to the expression value of the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) . Detection of viral N-protein RNA was performed with the same protocol for qRT-PCR using the following oligonucleotides: 5-GAT CCT GAT GAY GTA TGT TCC TA-3’ ( forward ) , 5’-RGA TTC CGT AGC TRG TCC A-3’ ( reverse ) [33] purchased at Metabion , Germany . Statistical analysis was performed using GraphPad Prism software , Version 6 . 00 . Statistical differences between groups were assessed by the Mann Whitney , Kruskal-Wallis , one-way ANOVA Tukey’s multiple comparisons or Dunnett’s multiple comparisons test .
To verify antigen expression , HeLa cells were transfected with mRNA encoding rabies virus glycoprotein ( RABV-G ) of the Pasteur strain ( GenBank accession number: AAA47218 . 1 ) . Presence of translated glycoprotein at the cell membrane was demonstrated by flow-cytometric cell surface staining using a RABV-G specific antibody indicating protein expression and proper trafficking to the cell membrane . Cells transfected with mRNA encoding influenza hemagglutinin served as negative control ( S2 Fig ) . After showing the expression of functional RABV-G in vitro , we next tested whether RABV-G mRNA vaccine was able to induce antigen-specific immune responses in vivo . BALB/c mice were immunized on days 0 and 21 with 80 μg of the RABV-G mRNA or buffer . Two weeks after the second immunization , blood was drawn for antibody analysis and splenocytes were isolated for the analysis of antigen specific T cells . After two vaccinations , all RABV-G immunized mice developed relevant virus neutralizing ( VN ) titers of ≥0 . 5 IU/ml ( range: 5 . 9 to 70 . 2 IU/ml ) , considered as protective in humans , dogs and cats [34] . Buffer treated mice were negative for rabies specific antibodies ( Fig 1A ) . RABV-G mRNA vaccine induced antigen-specific T cells were analyzed by ELISPOT assay after stimulation of isolated spleen cells with Rabipur , a licensed rabies vaccine containing inactivated rabies virus . This analysis revealed that in splenocytes of RABV-G mRNA vaccinated mice , IFN-γ secreting cells were detected upon Rabipur stimulation , but not after stimulation with BSA ( negative control ) or in splenocytes of buffer treated control mice ( Fig 1B ) . We addressed the dose-response relationship of the RABV-G vaccine and evaluated if the observations of the initial experiment in BALB/c were strain specific . BALB/c mice produce predominantly Th2 helper cells and might therefore develop a better antibody response . In contrast , C57BL/6 mice exhibit a Th1 bias and more pronounced cellular immune responses [35] . Female C57BL/6 ( Fig 1C ) and BALB/c mice ( Fig 1D ) were vaccinated on days 0 and 21 with vaccine doses ranging from 1 . 25 μg to 80 μg mRNA . For positive control , mice received the licensed vaccines HDC or Rabipur . Due to volume restrictions we vaccinated mice intramuscularly with 100 μl ( 0 . 1 human doses ) of HDC and Rabipur , previously shown to be protective in mice [36 , 37] . Two weeks after the second immunization , 100% of C57BL/6 and 90% ( 29 of 32 ) of BALB/c mice injected with ≥10 μg RABV-G mRNA vaccine developed virus neutralizing ( VN ) titers of ≥0 . 5 IU/ml . Thus , in both mouse strains , a dose-response correlation was seen and high neutralizing antibody titers were induced at doses ≥10 μg mRNA . In C57BL/6 mice immunization with a dose of 10 μg RABV-G mRNA vaccine ( range: 0 . 5 to 40 . 6 IU/ml ) revealed comparable immunogenicity to HDC ( range: 1 . 5 to 13 . 5 IU/ml ) and significantly higher titers were achieved at mRNA doses of ≥20 μg ( range: 17 . 8 to 92 . 4 IU/ml ) . In BALB/c mice immunogenicity for HDC ( range: 7 . 8 to 92 . 4 IU/ml ) and Rabipur ( range: 17 . 8 to 92 . 4 IU/ml ) equaled that of ≥40 μg RABV-G mRNA ( range: 0 . 2 to 70 . 2 IU/ml ) . These experiments , therefore , indicate comparable immunogenicity of the mRNA vaccine with licensed rabies vaccine and the general induction of specific immune response in mice . Prophylactic vaccination must also induce durable protection . We tested the longevity of the humoral immune response . BALB/c mice treated with two vaccinations on days 0 and 21 and doses of 1 . 25 μg , 5 μg , 20 μg , and 80 μg RABV-G mRNA vaccine or 0 . 1 human dose Rabipur were observed for about one year and antibodies in the serum of vaccinated mice were analyzed monthly . All mice treated with the RABV-G vaccine developed high titers of neutralizing antibodies . We found that after vaccination with 20 μg and 80 μg RABV-G mRNA or with Rabipur antibody titers remained stable throughout the observation period with mean titers between 17 and 65 IU/ml ( Fig 1E ) . For the 1 . 25 μg and 5 μg mRNA vaccine doses , response onset was delayed , but caught up by week 12 of the experiment and titers remained at a high level of ≥ 10 IU/ml . Inter-individual variability was low in all test groups . Although T cells do not prevent initial viral infection of host cells , they provide important impact on rabies virus clearance in mice [38] . Rabies-specific T cell clones have also been isolated from human vaccinees [39] . Thus , we analyzed cellular immune response induced by RABV-G mRNA vaccine in more detail and used the licensed rabies vaccine Rabipur and buffer as positive and negative control group , respectively . We analyzed the presence of antigen specific activated T cells by measuring cytokine induction upon stimulation with a RABV-G spanning overlapping peptide library . Cytokine producing cells were detected by a flow cytometry based method for intracellular cytokine staining ( Fig 2 ) . Six days after a second vaccination with 80 μg RABV-G mRNA or 0 . 1 human dose of Rabipur , frequencies of antigen-specific interferon gamma ( IFN-γ ) and tumor necrosis factor alpha ( TNFα ) positive CD8+ and CD4+ T cells were detected in all vaccinated mice . The frequencies of RABV-G specific CD8+ T cells of mice receiving Rabipur or the RABV-G mRNA vaccine were comparable ( e . g . IFN-γ/TNFα-double positive CD8+ T cells with a mean of 0 . 59% after RABV-G mRNA and 0 . 43% after Rabipur vaccination ) ( Fig 2A , right panel ) . In contrast , antigen-specific CD4+ T cells were significantly elevated in mRNA immunized mice compared to Rabipur treated animals with a high proportion of IFN-γ/TNFα-double positive CD4+ T cells ( mean of 0 . 48% for IFN-γ/TNFα expressing CD4+ T cells after RABV-G mRNA and 0 . 091% after Rabipur vaccination ) ( Fig 2B , right panel ) . These results indicate efficient RABV-G-specific T cell induction by RABV-G mRNA and better induction of CD4+ T cells by the mRNA vaccine compared to Rabipur . In addition , we analyzed the longevity of the cellular immune response induced by RABV-G mRNA . Ten weeks after the second injection ( study day 91 ) splenocytes were isolated from vaccinated and control mice and antigen-specific CD8+ and CD4+ T cells were analyzed upon specific stimulation ( Fig 2C ) . In splenocytes of all mice treated with 80 μg RABV-G mRNA or Rabipur , low , but significant frequencies of activated , antigen-specific CD8+ T cells were detected , characterized by staining of intracellular TNFα and IFN-γ ( Fig 2C , left panel ) . A significantly higher activity of IFN-γ and TNFα expressing CD4+ T cells was detected after mRNA ( mean of 0 . 084% ) compared to Rabipur ( mean of 0 . 034% ) immunization ( Fig 2C , right panel ) . Frequencies of antigen-specific CD4+ T cells were dose dependent and declined with the dose of RABV-G mRNA used for vaccination ( S3 Fig ) . To test the protective capacity of the RABV-G mRNA vaccine against rabies infection , RABV-G mRNA vaccinated mice were challenged intracerebrally ( i . c . ) with infectious rabies virus of strain CVS-11 ( challenge virus standard-11 ) . Intracerebral infection poses an extremely harsh challenge that is artificial , but accepted by the scientific community as a stringent experimental test . Importantly , it also forms the basis of the widely used National Institutes of Health ( NIH ) potency test for rabies vaccines [40] . BALB/c mice were vaccinated on days 0 and 21 with 80 μg RABV-G mRNA . Positive control mice were vaccinated intramuscularly with 0 . 1 human dose of HDC , negative control mice received injection buffer ( Ringer-Lactate solution ) . Six weeks after the second injection , mice were challenged i . c . with 40-fold median lethal doses ( LD50 ) of the CVS-11 strain . Body weight , clinical signs of disease and survival of infected mice were monitored daily . All RABV-G mRNA and HDC vaccinated mice were protected against lethal rabies virus challenge ( Fig 3A ) . None of the RABV-G vaccine treated mice displayed any weight loss . Two mice treated with HDC showed a transient weight loss ( 10–20% of initial body weight ) , but survived the experiment ( Fig 3B ) . In contrast , at day 9 after infection , first buffer treated mice had to be sacrificed due to pronounced weight loss ( 25% of initial body weight ) and none in this group survived the infection . This challenge study clearly indicates that the RABV-G mRNA vaccine induces protective immunity against an otherwise lethal infection . Having demonstrated protection against disease and death , we next analyzed cerebral viral loads in infected mice . As before , we injected BALB/c mice on days 0 and 21 with 80 μg RABV-G mRNA , 0 . 1 human doses of Rabipur or buffer . At day 56 of trial , all animals were infected with a 40-fold LD50 of CVS-11 by i . c . injection in the telencephalon . At days 3 and 6 after infection three animals per group were sacrificed . Perfused brains were tested for rabies virus replication by quantitative RT-PCR of RNA encoding the rabies nucleoprotein ( N protein ) . At day 3 after infection a low quantity of N-protein mRNA was detectable in the telencephalon of animals treated with buffer ( mean: 31 . 4 cycle threshold ( ct ) -value ) whereas the cerebellum was negative for viral N-protein mRNA ( mean above detection limit ) . Ct-values , however , decreased over the period of infection as at day 6 high viral loads were detected in both analyzed parts of the brains ( mean ct-values: 23 . 1 ( telencephalon ) and 24 . 7 ( cerebellum ) ) . N-protein mRNA was not normalized to a cellular house-keeping gene as viral gene expression does not necessarily correlate with cellular gene expression . However , RNA concentration of each sample was determined and the amount of RNA used for the assay was adjusted accordingly . In contrast , all but one of the analyzed brains of mice immunized with RABV-G mRNA or Rabipur were negative for N-protein mRNA at both time points , demonstrating a strong suppression of viral replication below the detection limit after vaccination ( Fig 4A ) . The brain of one mRNA vaccinated mouse was positive for viral N-protein RNA at day 6 after infection ( telencephalon: ct-value of 25 . 4 ) indicating a non-protective response to the mRNA vaccine in one case . The homeostasis of the CNS is maintained by the blood-brain-barrier ( BBB ) , a complex system of different cell types [41] . It has been reported that rabies virus-induced encephalitis results in an elevation of different pro-inflammatory cytokines . Increased levels of TNFα and IFN-γ have been causally linked to increased BBB permeability which also allows the strong influx of immune factors [42 , 43] . We analyzed mRNA levels of TNFα in brains at 3 and 6 days after infection by qRT-PCR together with the viral N protein analyzed above . The mRNA levels of TNFα in the telencephalon rose rapidly in the buffer injected group up to 25 . 8-fold at day 3 and 94 . 6-fold at day 6 after infection compared to non-infected controls , which reflects the early activation of this pro-inflammatory cytokine as response to the virus infection . Also in the cerebellum , the level of TNFα mRNA transcripts rose up to 60 . 5-fold at day 6 compared to uninfected controls , indicating a strong pro-inflammatory innate immune response upon viral spread . In mRNA and Rabipur vaccinated mice TNFα mRNA transcript level was reduced compared to mock vaccinated control group at both analysis time points and different brain sections ( Fig 4B ) . The RABV-G mRNA vaccine induced strong CD4+ T cell responses compared to licensed rabies vaccine ( Fig 2B and 2D ) . In order to assess the mode of action of the mRNA based rabies vaccine , we addressed the role of mRNA vaccine-induced CD4+ T cells in forming VN antibodies and in protecting against challenge infection . To this end , in mRNA vaccinated BALB/c mice CD4+ T cells were depleted during both , prime and boost immunization periods ( around days 0 and 21 ) by injecting a specific anti-CD4 monoclonal antibody [31] . Analysis by flow cytometry confirmed a drastic reduction of the CD4+ T cell population by about 98 . 6% at day 6 and 97 . 1% at day 23 after first immunization ( S4 Fig ) . 28 days after the second immunization , VN antibodies in sera were quantified ( Fig 5A ) . Mice with intact CD4+ cell compartment immunized with either RABV-G mRNA or Rabipur had comparable VN titers with means of about 50 IU/ml ( undepleted positive controls ) . In the CD4-depleted , mRNA immunized group VN titers were strongly reduced: 3 out of 8 mice showed VN titers below 0 . 5 IU/ml and the mean titer of the groups was about 3 IU/ml , i . e . more than 15-fold reduced compared to the CD4-intact , mRNA-vaccinated group . The functional role of CD4+ T cells for the generation of neutralizing antibodies or direct antiviral protection was further reflected by survival rates of mice after lethal i . c . challenge with CVS-11: All mice vaccinated with Rabipur ( undepleted positive control ) survived the challenge infection while buffer injected mice ( negative controls ) had to be sacrificed by day nine post challenge due to dramatic weight loss ( Fig 5C ) . In groups with an intact CD4+ T cell compartment during prophylactic immunization , more than 87% of mRNA-vaccinated mice survived infection ( one out of eight mRNA-immunized mice without detectable virus neutralizing antibodies after immunization had to be sacrificed on day ten due to pronounced weight loss ) ( Fig 5B ) . In the CD4-depleted , mRNA vaccinated group , all mice had to be sacrificed within 11 days after infection with similar kinetics as in the negative control group ( Fig 5C ) in line with the strongly reduced VN titers in this group . We next analyzed immunogenicity in domestic pigs , a large animal model that exhibits relevant physiological and anatomical similarities to humans [44 , 45] . First , we investigated whether the RABV-G mRNA vaccine induces protective antibody titers in large animals with a body weight above 20 kg . Therefore , adult pigs at 6–8 weeks of age ( 22 . 2–31 . 2 kg body weight ) were vaccinated intradermally with 80 μg RABV-G mRNA or buffer at days 0 , 14 and 49 ( Fig 6A ) . mRNA was applied at a three dose schedule as recommended for licensed vaccine benchmarks , however , longer intervals were chosen between vaccinations to assess the impact of each single prime and follow-up booster vaccination . The first two vaccinations with RABV-G mRNA led to seroconversion of all animals with antibody titers >0 . 5 IU/ml . The third vaccination at day 49 did not further increase RABV-G specific neutralizing antibody levels . Eight weeks post second boost RABV-G specific neutralizing antibodies had a mean titer of 2 . 9 IU/ml and were still above the 0 . 5 IU/ml limit . Furthermore , we assessed whether the RABV-G mRNA vaccine induced protective antibody titers in newborn piglets with an immature immune system , thereby extending former findings on vaccine immunogenicity in newborn mice [16] . Piglets ( approx . 1 . 5 kg body weight ) were immunized intradermally with 80 μg or 240 μg RABV-G mRNA vaccine doses within three days after birth and corresponding booster injections three weeks later . One group received 240 μg of irrelevant mRNA . For comparison with a licensed vaccine , one group of piglets received a full human dose of Rabipur that was injected intramuscularly as recommended . All specifically immunized piglets rapidly seroconverted to neutralizing antibody titers >0 . 5 IU/ml which was already reached at day 28 , the first analysis time point after the initial vaccination . Responses to RABV-G mRNA vaccine were dose dependent . Piglets receiving 80 μg RABV-G mRNA developed mean protective titers of 11 . 0 IU/ml at day 28 and 2 . 5 IU/ml at day 70 , while piglets immunized with the 240 μg dose revealed higher mean antibody titers of 56 . 8 IU/ml at day 28 and 8 . 3 IU/ml at day 70 that were comparable to those induced by full doses of the licensed human vaccine ( Fig 6B ) . These data demonstrate that RABV-G vaccine is immunogenic in newborn piglets , leading to rapid seroconversion and indicating comparable VN titer kinetics for mRNA vaccine compared to the licensed Rabipur vaccine .
Rabies is a severe neurological disease with a mortality rate of almost 100% in symptomatic individuals for whom no effective therapy exists [46] . The disease remains endemic in developing countries where stray dogs transmitting the disease are not controlled and the imperative need for better vaccines is illustrated by the fact that in Asia and Africa 3–4 billion people are still considered at risk of exposure to rabies virus [47] . Though vaccination of dogs combined with human post-exposure prophylaxis programs became a focus in rabies elimination , a post-exposure prophylaxis especially in countries at high risk face different difficulties , including delays in patient access to suitable medical care [48] . Efficacy , availability and affordable cost for prophylactic vaccines for human use may significantly contribute to resolve this problem , since the amount of vaccinations in this setting is reduced to a single vaccination and rabies immune globulin is dispensable . Messenger RNA is a promising new vector format that may allow for significant improvements in vaccine manufacture and supply [17 , 18] . In the present study , we demonstrated the immunogenicity and protective efficacy of an experimental mRNA-based rabies vaccine in animals . This mRNA vaccine encoding the Rabies virus glycoprotein was immunogenic upon two injections at microgram doses and resulted in the induction of virus neutralizing antibodies , antigen-specific CD4+ T cells and CD8+ T cells ( Fig 1 ) . Protection against infectious challenge was stringently demonstrated in mice . As the neurotropic virus was directly injected into the central nervous system ( CNS ) , the time frame for effective neutralization of infectious particles by pre-existing antibodies is extremely short . Using qRT-PCR based analysis of the viral nucleoprotein gene it was revealed that spread of the virus was strongly inhibited by RABV-G mRNA vaccination . Protection against intracerebral infection may result from antibodies that neutralize free viral particles before entering nerve cells [49 , 50] or from invading B cells that directly produce neutralizing antibodies in the CNS [51] . We found a clear correlation between the induction of protective virus neutralization titers and survival upon infectious challenge . Our finding that depletion of CD4+ T cells during the immunization phase results in a loss of protection against lethal challenge infection further indicates the need for T cell help in mounting a protective neutralizing antibody response . Interestingly , some mice in the T cell depleted group showed VN titers above 0 . 5 IU/ml but succumbed to the challenge infection . Similar observations have been reported by others as well [52 , 53] and , moreover , a study analyzing the correlation between VN titer and protection against i . c . challenge for BALB/c mice in the NIH potency test for rabies vaccines reported that individual animals with titer up to 7 . 8 IU/ml were not protected [49] . This might indicate that the titer of 0 . 5 IU/ml is rather a surrogate marker for protection for a natural rabies infection ( e . g . intramuscular in the periphery ) than for the laboratory intracerebral infection in our experimental setting . Concerning the induction of neutralizing antibodies , this finding indicates a comparable mode of action for the mRNA vaccine format as seen for cell based vaccines and other vaccine formats [3 , 13] . We analyzed TNFα expression in brains of vaccinated and control animals after rabies infection . In the brains of RABV-G mRNA or Rabipur vaccinated mice , the TNFα mRNA expression rose but to lower levels compared to buffer immunized animals . Though not statistically significant , the data indicate a reduced innate inflammatory reaction which might result in the maintenance of brain homeostasis upon vaccination with RABV-G mRNA or licensed rabies vaccine . TNFα appears to be an important cytokine in the brain for viral clearance with the function to attract effector cells , and therefore also in immunized mice the elevation of TNFα mRNA expression was expected for initiating viral clearance by effector cells . However , while TNFα plays a major role in attracting immune cells and thereby boosting inflammation that may lead to rabies-encephalitis , the direct impact of TNFα on BBB integrity remains controversial [43 , 54] . In buffer-treated mice we found viral replication in the telencephalon ( the site of injection ) and spreading to the cerebellum . In addition , both telencephalon and cerebellum of these animals showed increased TNFα expression consistent with the idea of a compromised BBB integrity and inflammation processes throughout the whole brain . In contrast and disregarding a single non-protected mouse , RABV-G mRNA or Rabipur vaccinated mice survived challenge infections without clear signs of viral replication and spread into the cerebellum in quantitative RT-PCR analyses as early as 3 days after infection . These findings underline the robust protection by the mRNA vaccine . Immunogenicity of RABV-G mRNA vaccine was further assessed in domestic pigs . In adult pigs , titers reached the protective limit of ≥0 . 5 IU/ml after the first immunization and could be further increased by booster vaccination , then remaining stable throughout the experiment . Interestingly , a third vaccination did not result in a further strong titer increase , suggesting a maximal humoral immune response by the prime-boost strategy in pigs . Furthermore , immunogenicity of the RABV-G mRNA was also investigated in newborn piglets , again showing neutralizing antibody titers after the first vaccination in the protective range that were further increased after the booster vaccination . The kinetic of virus neutralizing antibody response for the RABV-G mRNA was comparable to the full human dose of the licensed rabies vaccine Rabipur . These data support and extend previous findings for mRNA vaccines against influenza in adult and newborn mice [16] . A clinical phase I study to test safety and immunogenicity of this RABV-G mRNA vaccine in healthy volunteers has been initiated ( EudraCT no . 2013-002171-17 , NCT02241135 ) . In summary , we further substantiated and extended previously published work on non-replicating influenza-specific mRNA vaccines [16] , proving the protective efficacy of mRNA vaccination in a second , harsh viral challenge model . Unlike in the case of influenza , pre-existing immunity was not expected to affect experimental outcomes especially in pigs . This allowed for bona fide assessments of vaccine immunogenicity in naïve individuals on the basis of a widely recognized and standardized functional correlate of protection ( virus neutralizing titers ) . These findings , together with the stability of mRNA vaccine [16 , 55] and projected as well as observed cost for production of mRNA vaccines [19–21] further substantiate the assumption that this new vaccination strategy may be extended to the prophylaxis and treatment of infectious diseases in general .
|
Although first successful vaccination against rabies virus infection was performed by Louis Pasteur in the 19th century , every year about 50 , 000 patients , predominantly children , succumb to rabies infection because of insufficient availability of effective low-cost vaccines worldwide . The work presented here describes the protective capacity of such a vaccine candidate based on a non-replicating messenger RNA ( mRNA ) . Here we highlight the efficacy of this type of vaccine in a highly fatal viral infection mouse model and demonstrate the induction of accepted correlates of protection in domestic pigs . The results extend and strengthen our previous work on mRNA-based vaccines protecting against Influenza . The data from Rabies and Influenza studies , together with the increased thermostability ( manuscript in preparation ) and the conceived cost-effectiveness of production suggest that non-replicating mRNA-based vaccines are an attractive and promising format for the development of protective vaccines against a wide range of infectious diseases .
|
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2016
|
An mRNA Vaccine Encoding Rabies Virus Glycoprotein Induces Protection against Lethal Infection in Mice and Correlates of Protection in Adult and Newborn Pigs
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Primate lentiviruses have evolved sophisticated strategies to suppress the immune response of their host species . For example , HIV-2 and most simian immunodeficiency viruses ( SIVs ) use their accessory protein Nef to prevent T cell activation and antiviral gene expression by downmodulating the T cell receptor CD3 . This Nef function was lost in HIV-1 and other vpu-encoding viruses suggesting that the acquisition of Vpu-mediated NF-κB inhibition reduced the selection pressure for inhibition of T cell activation by Nef . To obtain further insights into the modulation of NF-κB activity by primate lentiviral accessory factors , we analyzed 32 Vpr proteins from a large panel of divergent primate lentiviruses . We found that those of SIVcol and SIVolc infecting Colobinae monkeys showed the highest efficacy in suppressing NF-κB activation . Vpr-mediated inhibition of NF-κB resulted in decreased IFNβ promoter activity and suppressed type I IFN induction in virally infected primary cells . Interestingly , SIVcol and SIVolc differ from all other primate lentiviruses investigated by the lack of both , a vpu gene and efficient Nef-mediated downmodulation of CD3 . Thus , primate lentiviruses have evolved at least three alternative strategies to inhibit NF-κB-dependent immune activation . Functional analyses showed that the inhibitory activity of SIVolc and SIVcol Vprs is independent of DCAF1 and the induction of cell cycle arrest . While both Vprs target the IKK complex or a factor further downstream in the NF-κB signaling cascade , only SIVolc Vpr stabilizes IκBα and inhibits p65 phosphorylation . Notably , only de-novo synthesized but not virion-associated Vpr suppressed the activation of NF-κB , thus enabling NF-κB-dependent initiation of viral gene transcription during early stages of the replication cycle , while minimizing antiviral gene expression at later stages . Our findings highlight the key role of NF-κB in antiviral immunity and demonstrate that primate lentiviruses follow distinct evolutionary paths to modulate NF-κB-dependent expression of viral and antiviral genes .
Cells are equipped with a plethora of pattern recognition receptors ( PRRs ) that induce an antiviral immune response upon sensing of patterns associated with viral infection . Among them are cytosolic receptors such as cGAS , PQBP1 , IFI16 , and RIG-I recognizing viral DNA or RNA species , as well as restriction factors such as TRIM5α and Tetherin that sense viral capsids or budding virions , respectively [1] . The signaling cascades initiated by these receptors converge in the activation of a few key transcription factors ( i . e . NF-κB , IRF3 and IRF7 ) , which induce the expression of interferons ( IFNs ) and other antiviral factors [1 , 2] . HIV and related simian lentiviruses have evolved sophisticated means to evade these innate sensing pathways . For example , reverse transcription of viral RNA mostly occurs before uncoating of the viral capsid is completed [3] . Thus , viral RNA and DNA intermediates of reverse transcription ( RTIs ) are cloaked by the viral capsid protein and cellular cofactors to prevent their recognition by cytosolic PRRs [4] . However , primate lentiviruses do not only hide to evade recognition by PRRs , but also directly target the signaling cascades that induce an antiviral immune response . Especially the NF-κB pathway is tightly regulated since this transcription factor plays a dual role in the retroviral replication cycle [5] . While NF-κB is essential for efficient LTR-driven viral gene expression , it may also be detrimental to viral replication because it induces the expression of cellular restriction factors and other antiviral genes . We have recently shown that HIV-1 and related primate lentiviruses cope with this double-edged sword by tight temporal regulation of NF-κB activity throughout the viral replication cycle [6] . During the early stage of infection , the accessory protein Nef boosts NF-κB activation to initiate LTR-driven transcription of viral genes . A similar enhancing effect has been described for the lentiviral envelope glycoprotein gp41 [7] . Once efficient and stable viral transcription is ensured by the viral Tat protein , the late protein Vpu inhibits the activation of NF-κB in a dominant manner to suppress expression of type I IFNs , restriction factors and other antiviral genes [6] . This inhibitory effect on NF-κB is highly conserved among primate lentiviral Vpu proteins [6 , 8] , suggesting an important role in vivo . Notably , however , only HIV-1 and a few closely related simian immunodeficiency viruses ( SIVs ) encode a vpu gene . HIV-2 and most SIVs employ an alternative strategy and suppress T cell activation and consequently NF-κB activation and antiviral gene expression by Nef-mediated downmodulation of the T cell receptor ( TCR ) CD3 from the cell surface [9–11] . This Nef function was lost in HIV-1 and its vpu-containing SIV counterparts , i . e . SIVcpz , SIVgor , SIVgsn , SIVmus and SIVmon , infecting chimpanzees , gorillas and greater spot-nosed , mustached and mona monkeys , respectively [10] . The striking concordance between the presence of a vpu gene and loss of a specific Nef function suggests that primate lentiviruses might use Nef-mediated downmodulation of CD3 or Vpu-dependent NF-κB inhibition as alternative strategies to suppress antiviral gene expression during late stages of the viral replication cycle [6 , 10 , 11] . One exception , however , has been reported: SIVolc infecting olive colobus monkeys does not encode Vpu , but lost the CD3 downmodulation function of Nef [11] . Here , we examined how SIVolc might modulate NF-κB activity and whether additional exceptions exist . We show that SIVcol from mantled guerezas also lacks both , a vpu gene and the ability to efficiently downmodulate CD3 via Nef . Comprehensive analyses of Vpr proteins from a large panel of diverse primate lentiviruses demonstrated that those from SIVolc and SIVcol are most effective in inhibiting the activation of NF-κB , thereby suppressing the induction of IFN expression . Thus , primate lentiviruses evolved at least three alternative strategies ( via Nef , Vpu or Vpr ) to attenuate NF-κB-dependent antiviral immune activation . Our results illustrate the enormous evolutionary flexibility of lentiviral accessory proteins and corroborate the role of NF-κB as a key regulator of antiretroviral immune responses .
Of more than 20 different SIV investigated , SIVolc from olive colobus monkeys ( Procolobus verus ) is the only known vpu-deficient primate lentivirus that fails to downmodulate CD3 via Nef [10 , 11] . All other vpu-deficient SIVs , including SIVwrc from Western red colobus monkeys ( Piliocolobus badius badius ) , a close relative of SIVolc [12] , use their Nef protein to suppress CD3-mediated T cell activation . To determine whether SIVolc is the only exception , we analyzed the CD3 downmodulation activity of SIVcol from mantled guerezas ( Colobus guereza ) , whose Nef protein has not been fully characterized so far . SIVcol Nef caught our attention as it fails to downmodulate CD4 , but efficiently decreases CXCR4 surface levels , thereby differing from all other lentiviral Nef proteins investigated [13] . Although SIVcol and SIVolc infect Old World monkey species of the Colobinae subfamily , they are only distantly related [14] . CD3 downmodulation was analyzed in human peripheral blood mononuclear cells ( PBMCs ) infected with HIV-1 NL4-3 IRES eGFP constructs encoding the nef alleles of SIVcol isolates CGU1 , CM243 , and CM1437 , SIVolc 97CI12 , or SIVwrc 98CI04 ( S1A Fig ) . HIV-1 NL4-3 and SIVmac239 Nefs served as controls . Flow cytometric analyses confirmed [11] that Nef from SIVolc does not downmodulate CD3 ( Fig 1A ) . Interestingly , a similar phenotype was observed for the three SIVcol Nefs , which did not or only inefficiently decrease CD3 cell surface levels in human cells . Notably , all Nef proteins were expressed and functional as they efficiently increased virion infectivity by antagonizing the host restriction factor SERINC5 ( Fig 1B ) and decreased surface levels of CD28 and/or CXCR4 ( S1B and S1C Fig ) . Since lentiviral Nef proteins target the ζ chain of the TCR complex [15] , we PCR-amplified and cloned the CD3ζ chain of colobus monkeys to exclude that lack of activity in SIVcol and SIVolc Nefs is due to species-specific differences in the target sequence . The intracellular domain of human or colobus CD3ζ was fused to the extracellular domain of human CD8 to facilitate detection by flow cytometry . While SIVwrc and SIVmac Nefs downmodulated the human and colobus orthologs with similar efficiencies , SIVolc and SIVcol Nefs had no significant effects ( Fig 1C , S1D Fig ) . Thus , SIVolc and SIVcol lack efficient Nef-mediated suppression of T cell activation , as well as Vpu-mediated inhibition of NF-κB activation , and it remained unclear whether/how they might suppress NF-κB-dependent antiviral gene expression . Besides Vpu and Nef , the accessory protein Vpr of the lab-adapted HIV-1 strains 89 . 6 , NL4-3 , HxBru , and IIIB_LAI has been suggested to modulate the induction of NF-κB-dependent antiviral and proinflammatory gene expression [16–20] . To obtain more comprehensive insights into the effect of Vpr on NF-κB signaling and immune activation , we examined a panel of 32 phylogenetically diverse vpr alleles representing all major lineages of HIV and SIV ( i . e . HIV-1/SIVcpz/SIVgor , HIV-2/SIVsmm/SIVmac , SIVgsn/mon/mus , SIVrcm , SIVsyk , SIVcol , SIVwrc/SIVolc , SIVsab , and SIVlst ) [12] . The deduced Vpr amino acid sequences varied considerably in their lengths ( 83 to 138 amino acids ) and showed limited sequence conservation ( S2A Fig ) . One exception was a highly conserved EAxxHF motif in the N-terminal α-helical domain , known to be important for the induction of a G2 cell cycle arrest , nuclear localization and virion-packaging of Vpr [21 , 22] . To determine the effect of these Vpr proteins on NF-κB activity , we took advantage of a reporter vector expressing firefly luciferase under the control of three NF-κB binding sites [6] . HEK293T cells were cotransfected with this reporter construct , expression plasmids for Vpr , and an NF-κB-independent Gaussia luciferase vector to normalize for cell viability and transfection efficiencies . In the absence of any stimulus , most Vpr proteins increased NF-κB activity 2- to 50-fold , with those of SIVgsn , SIVmon and SIVlst having the strongest effects ( Fig 2 , upper panel ) . In contrast , Vprs of SIVrcm , SIVcol and SIVolc had no significant effect or even decreased NF-κB activity . While SIVrcm Vpr was hardly detectable by Western blotting , inefficient expression or induction of cell death did not explain the lack of NF-κB modulation by SIVcol and SIVolc Vprs ( S2B and S2C Fig ) . To further analyze how primate lentiviral Vpr proteins modulate NF-κB activation , we next tested the effects of all Vprs in the presence of TNFα , a potent activator of NF-κB . Again , the effects varied substantially between different Vpr proteins: those from HIV-1 THRO , SIVgsn , SIVmon , SIVmus , SIVmac , SIVsab , and SIVlst enhanced NF-κB-driven reporter gene expression up to 5-fold , whereas SIVolc and SIVcol Vprs suppressed NF-κB activation by about 9-fold ( Fig 2 , middle panel ) . To investigate whether the effects of Vpr on NF-κB-mediated gene expression are independent of the receptor , we repeated the experiment using a constitutively active mutant of IKKβ for stimulation . This mutant induces the phosphorylation and degradation of IκBα , the inhibitor of NF-κB , and allows clarifying whether active Vpr proteins target the NF-κB pathway upstream or downstream of the IKK complex . While the impact of lentiviral Vprs on NF-κB activity was again highly variable ( Fig 2 , bottom panel ) , the effects correlated well with those observed upon stimulation with TNFα ( S2D Fig ) . However , when IKKβ instead of TNFα was used for stimulation , only SIVgsn Vpr significantly boosted NF-κB activity . Most Vprs displayed modest suppressive effects , while those of SIVcol and SIVolc were highly potent inhibitors ( 69–95% and 97% reduction , respectively ) . In line with the high evolutionary conservation of the NF-κB signaling cascade [23] , the potent inhibitory effects of SIVcol and SIVolc Vpr were also observed in a simian cell line ( S2E and S2F Fig ) . To assess whether Vpu or Nef function affected the selection pressure for Vpr-mediated modulation of NF-κB activity , we grouped the Vpr alleles according to the presence or absence of a vpu gene and efficient Nef-mediated CD3 downmodulation activity in the respective viruses ( Fig 2 , right panels ) . On average , Vpr proteins of lentiviruses expressing Vpu ( HIV/SIVvpu ) or downmodulating CD3 ( HIV/SIVCD3 ) inhibited NF-κB less efficiently than those of SIVolc/col , or even boosted the activation of this transcription factor . While inhibition of NF-κB may confer a selection advantage as it suppresses antiviral gene expression , primate lentiviruses also need to ensure efficient initiation of NF-κB-dependent viral gene expression . To achieve this , most HIV/SIV strains use Nef and potentially gp41 to boost NF-κB activation during early stages of the replication cycle [6 , 7] . Some viruses ( e . g . SIVgsn , SIVmon ) , however , lack the ability to enhance NF-κB activation via Nef and may use Vpr instead [6] . Thus , several viral proteins seem to cooperate or compensate for each other in order to regulate the activation of NF-κB throughout the viral replication cycle . Another example is SIVsmm , which induces only low levels of immune activation and apoptosis despite high levels of viremia in infected sooty mangabeys [24] . While this virus prevents T cell activation via Nef-mediated downmodulation of CD3 , its Vpr protein also inhibited TNFα- and IKKβ-induced NF-κB activation , albeit to a lesser extent than SIVolc and SIVcol Vpr . To test whether Vpr-mediated modulation of NF-κB activity affects antiviral gene expression , HEK293T cells were cotransfected with expression vectors for Vpr and a reporter construct expressing firefly luciferase under the control of the IFNβ core promoter ( Fig 3A ) . Cells were stimulated with Sendai virus to activate both , NF-κB- and IRF3-mediated transcription [6 , 25] . Both pathways are evolutionarily highly conserved [23 , 26 , 27] . With the exception of a few orthologs ( e . g . those of SIVmon , SIVmus , SIVsab ) , most Vprs suppressed the activation of the IFNβ promoter ( S3 Fig ) . With a >10-fold reduction , SIVolc and SIVcol Vpr were the most potent inhibitors . To determine whether this effect can be attributed to reduced NF-κB activity , the experiment was repeated using a mutant IFNβ promoter lacking the NF-κB binding site ( Fig 3A ) [6] . Even in the absence of any NF-κB binding site , many Vprs moderately inhibited luciferase reporter gene expression ( S3 Fig ) , suggesting that NF-κB-independent and/or unspecific inhibitory effects contribute to Vpr-mediated suppression of IFNβ induction . On average , however , SIVolc and SIVcol Vprs suppressed IFNβ promoter activity substantially more efficiently in the presence ( 7 . 3-fold ) than in the absence ( 2 . 0-fold ) of NF-κB binding sites ( Fig 3B ) . Thus , SIVcol and SIVolc Vpr proteins inhibit virus-induced IFN expression mainly by interfering with NF-κB activation . To analyze modulation of immune activation and IFNβ expression by Vpr in infected cells , we inserted 13 vpr alleles with varying effects on NF-κB into the CH293 HIV-1 infectious molecular clone ( IMC ) . We selected CH293 since it represents a primary strain of the most widespread clade C of HIV-1 [28] . The vpr open reading frame in the vif-tat1 intergenic region of HIV-1 M CH293 was replaced by restriction sites for XbaI and MluI , and heterologous AU1-tagged vpr alleles were inserted to generate a derivative named CH293 . 1 ( Fig 4A ) . Premature stop codons were inserted in the vpu gene to investigate whether some Vpr proteins may compensate for the lack of Vpu-mediated NF-κB inhibition . In contrast , the nef and env open reading frames were maintained as the respective gene products have been shown to boost rather than suppress NF-κB activation [6 , 7] . All proviral constructs expressed their respective heterologous Vpr protein ( Fig 4B , lower panel ) and ( with the exception of HIV-2 20_56 ) all Vprs were detected in purified viral particles ( Fig 4B , upper panel ) . In some cases ( e . g . HIV-2 20_56 ) , exchange of vpr reduced Env expression and thus infectious virus yield ( Fig 4B , S4A Fig ) . This defect , however , could be rescued by pseudotyping the virions with the vesicular stomatitis virus glycoprotein ( VSV-G ) ( S4A Fig ) . Unfortunately , however , the IMCs encoding SIVcol CGU1 , CM243 and CM1437 vpr remained non-infectious , possibly due to the disruption of splice sites regulating Tat expression [29] , and could therefore not be used for infection studies . All chimeric CH293 constructs were tested in transfected HEK293T cells to elucidate the impact of Vpr on NF-κB activity if expressed in a proviral context , via the viral LTR promoter . Here , the CH293 . 1 wild type virus induced the activation of NF-κB in the absence of any other stimuli ( Fig 4C ) . This activation was increased about 4-fold in the absence of intact vpu and vpr genes . Lack of Vpu-mediated NF-κB inhibition was rescued by in cis expression of SIVsmm , SIVcol and SIVolc Vpr ( Fig 4C ) . In agreement with the results obtained using expression vectors for Vpr ( Fig 2 ) , SIVgsn Vpr boosted the activation of NF-κB . To validate these effects in infected T cells , we transduced SupD1 cells with VSV-G pseudotyped CH293 . 1 vpu- strains expressing the Vpr proteins of HIV-1 NL4-3 , SIVgsn , SIVsmm , SIVolc or SIVwrc . This T cell line is a derivative of SupT1 cells and expresses a short-lived firefly luciferase under the control of an NF-κB promoter that allows monitoring of NF-κB activation over time [6] . In agreement with published data [6] , vpu-defective HIV-1 CH293 . 1 constructs induced higher levels of NF-κB activation than the parental virus ( Fig 4D , S4B Fig ) . Lack of Vpu-mediated NF-κB inhibition was rescued by SIVsmm and SIVolc ( but not by HIV-1 and SIVwrc ) Vprs . Again , SIVgsn Vpr enhanced the activation of NF-κB . Notably , these differences in NF-κB activity were not due to differences in infection rates ( S4C Fig ) . To test whether Vpr-mediated inhibition of NF-κB activation results in attenuated immune activation in primary cells , we infected human PBMCs from three different donors with CH293 . 1 wt or vpu- viruses expressing either no Vpr or the Vpr protein of HIV-1 NL4-3 , HIV-1 CH293 , SIVolc or SIVwrc . At 72 hours post-infection , IFNβ expression levels were quantified by qRT-PCR . In agreement with potent Vpu-mediated inhibition of NF-κB activation , CH293 . 1 wild type induced only low levels of IFNβ and deletion of vpu and vpr led to a 2- to 3-fold increase in IFNβ expression ( Fig 4E ) . This immune activation was fully suppressed by in cis complementation with Vpr of SIVolc , but not SIVwrc or HIV-1 Vprs ( Fig 4E , S4D Fig ) . Furthermore , SIVolc Vpr also inhibited induction of IFI44 expression , a typical ISG with proposed anti-HIV-1 activity [30] , which was upregulated in PBMCs infected with vpu-deficient CH293 . 1 ( S4E Fig ) . Higher IFNβ and IFI44 levels were not due to increased infection rates ( S4F Fig ) . Thus , SIVolc Vpr is a potent inhibitor of NF-κB-driven immune activation in infected primary cells that can compensate for the lack of vpu . HIV-1 Vpr is well-known for its ability to induce a G2 cell cycle arrest , a process that involves the recruitment of a DCAF1/DDB1/Cul4 E3 ligase complex and has been shown to mediate escape from innate immunity [31] . To investigate whether the inhibition of NF-κB activation by SIVolc and SIVcol Vpr depends on this activity , we infected Jurkat T cells with the chimeric CH293 . 1 viruses and analyzed cell cycle progression by flow cytometry . While HIV-1 Vprs inhibited the G2/M transition as expected , this was not the case for SIVolc Vpr ( Fig 5A ) . Thus , the ability of Vpr proteins to inhibit NF-κB activation did not correlate with the induction of cell cycle arrest . In agreement with this finding , SIVcol and SIVolc efficiently suppressed the activation of NF-κB upon knockdown of DCAF1 ( S5A Fig ) . To further elucidate the mechanisms underlying Vpr-mediated modulation of NF-κB activation , we directly compared the ability of SIVolc and SIVcol Vpr to inhibit NF-κB activation upon TNFα stimulation or overexpression of the restriction factor Tetherin , a constitutively active mutant of IKKβ , or p65/NF-κB itself . Dominant negative mutants of IKKβ and βTr-CP , which prevent the degradation of IκB , served as controls . While SIVolc Vpr generally suppressed NF-κB activity by >90% , SIVcol Vpr reduced Tetherin-induced signaling only by about 30% ( Fig 5B ) . These findings suggest that the distantly related SIVcol and SIVolc Vprs have evolved different mechanisms to inhibit NF-κB-mediated immune activation . In accordance with this , SIVolc , but not SIVcol stabilized IκB ( Figs 5C and 3A , S5B Fig ) and reduced the activating phosphorylation of p65 at serine 529 ( Figs 5D and 3A , S5C Fig ) upon TNFα stimulation . Thus , while both , SIVcol and SIVolc Vpr suppress NF-κB activation independently of DCAF1 and the induction of a cell cycle arrest , only SIVolc Vpr prevents degradation of IκB and phosphorylation of p65 . HIV-1 boosts NF-κB activation during early stages of its replication cycle to ensure efficient LTR-driven expression of viral genes , while it suppresses activation of this transcription factors during later stages to minimize cellular antiviral gene expression [6] . Similar to HIV-1 LTRs , those of SIVolc and SIVcol contain putative NF-κB binding sites ( S6A Fig ) . To analyze NF-κB dependency , we amplified the LTR sequences of these simian viruses from cDNA of naturally infected monkeys and generated firefly luciferase reporter constructs . Experiments in transfected HEK293T cells revealed that these promoters are activated upon stimulation with TNFα ( Fig 6A ) or a constitutively active mutant of IKKβ ( Fig 6B ) , similarly to an HIV-1 LTR promoter . LTR activity was suppressed by SIVolc and SIVcol Vpr ( Fig 6A and 6B ) , and mutational analyses showed that this inhibitory activity depends on the presence of NF-κB , but not Sp1 binding sites ( S6B Fig ) . In summary , our results suggest that SIVolc and SIVcol may also benefit from a temporal regulation of NF-κB activation that enables initiation of viral gene expression during early stages while minimizing cellular antiviral gene expression during late stages of the viral replication cycle . Vpr may act early and late on NF-κB activity because it is expressed during later stages of the replication cycle , but also incorporated into viral particles . To determine whether virion-associated and/or de-novo expressed Vpr accounts for the effect on NF-κB activity , HEK293T cells were transfected either with HIV-1 CH293 . 1 vpu- chimeras expressing heterologous Vpr proteins in cis or cotransfected with CH293 . 1 vpu- vpr- and an expression vector for Vpr in trans . In the latter case , Vpr is incorporated into virions but not produced in newly infected cells . Western blotting confirmed that most Vprs were efficiently incorporated ( S7A Fig ) . Only SIVwrc Vpr was hardly detectable in virions if provided in cis ( S7A Fig , Fig 4B ) , and the results obtained with this Vpr need to be interpreted with caution in this assay . The in cis or in trans complemented viruses were used to infect SupD1 reporter cells , and NF-κB activity was monitored for 80 hours . Infections rates were controlled by flow cytometric analysis ( S7B Fig ) . Only vpu/vpr defective but not wild type HIV-1 CH293 . 1 induced the activation of NF-κB ( Fig 7A , S7C Fig ) . Immune activation by CH293 . 1 vpu- vpr- could not be suppressed by in trans or in cis complementation with CH293 or SIVwrc Vpr , confirming that these proteins do not inhibit NF-κB activation ( Fig 7A and 7B , S7C Fig ) . In contrast , expression of SIVolc Vpr in cis but not in trans suppressed activation of NF-κB by vpu-deficient CH293 . 1 constructs ( Fig 7C , S7C Fig ) . Thus , only de-novo synthesized but not virion-associated SIVolc Vpr modulates the activation of NF-κB in infected T cells . Similarly , SIVgsn Vpr boosted NF-κB activation in cis but not in trans ( Fig 7D , S7C Fig ) . Notably , the results were not biased by multiple rounds of infection as treatment with the protease inhibitor Darunavir did not significantly affect induction of NF-κB activation upon HIV-1 infection or NF-κB inhibition by SIVolc Vpr , although it efficiently blocked de novo generation of infectious HIV-1 particles ( S7D–S7F Fig ) . Thus , SIVolc Vpr will not interfere with efficient initiation of viral gene expression early after infection , since de novo synthesis of this viral protein is required to suppress the activation of NF-κB in infected T cells .
In this study , we show that primate lentiviruses use at least three alternative proteins ( i . e . Nef , Vpu or Vpr ) to suppress NF-κB-mediated immune activation in infected cells . HIV-2 and the majority of SIVs reduce T cell activation and NF-κB activation by Nef-mediated downmodulation of CD3 [10 , 11] . However , this function was lost independently twice during lentiviral evolution when the precursors of the SIVgsn/mon/mus and SIVcpz/gor/HIV-1 lineages acquired a vpu gene ( Fig 8 , left panel ) . We have recently shown that Vpu proteins directly target the canonical NF-κB signaling pathway and inhibit nuclear translocation of p65 to suppress expression of type I IFNs and other antiviral factors [6] . This function is highly conserved among primate lentiviruses encoding vpu , suggesting that the evolution of Vpu-mediated NF-κB inhibition has relieved the selection pressure for suppressing T cell activation by Nef . Here , we demonstrate that SIVcol and SIVolc , which lack a vpu gene and fail to efficiently downmodulate CD3 via Nef , evolved Vpr as potent inhibitor of NF-κB activity and consequently type I IFN expression . Our findings are another example for the enormous functional plasticity of lentiviral accessory proteins and add to the accumulating evidence that these proteins often compensate for each other or cooperate to accomplish the same goal . For example , a similar evolutionary toggling between accessory viral proteins has been described for the counteraction of cellular restriction factors: While HIV-2 and related SIV strains use Vpx to antagonize the host restriction factor SAMHD1 in their respective host species , other primate lentiviruses achieve this by using Vpr [32] . Similarly , primate lentiviruses switched several times between Vpu- and Nef-mediated Tetherin antagonism before giving rise to HIV-1 [33] . Finally , three lentiviral proteins ( i . e . Nef , Vpu and Env ) cooperate in the downmodulation of CD4 [13] . This enormous functional divergence of accessory proteins even from the same group or lineage of HIV or SIV illustrates that results obtained with a single allele need to be interpreted with great caution . Thus , although all SIVcol and SIVolc Vprs analyzed in this study efficiently suppressed the activation of NF-κB , other isolates of these viruses may use yet another strategy to minimize immune activation . In fact , the large differences in modulation of NF-κB activity by HIV-1 Vpr proteins observed in the present study may explain why previous reports on the role of Vpr in immune activation yielded contradictory results [16 , 19 , 20 , 34–43] . While several groups reported reduced nuclear translocation of p65 and decreased secretion of IFNs in the presence of Vpr [16 , 34–38] , others observed no effect on nuclear translocation and DNA binding of this transcription factor [17] , or even reported increased NF-κB-mediated immune activation [19 , 20 , 39–43] . Furthermore , modulation of NF-κB activity may not only depend on the Vpr proteins analyzed but also on the stimulus used to activate NF-κB signaling . We therefore examined several stimuli ( TNFα , Tetherin , IKKβ , p65 , Sendai virus ) in various cell types from different species ( PBMCs , SupD1 , HEK293T , COS-7 ) . To better mimic the in vivo situation , we generated chimeric HIV-1 constructs and monitored the effects of Vpr on NF-κB and immune activation in virally infected human PBMCs . SIVolc and SIVcol Vpr potently suppressed NF-κB activation under all experimental conditions . Flow cytometric analyses revealed that SIVolc stabilizes IκBα upon TNFα stimulation . As expected , the stabilization of this endogenous NF-κB inhibitor also prevented phosphorylation of p65 at serine 529 by casein kinase II [44] . Notably , SIVcol Vpr seems to target different steps of the NF-κB signaling cascade as it neither affected p65 phosphorylation nor IκBα degradation . Moreover , SIVcol Vpr suppressed Tetherin-induced NF-κB activation by only 30% , while SIVolc Vpr inhibited it by more than 90% . It has been suggested that Vpr may suppress NF-κB activation by preventing the sensing of reverse transcription intermediates ( RTIs ) [31] . Laguette and colleagues showed that HIV-1 Vpr induces the degradation of RTIs by recruitment of the SLX4-associated MUS81-EME1 endonucleases via DCAF1 , a process that might also prevent G2/M cell cycle transition . A more recent study , however , suggested that some Vpr proteins can induce a cell cycle arrest also in the absence of SLX4 [45] . Here , we show that the ability of SIVcol and SIVolc Vpr to suppress NF-κB activation is independent of the induction of a cell cycle arrest and the adaptor protein DCAF1 . In agreement with this , SIVcol and SIVolc Vpr inhibited NF-κB in both , human and simian cells , although they fail to recruit the human SLX4 complex and do not induce a cell cycle arrest in human cells [46] . In our experiments , expression of HIV-1 Vpu and SIVolc Vpr resulted in a 2- to 3-fold decrease in IFNβ mRNA levels in infected cells ( Fig 4E ) . Although these differences may seem low , it is very likely that the suppression of NF-κB activation by Vpu and/or Vpr confers a selection advantage to the virus: First , the observation that Vpu-mediated NF-κB inhibition is conserved among almost all lentiviruses encoding this accessory gene suggests that this activity constitutes a significant fitness advantage . Second , NF-κB is a broad regulator of antiviral gene expression , and its modulation will probably not only affect type I IFN production , but also a variety of other antiviral proteins that cooperate in inhibiting viral replication . Finally , the inhibitory effects determined by qRT-PCR may have been masked by uninfected bystander cells and suppression of antiviral gene expression is presumably more pronounced within infected cells . Global transcriptome analyses in combination with ex vivo or even in vivo replication kinetics will be necessary to decipher the overall effects of Vpu-/Vpr-mediated NF-κB inhibition on cellular gene expression , viral replication and spread . While it is not known whether Nef-mediated downmodulation of CD3 was lost before or after the evolution of Vpr-mediated NF-κB inhibition , it is clear that both accessory proteins target the NF-κB signaling cascade at different steps ( Fig 8 , right panels ) . By downmodulating CD3 , Nef specifically inhibits the very first step of the T cell receptor signaling pathway , whereas SIVolc and SIVcol Vpr target the NF-κB signaling cascade further downstream and may thus exert inhibitory activities on several pathways that culminate in the activation of NF-κB . Although each viral particle contains about 275 Vpr molecules [47] , inhibition of NF-κB signaling requires the de-novo synthesis of SIVolc Vpr . Thus , Vpr ( like Vpu ) suppresses NF-κB activity only during late stages of the viral replication cycle , thereby enabling the activation of this transcription factor during early stages to initiate LTR-dependent viral gene expression . As soon as the viral Tat protein ensures efficient viral gene expression , Vpr ( or Vpu ) inhibit the activation of NF-κB to limit immune activation and antiviral gene expression . In summary , our findings highlight the key role of NF-κB in antiviral immunity and show that primate lentiviruses follow distinct evolutionary paths to balance NF-κB-dependent expression of viral and antiviral genes . The present results improve our understanding of the modulation of NF-κB-driven proinflammatory gene expression and thus shed light on the establishment of viral latency and the pathophysiology of HIV infections , since chronic immune activation is an important driver of the progression to AIDS . Finally , our data add to the accumulating evidence that lentiviral accessory proteins do not only directly target restriction factors to evade the immune system but also interfere with their expression by modulating innate signaling cascades .
Experiments involving human peripheral blood mononuclear cells were reviewed and approved by the Institutional Review Board ( i . e . the Ethics Committee of Ulm University ) , and individuals and/or their legal guardians provided written informed consent prior to donating blood . All blood samples were anonymized before use . The use of established cell lines ( HEK293T , COS-7 , TZM-bl and Jurkat cells ) did not require the approval of the Institutional Review Board . No non-human primates were involved , harmed , sampled or kept for this study . cDNA of mantled guerezas ( Colobus guereza ) had been obtained from bushmeat samples of wild-caught animals in previous studies [48 , 49] . Similarly , the cDNA of a Peter’s Angola colobus ( Colobus angolensis palliatus ) used in this study had been prepared before [50] . Primers flanking the nef ( oligonucleotides P1 , P2 ) and vpr ( oligonucleotides ( P11 , P12 ) open reading frame ( ORF ) were used to PCR-amplify the genes from cDNA of mantled guerezas ( Colobus guereza ) infected with SIVcol CM243 or CM1437 . PCR products from five independent amplifications were sequenced to identify the most abundant sequence variant for subsequent cloning . SIVcol nef alleles were cloned via HpaI and MluI restriction sites into HIV-1 NL4-3-based proviral constructs coexpressing eGFP via an internal ribosome entry site ( IRES ) [51] ( oligonucleotides P3-P10 ) . NL4-3 IRES eGFP reporter viruses containing SIVolc and SIVwrc nef alleles have been described before [11] . SIVcol CM243 and CM1437 vpr alleles were fused to an N-terminal AU-1 tag and cloned via XbaI and MluI restriction sites into bicistronic pCG vectors coexpressing eGFP via an IRES ( oligonucleotides P13 , P14 ) . All remaining vpr alleles were either chemically synthesized or amplified from proviral constructs before cloning into the pCG expression vector . Notably , N-terminal tagging was previously shown to not affect Vpr function [31] . Human SERINC5 was expressed from PBJ6 ( derived from PBJ5 by removing the SV40 origin of replication from the SV40-HTLV-1 hybrid promoter region ) expression vectors [52] . The coding sequence of colobus CD3ζ was amplified essentially as described [50] . Total RNA from PBMCs of a Peter’s Angola colobus ( Colobus angolensis palliatus ) was extracted using Qiagen RNeasy Plus Mini Kit and was used to prepare cDNA using Transcriptor High Fidelity cDNA Synthesis Kit ( Roche ) . Nested PCR was performed on cDNA using Pfx Supermix ( Life Technologies ) and two primer pairs binding in untranslated regions ( oligonucleotides P15-P18 ) . PCR products were sequenced and the resulting sequences were assembled to build a reference coding sequence . The PCR products were subsequently cloned into the pCR-BluntII-TOPO vector ( Life Technologies ) . Five individual clones were sequenced using M13 fw and M13 rev primers as well as two CD3ζ specific sequencing primers ( oligonucleotides P19 , P20 ) . The intracellular domain of CD3ζ was fused to the extracellular and transmembrane domain of human CD8 ( amino acids 1–205 ) , and cloned into the CMV-promoter based pCG expression vector via XbaI/MluI . Oligonucleotides P21 and P22 were used to PCR-amplify the 3’ LTR from cDNA of mantled guerezas infected with SIVcol CM243 . PCR products from five independent amplifications were sequenced to identify the most abundant sequence variant for subsequent cloning . The SIVolc 97CI12 LTR sequence was derived from the Los Alamos sequence database and synthesized ( Baseclear ) . SIVcol CM243 ( oligonucleotides P23 , P24 ) and SIVolc 97CI12 were cloned via MluI and XhoI restriction sites into pGL3-enhancer vectors expressing firefly luciferase under the control of the respective LTR . Please refer to S1 , S2 , S3 and S4 Tables in the supporting information files for oligonucleotide sequences P1-P24 . Generation of the infectious molecular clone ( IMC ) of the HIV-1 group M subtype C chronic control virus CH293 has been described previously [28] . To monitor the ability of Vpr proteins to modulate NF-κB activation during infection , we created a variant of CH293 allowing the insertion of AU1-tagged vpr alleles from various HIV and SIV species via unique XbaI and MluI restriction sites . This modified version was named CH293 . 1 . The CH293 vpr open reading frame ( ORF ) in the vif/tat1 intergenic region was replaced by XbaI and MluI restriction sites and the following additional mutations were introduced using overlap extension PCR: The vpr start codon in vif was mutated with a synonymous mutation in the vif ORF , so that the Vif protein would remain unchanged and functional . Since the insertion of a new vpr gene also introduces a second tat start codon , an additional base ( cytosine ) was introduced downstream of the MluI restriction site , prior to the original tat start codon . This creates a frameshift resulting in premature stop codons in all possible reading frames of the inserted second tat start codon to avoid the expression of an additional Tat protein ( oligonucleotides P25-P28 ) . Two additional XbaI restriction sites within the env sequence of CH293 were mutated with synonymous mutations in the env ORF to facilitate cloning via XbaI/MluI ( oligonucleotides P29- P32 ) . Finally , vpr alleles with N-terminal AU1 tag were excised from pCG expression constructs and cloned into CH293 . 1 via the XbaI/MluI restriction sites . When indicated , Vpu expression was disrupted by insertion of two stop codons downstream of the vpu start codon using the QuikChange II XL site-directed mutagenesis kit ( Agilent Technologies ) according to the manufacturer’s instructions ( oligonucleotides P33 , P34 ) . Please refer to S5 Table of the supporting information files for oligonucleotide sequences P25-P34 . Human Embryonic Kidney ( HEK ) 293T cells and COS-7 cells ( both obtained from the American Type Culture Collection ( ATCC ) ) were first described by DuBridge et al . [53] and Gluzman [54] , respectively . TZM-bl reporter cells ( kindly provided by Drs . Kappes and Wu and Tranzyme Inc . through the NIH AIDS Reagent Program [55] ) were used to determine infectious virus yield . All three cell lines were maintained in Dulbecco’s modified Eagle medium ( DMEM ) supplemented with 10% fetal calf serum ( FCS ) , 2 mM glutamine , 100 μg/ml streptomycin and 100 U/ml penicillin . Jurkat cells ( obtained from the American Type Culture Collection ( ATCC ) ) were generated by Schneider et al . [56] and cultivated in RPMI 1640 medium supplemented with 10% FCS , 2 mM glutamine , streptomycin ( 100 μg/ml ) and penicillin ( 100 U/ml ) . The SupD1 cell line ( generated in our lab [6] ) expresses a short-lived version of an NF-κB-dependent firefly luciferase reporter . SupD1 cells were cultivated in RPMI 1640 medium supplemented with 10% FCS , 2 mM glutamine , streptomycin ( 100 μg/ml ) , penicillin ( 100 U/ml ) and hygromycin B ( 200 μg/ml ) . Peripheral blood mononuclear cells ( PBMCs ) from healthy human donors were isolated from buffy coats using lymphocyte separation medium ( Biocoll separating solution; Biochrom ) and cultivated in RPMI 1640 medium supplemented with 10% FCS , 2 mM glutamine , streptomycin ( 100 μg/ml ) , penicillin ( 100 U/ml ) , IL-2 ( 10 ng/ml ) ( Miltenyi Biotec ) and PHA ( 1 μg/ml ) ( Thermo Scientific ) . To determine the effect of Vpr on NF-κB activity , HEK293T cells were seeded in 96-well plates coated with poly-L-lysine and transfected in triplicates using a standard calcium phosphate transfection protocol [10] . COS-7 cells were seeded in non-coated 96-well plates and transfected using polyethylenimine ( PEI ) . Cells were cotransfected with a firefly luciferase reporter construct under the control of three NF-κB binding sites ( 100 ng ) , a Gaussia luciferase construct under the control of a constitutively active pTAL promoter ( 5 ng ) for normalization , and expression vectors for different Vpr proteins ( 100 ng ) or CH293 . 1 proviral constructs expressing heterologous Vpr proteins ( 100 ng ) . To determine the influence of DCAF1 on modulation of NF-κB activation by Vpr , DCAF1 was depleted by cotransfecting expression vectors for three different shRNAs ( 50 ng ) [57] . To activate NF-κB , Tetherin ( 40 ng ) , p65 ( 1 . 6 ng ) or a constitutively active mutant of IKKβ ( 40 ng ) was cotransfected or cells were stimulated with TNFα ( 20 ng/ml ) for 24 hr . 40 hr post-transfection , a dual luciferase assay was performed and the firefly luciferase signals were normalized to the corresponding Gaussia luciferase control values . To determine the effect of Vpr proteins on IFNβ-promoter activity , dual luciferase assays were performed as described above . Cells were transfected with firefly luciferase reporter constructs under the control of the wild type IFNβ-promoter ( 100 ng ) or a mutant thereof lacking the NF-κB binding site as previously described [6] . The promoter was activated by stimulation with Sendai virus for 24 hr . To determine the effect of Vpr proteins on LTR activity , reporter constructs were generated in which a firefly luciferase reporter gene is expressed under the control of the SIVcol CM243 , SIVolc 97CI12 and HIV-1 NL4-3 LTR , or mutants thereof with mutated NF-κB or Sp1 binding sites . HEK293T cells were cotransfected with these constructs ( 100 ng ) , expression vectors for different Vpr proteins ( 100 ng ) and Gaussia luciferase vectors under the control of a constitutively active pTAL promoter ( 5 ng ) for normalization . LTR-mediated transcription was activated by cotransfection of a constitutively active mutant of IKKβ ( 40 ng ) , Sp1 ( 40 ng ) or by stimulation with TNFα ( 20 ng/ml ) . 40 hr post-transfection , a dual luciferase assay was performed and the firefly luciferase signals were normalized to the corresponding Gaussia luciferase control values . To generate virus stocks , HEK293T cells were transfected in 6-well plates with proviral HIV-1 constructs ( 5 μg ) using a standard calcium phosphate transfection protocol [10] . For the production of VSV-G pseudotyped HIV-1 particles , the proviral constructs were cotransfected with expression plasmids for VSV-G ( 1 μg ) . For mock infection controls , HEK293T cells were treated with transfection reagents only . Supernatants were harvested 40 hr post-transfection . Infectious HIV-1 yield was determined by a 96-well infection assay using TZM-bl indicator cells . Briefly , 6 , 000 cells were seeded in 96-well plates and infected in triplicates with cell culture supernatants . Three days later , infection rates were measured using a galactosidase screen kit ( GalScreen-Applied Bioscience ) according to the manufacturer’s instructions . β-galactosidase activities were quantified as relative light units per second ( RLU/s ) using an Orion Microplate Luminometer . To show expression of functional Nef proteins , HEK293T cells were cotransfected in 6-well plates with increasing doses ( 0; 0 . 1; 0 . 5; 2 . 5 μg ) of SERINC5 expression vectors and HIV-1 NL4-3 proviral constructs expressing different Nef proteins ( 2 . 5 μg ) . 40 hr post-transfection , infectious virus yield was determined by infection of TZM-bl indicator cells for 72 hr in triplicates . To determine the effect of Vpr on the levels of IκBα and phosphorylation of p65 at Ser529 , HEK293T cells were transfected in 6-well plates with expression vectors for different Vpr proteins ( 2 . 5 μg ) coexpressing GFP via an IRES . 24 hours post-transfection cells were left untreated or stimulated with TNFα ( 10 ng/ml ) for 15 minutes at 37°C before fixation with 4% PFA for 10 minutes at 37°C . Cells were permeabilized with ice-cold methanol for 30 minutes on ice and washed twice before staining with AF647-coupled antibodies for IκBα ( BD #560817 ) or p65 phosphorylated at Ser529 ( BD #558422 ) or the respective isotype controls . For analysis , the APC signals of the isotype controls were subtracted and the APC signals of the GFP positive population of the TNFα-stimulated samples were normalized to the APC signals of the GFP positive population of the corresponding unstimulated controls . To determine the ability of human and simian Nef proteins to downmodulate human CD3 ( BD #555333 ) , CXCR4 ( BD #555974 ) or CD28 ( BD #559770 ) from the cell surface , PBMCs were transduced with VSV-G pseudotyped HIV-1 NL4-3 expressing different Nef proteins and coexpressing GFP via an IRES . Protein surface expression was determined 3 days post-transduction . To analyze the effects of Nef on human and colobus CD3 , HEK293T cells were cotransfected with proviral constructs for HIV-1 NL4-3 expressing different Nef proteins and coexpressing GFP via an IRES and constructs expressing fusion proteins between the cytoplasmic part of human or colobus CD3ζ and the extracellular part of CD8 . CD8 surface expression ( BD #555369 ) was determined 40 hr post-transfection . Infection rates of SupD1 cells or PBMCs were controlled by intracellular staining for p24 ( KC57-RD1; Beckman Coulter ) after fixation and permeabilization of the cells using the FIX&PERM kit ( Nordic MUbio ) according to the manufacturer’s instructions . Flow cytometric measurements were performed using a BD FACS Canto II flow cytometer . Jurkat cells were transduced with VSV-G pseudotyped HIV-1 CH293 . 1 expressing heterologous Vprs . After 48 hr , cells were fixed with 1% PFA for 20 min at RT and subsequently permeablized with 0 . 1% Triton to stain p24 ( KC57-FITC; Beckman Coulter ) for 45 min at 4°C . DNA staining was performed with propidium iodide ( 50 mg/ml ) and 100 μg/ml RNase in 0 . 1% Triton for 1 hr at RT before flow cytometric analysis to determine the effect of Vpr on cell cycle phases in infected ( p24+ ) cells . HEK293T cells were transfected with pCG vectors coexpressing Vpr and eGFP . Two days post transfection , cells were stained with Fixable Viability Stain ( FVS , BD #562247 ) and Annexin V ( AnnV; BD #550474 ) and analyzed by flow cytometry . Cells were categorized as FVS+/AnnV+ ( dead ) , FVS-/AnnV- ( live ) or FVS-/AnnV+ ( early apoptosis ) . To determine the effect of Vpr proteins on NF-κB activity , SupD1 cells were seeded in 96-well plates and transduced in triplicates with VSV-G pseudotyped HIV-1 CH293 . 1 expressing heterologous Vprs . Cells were harvested at various time points post-transduction to determine NF-κB-dependent firefly luciferase activity . Transduction efficiency was monitored by flow cytometry . To determine the effect of multiple rounds of infection on NF-κB activation , SupD1 cells were infected in the presence or absence of the protease inhibitor Darunavir ( 10 mM ) . NF-κB activation was measured at various time points post-transduction and supernatants were used to infect TZM-bl indicator cells to check whether Darunavir treatment was efficient . Cells were lysed in Western blot lysis buffer ( 150 mM NaCl , 50 mM HEPES , 5 mM EDTA , 0 . 1% NP40 , 500 μM Na3VO4 , 500 μM NaF , pH 7 . 5 ) . Cell-free virions were pelleted by centrifugation of cell culture supernatants through a 20% sucrose cushion at 20 , 800 g for 90 min at 4°C and lysed in Western blot lysis buffer . Lysates were mixed with Protein Sample Loading Buffer ( LI-COR ) supplemented with 10% β-mercaptoethanol , heated at 95°C for 5 min , separated on NuPAGE 4–12% Bis-Tris Gels ( Invitrogen ) and blotted onto Immobilon-FL PVDF membranes ( Merck Millipore ) . Proteins were stained using primary antibodies directed against HIV-1 Env ( obtained through the NIH AIDS Reagent Program , Division of AIDS , NIAID , NIH: 16H3 mAb from Drs . Barton F . Haynes and Hua-Xin Liao ) [58] , p24 ( Abcam #ab9071 ) , AU-1 ( Novus Biologicals #NB600-453 ) , β-actin ( Abcam #ab8226 ) , GAPDH ( BioLegend #631401 ) , GFP ( Abcam #ab290 ) , DCAF1 ( Proteintech #11612-1-AP ) and Infrared Dye labeled secondary antibodies ( LI-COR IRDye ) . Proteins were detected using an LI-COR Odyssey scanner and band intensities were quantified using LI-COR Image Studio Lite Version 3 . 1 . Total RNA was isolated and purified from transduced PBMCs using the RNeasy Plus Mini Kit ( QIAGEN ) and residual genomic DNA was removed using the DNA-free™ Kit ( Life Technologies #AM1906 ) . 150 ng of RNA were reversely transcribed using the PrimeScript RT reagent Kit ( TAKARA #RR037A ) with oligo dT and random hexamer primers . To control complete removal of genomic DNA , control samples without reverse transcriptase were included in the reaction . Generated cDNA was subjected to quantitative real time PCR using TaqMan primer/probe sets for human IFNB1 ( Thermo Fisher Scientific #Hs01077958_s1 ) , IFI44 ( Thermo Fisher Scientific #Hs00197427_m1 ) and GAPDH ( Thermo Fisher Scientific #4310884E ) as control . Ct data was processed relative to the GAPDH control . Statistical analyses were performed using GraphPad Prism 5 . 0 . Two-tailed , unpaired or paired student’s t-test and one sample t-test were used to determine statistically significant differences ( * p ≤ 0 . 05; ** p ≤ 0 . 01; *** p ≤ 0 . 001 ) . Correlation analyses were performed using Spearman’s non-parametric correlation test .
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The cellular transcription factor NF-κB plays a complex role in the lentiviral replication cycle . On the one hand , activation of NF-κB is required for efficient transcription of viral genes and reactivation of latent proviruses . On the other hand , NF-κB is also a key driver of antiviral gene expression , immune activation and progression to AIDS . As a result , primate lentiviruses tightly regulate the activation of NF-κB throughout their replication cycle to enable transcription of viral genes while minimizing antiviral gene expression . Here , we show that human and simian immunodeficiency viruses have evolved at least three alternative strategies to suppress NF-κB-dependent immune activation: HIV-2 and most SIVs prevent T cell activation via Nef-mediated downmodulation of CD3 . In comparison , HIV-1 and its vpu-containing SIV precursors inhibit NF-κB activation via their accessory protein Vpu and lost the CD3 downmodulation function of Nef . Finally , SIVcol and SIVolc , infecting mantled guerezas and olive colobus monkeys , respectively , utilize Vpr . Our findings emphasize the key role of NF-κB as inducer of antiretroviral immune responses and add to the accumulating evidence that lentiviral accessory proteins target innate signaling cascades by sophisticated mechanisms to evade restriction .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
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] |
2017
|
Primate lentiviruses use at least three alternative strategies to suppress NF-κB-mediated immune activation
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High capacity and low capacity running rats , HCR and LCR respectively , have been bred to represent two extremes of running endurance and have recently demonstrated disparities in fuel usage during transient aerobic exercise . HCR rats can maintain fatty acid ( FA ) utilization throughout the course of transient aerobic exercise whereas LCR rats rely predominantly on glucose utilization . We hypothesized that the difference between HCR and LCR fuel utilization could be explained by a difference in mitochondrial density . To test this hypothesis and to investigate mechanisms of fuel selection , we used a constraint-based kinetic analysis of whole-body metabolism to analyze transient exercise data from these rats . Our model analysis used a thermodynamically constrained kinetic framework that accounts for glycolysis , the TCA cycle , and mitochondrial FA transport and oxidation . The model can effectively match the observed relative rates of oxidation of glucose versus FA , as a function of ATP demand . In searching for the minimal differences required to explain metabolic function in HCR versus LCR rats , it was determined that the whole-body metabolic phenotype of LCR , compared to the HCR , could be explained by a ~50% reduction in total mitochondrial activity with an additional 5-fold reduction in mitochondrial FA transport activity . Finally , we postulate that over sustained periods of exercise that LCR can partly overcome the initial deficit in FA catabolic activity by upregulating FA transport and/or oxidation processes .
Fuel selection , the balancing of glucose , fatty acids , and amino acid utilization to match the ATP demand , is a hallmark of healthy metabolism [1] . It has been shown that endurance trained individuals can better maintain the oxidation of fatty acid ( FA ) throughout mild to moderate intensity exercise [2–4] . A number of studies have shown that exercise training increases skeletal muscle mitochondrial density [5–7] , intramuscular fat storage [8 , 9] , transport [10] , and oxidation [7 , 11] . These observations corroborate the idea that endurance athletes are better equipped to handle aerobic exercise because of their increased ability to utilize FA as a fuel source . However , FA utilization may not be as important , for instance with competitive endurance runners [12 , 13] , since their sustained exercise intensity typically exceeds 60% VO2max , a regime where most individuals have crossed over from dominant FA to carbohydrate utilization [14] . Thus , exercise fuel utilization depends on its intensity ( %VO2max ) . Normalizing for this produces similarities in fuel utilization even among various organisms [15–17] . Yet , there are many studies that have demonstrated differences between subjects , namely exercise trained and untrained individuals [2 , 3 , 18 , 19] , even when accounting for normalization ( %VO2max ) . A popular mechanistic view of fuel selection centers on the Randle cycle [20 , 21] , which explains the preference for FA by the inhibition of the pyruvate dehydrogenase complex , an enzyme at the interface of glycolysis and the TCA cycle and a gate keeper for aerobic glucose oxidation . Extensions [20] to the Randle cycle have been proposed , such as the inhibition of carnitine palmitoyltransferase-1 by malonyl-CoA [22] , to explain how glucose oxidation inhibits fatty acid oxidation ( FAO ) . Although the Randle cycle is proposed to describe the reciprocal relationship between glucose and FAO [23] , it has been shown to be too simple to explain the etiology of type 2 diabetes [24 , 25] and fuel selection in exercise [17 , 26 , 27] . High and low capacity running rats [28] , ( HCR and LCR ) are genetically outbred rats that have been bred to model extreme genotypes and phenotypes with regard to exercise performance . The main difference in exercise ability between these rats lies in skeletal muscle [29] substrate selection between glucose and FA metabolism [30] . Recently , it has been shown that HCR can effectively utilize FA during graded treadmill exercise , where LCR largely lack this ability [30] . To explore this phenomenon , we have developed a computer model of whole-body central metabolism that accounts for mass balance and thermodynamic constraints to simulate fuel selection during exercise . Our model explicitly accounts for all the reactions in glycolysis , the TCA cycle , the mitochondrial electron transport chain , as well as FA transport and beta-oxidation reactions ( Fig 1 ) . Overall , the model includes 98 metabolites and 87 reactions ( Fig 1 ) , and has been parameterized with HCR and LCR respiration , plasma lactate , and muscle acyl-carnitine concentrations as a function of exercise [30] . Our primary objective was to find the minimal difference between HCR and LCR enzymatic activities required to simulate the apparent fuel selection difference between these animals [30] . Our results show that by minimally decreasing total HCR mitochondrial activity by 30–50% and by further reducing mitochondrial FA transport , we can match the LCR’s attenuated FA utilization activity during transient aerobic exercise . However , when these data are normalized with %VO2max and compared with steady-state data at 75% VO2max there is a major difference in respiratory exchange quotients between LCR transient and steady-state data for the LCR , but not for the HCR . We found that this difference may be explained , by the model , if FA transport and oxidative capacity are much more slowly mobilized upon exercise in the LCR compared to the HCR .
HCR and LCR metabolic data were obtained , during a graded treadmill experiment , from a previous publication [30] . In these experiments , HCR ( n = 23 ) and LCR rats ( n = 16 ) were ran on a treadmill with speed increasing every 2 minutes until exhaustion . HCR and LCR rats exhausted , on average , at about 50 and 14 minutes , respectively [30] . During the exercise regimen , O2 uptake , CO2 output , as well as carbohydrate and FA utilization were estimated [30] . Blood plasma was also sampled for glucose , FA , and lactate [30] . Additionally , gastrocnemius muscle biopsies were taken at 0 and 10 minutes , for both HCR and LCR , and at 45 minutes for HCR only [30] . Muscle biopsies and blood plasma were analyzed by metabolomics and proteomic methods [30] . HCR and LCR O2 and CO2 flux data ( Fig 2A and 2B ) , and carbohydrate and FA flux data ( Fig 2C and 2D ) , estimated from indirect calorimetry , were previously collected [30] during a graded treadmill exercise protocol ( described above ) . These data ( Fig 2 ) were used as transport flux inputs for a constraint-based [31 , 32] calculation to compute all 87 internal reaction fluxes of the metabolic system shown in Fig 1 for HCR and LCR data ( reactions shown in S1 Table ) . Transport fluxes ( Fig 2 ) at each time point for HCR and LCR were used to solve for internal fluxes ( J¯ ) ( Eq 1 , Methods ) , while maximizing mitochondrial ATP production as an objective function and applying ab initio thermodynamic cycle constraints for the network [33] . Initial FA , was simplified to be only palmitate ( C16 acyl chain length ) , and glucose was the only carbohydrate considered . The computed 87 internal reaction fluxes , with time , are shown for HCR ( Fig 3A ) and LCR ( Fig 3B ) . The reaction fluxes are annotated by an enzyme identifier ( Shown in S1 Table ) , and grouped by major pathways shown in Fig 1 . The constraint-based solution demonstrates the incline of metabolic flux with exercise for HCR ( Fig 3A ) and LCR ( Fig 3B ) , most consistently through the TCA cycle , glycolytic pathway , and bioenergetic reactions . The solution also demonstrates the attenuated flux through the FAO pathway for LCR ( inset Fig 3B ) relative to HCR ( inset Fig 3A ) . The constraint-based solution is a first approximation ( quasi-steady state ) that allows an estimation of internal fluxes and a starting point for parameterization of a kinetic modelling approach . The fluxes represent whole-body rates , measured in units of moles per unit time per body weight . The ATPase rate was used from this constraint-based solution at each time point ( Fig 3C ) to simulate the work load , or ATP demand , in HCR and LCR in the subsequently described kinetic model . To test the stability of the HCR and LCR solutions ( Fig 3 ) , we determined how uncertainty in the measured boundary fluxes translates into uncertainty in the estimated fluxes . Results from these analyses are summarized in S1–S3 Figs . The maximum and minimum solutions for HCR ( S1 Fig ) and LCR ( S2 Fig ) , at each time point , differ by only a small margin . A kinetic model for simulating HCR and LCR fuel selection was initially identified using fluxes from the constraint-based solution ( Fig 3 ) and using Eq 4 ( Methods ) to assign value for the enzyme activities ( X ) . Furthermore , ATP demand was simulated based on the interpolated rate from the constraint-based solution ( Fig 3C ) . Initial concentrations for 98 metabolites were obtained by a Monte Carlo method that randomly searched for a concentration vector satisfying the thermodynamic constraint of Eq 2 ( Methods ) . The directions of the fluxes in Eq 2 ( Methods ) were determined from the constraint-based solution at rest ( time = 0 ) . Reasonable concentration bounds determined from the literature were imposed on the Monte Carlo search ( Reported in S2 Table as lower ( LB ) and upper bounds ( UB ) ) . Finally , the activities were adjusted to fit the HCR data in Fig 4 , as described below . The initial concentration vector used to simulate the data in Fig 4 is reported in S2 Table . HCR CO2 ( Fig 4A ) and O2 ( Fig 4B ) fluxes ( JCO2 and JO2 ) , plasma lactate ( Fig 4C ) , respiratory quotient ( RQ; Fig 4D ) , and muscle acyl-carnitine profiles ( Fig 4E–4J ) ( all data derived from [30] ) were used to parameterize the model by least-squares minimization . With a total of 86 adjustable parameters , the solution illustrated in Fig 4 is not unique . Uncertainty of parameter values and their predictions were assessed below . After fitting the HCR data ( Fig 4; blue ) , we tested the hypothesis ( Hypothesis 1 ) that the metabolic data can be simulated by invoking only a difference in mitochondrial density between HCR and LCR ( Fig 4; red dash-dot lines ) . This hypothesis is derived from the observations that trained individuals have a higher proportion of mitochondria per muscle mass than untrained individuals , and this difference has been observed in both HCR and LCR rats [6 , 34] . Simulation of hypothesis 1 significantly deviated from the RQ data , where the error between the model and the data were quantitated by the sum of squared error function values defined in Eq 7 ( Fig 4D; red dash-dot lines; error function value = 2 . 89 ) . Thus , decreasing total HCR mitochondrial activity only ( optimal near a 50% decrease ) could not sufficiently switch HCR to utilize glucose in an aerobic manner , as demonstrated by LCR data ( Fig 4D; red dash-dot lines ) . However , this hypothesis does cause the model to switch to utilize glucose in an anaerobic manner ( Fig 4C; red dash-dot lines ) . Decreasing total HCR mitochondrial activity beyond 50% did not improve fitting to the LCR data . Second , we tested the hypothesis that HCR and LCR only differ in total FA utilization ( Fig 4; dashed lines ) . We found that this hypothesis ( Hypothesis 2 ) was also somewhat inconsistent with the data ( error function value = 4 . 03 ) . Decreasing only FAO enzyme activities ( optimal decrease around 10-fold ) matches the RQ data for LCR ( Fig 4D; dashed lines ) better than hypothesis 1 , indicative of increasing the aerobic oxidation of glucose . But decreasing FAO enzymes only was unable to match the observed increase in anaerobic glucose utilization ( Fig 4C; dashed lines ) and acetyl-carnitine concentrations with exercise ( Fig 4I; dashed lines ) . These observations led us to alter both total mitochondrial enzyme and FAO activities to achieve a minimal difference between HCR and LCR enzyme activities ( Fig 4; solid lines; error function value = 2 . 68 ) . By minimal , we are referring to the minimal number of enzyme activity differences between model parameterizations representing the LCR versus the HCR data . To be clear , when both mitochondrial enzyme activities and FAO enzyme activities were decreased this means that after applying , for example , a 50% decrease in all mitochondrial enzymes an additional decrease in FAO enzyme activities was applied to help fit the LCR data . This additional difference , between FAO enzymes and all other mitochondrial enzymes , can be seen in Fig 5 , which is discussed below . We found that decreasing FA transport enzyme activities was the most effective way to switch fuel usage from a more FAO dominant mode to a more glucose oxidative mode . Decreasing total mitochondrial enzyme activity between 30% and 50% was also required to best-fit the data . The predicted ratios of HCR and LCR enzyme activities ( XHCR/XLCR ) are shown in Fig 5 for the minimal best-fit parameter set of the LCR data ( Fig 4; red solid lines ) . The minimal best-fit parameter set for LCR has decreased all mitochondrial enzyme activities by 50% and additionally decreased several FAO related enzyme activities relative to HCR . The model was used to probe dynamic variables during exercise that are difficult to measure ( Fig 6 ) . The model demonstrates constant cytosolic ATP ( Fig 6A; blue ) and decreasing ( more positive ) cytosolic ATP potential ( Fig 6B ) , consistent with previous in vivo measurements during prolonged exercise [35] . Interestingly , the model simulation for LCR eventually fails because it is unable to meet the ATP demand ( Fig 6A; red ) . However , this phenomenon occurs long after LCR have exhausted in the experimental data ( Fig 4 ) . The model demonstrates LCR’s increased flux through aerobic glucose oxidation ( Fig 6D and 6E ) and anaerobic or glycolytic flux ( Fig 6F ) , but has reduced FAO ( Fig 6N ) flux compared to HCR . The model also demonstrates that as work increases the NAD pool becomes more reduced ( Fig 6C ) in the cytosolic fraction whereas the converse occurs in the mitochondrial fraction ( Fig 6K ) . The model predicts LCR is eventually unable to maintain the mitochondrial membrane potential ( Fig 6J ) due to the failure of aerobic glucose oxidation . One of the earliest indicators of failure in LCR is the drop in the acetyl-CoA/CoA ratio ( Fig 6L ) , where acetyl-CoA decreases and CoA increases . The cause for the eventual crashing is that the cytosolic NAD pool becomes overly reduced ( Fig 6C ) slowing down glycolysis ( Fig 6D ) , subsequent production of pyruvate ( Fig 6H and 6I ) , and acetyl-CoA feeding into the TCA cycle ( Fig 6M ) . This leads to decreased mitochondrial ATP output ( Fig 6O ) , which is unable to meet the ATP demand ( Fig 6A ) . Although β-oxidation decreases ( Fig 6N ) at about 35 minutes in the simulation it does not crash like glycolysis . These simulation results are generally consistent when using other enzyme activities that also fit the data , discussed below . Predicted metabolite concentrations for HCR and LCR are available in S3 and S4 Tables for HCR and LCR , respectively . These predicted metabolite concentrations were generated based on the activities used to produce Fig 6 . Ratios of the simulated metabolite concentrations as a function of time , and exercise , demonstrate further predicted differences ( S3 and S4 Figs ) between HCR and LCR . These figures predict higher concentrations of initial FAO substrates for HCR ( S3 Fig ) compared to LCR , whereas LCR has accumulated more FAO end products ( S4 Fig ) . This figure also demonstrates the model prediction that HCR will accumulate AMP and PPi ( S4A Fig ) , a consequence of HCR’s relative increased FAO flux compared to LCR . To evaluate the robustness of our results , we obtained an ensemble of independent parameter sets capable of fitting the data . To achieve this , we randomly perturbed the parameters from an initial fit to the HCR data ( Fig 4; blue ) and fed them into a simulated annealing algorithm followed by a local optimization algorithm . By this strategy , we obtained 10 different fits to the HCR data ( Fig 7; blue ) . Each of these HCR parameter sets were then used to obtain 10 minimal fits to LCR data by only changing total mitochondrial activities and the select activities shown in Fig 5 . The minimal changes made to these HCR parameter sets to fit LCR data are all similar to those shown in Fig 5 . HCR parameters were also used as initial starting points to find 10 non-minimal fits to the LCR data ( Fig 7; red ) . That is , we allowed all parameters to vary independently to match the LCR data . Like the minimal best-fit LCR simulation in Fig 4 , we observed that 7 out of these 10 LCR simulations eventually failed because they were unable to meet the ATP demand by relying on mostly glucose oxidation for an extended period of exercise . The difference , however , between the parameter sets used to simulate the LCR data in Fig 4 and in Fig 7 , is that the latter parameter sets were generated by allowing all enzyme activities to change to fit the LCR data . In other words , the LCR enzyme activities used to simulate LCR in Fig 7 do not reflect a minimal difference relative to HCR enzyme activities . To obtain a distribution of activity ratios ( XHCR/XLCR ) , such as that shown in Fig 5 for a minimal difference , we randomly perturbed each of the 10 parameter sets for HCR ( Fig 7; blue ) and LCR ( Fig 7; red ) until we obtained 103 parameter sets capable of fitting each data set . We then took the ratio of all possible combinations of parameter sets between HCR and LCR yielding 106 ratios ( Fig 8 ) for each enzyme activity . This demonstrates that the main difference between HCR and LCR enzyme activities lies in mitochondrial acyl-CoA/acyl-carnitine transport . The widest range in parameter differences between HCR and LCR is in the palmitoyl-CoA translocase ( PCT ) and carnitine palmitoyltransferase-2 ( CPT2 ) activities . However , the output of the model is not particularly sensitive to these activities . Although a number of enzyme activities ( model adjustable parameters ) tend to fall within a relatively small range ( Fig 8 ) to fit the data ( Fig 7 ) this does not mean that we have identified absolute enzyme activities because of the correlations that exist in parameter space and because of the simplified nature of the kinetic model . Thus , one should not assign strict value to these enzyme activities , but understand that simulating LCR data from a HCR model starting point can generally be achieved by minimally altering FAO and FA transport enzyme activities with some additional decrease in total mitochondrial enzyme activity . In order to determine what enzyme activities are most important to fuel selection in exercise , we calculated sensitivity coefficients for each of the enzyme activities for HCR and LCR for all 103 parameter sets with respect to the simulation of the respiratory quotient ( JCO2/JO2 ) . The respiratory quotient is typically considered to be a good indicator of fuel selection based on stoichiometric utilization of O2 and production of CO2 for different substrates . The results of this calculation yielding 103 sensitivity coefficients for HCR ( Fig 9 ) and LCR ( Fig 10 ) are displayed in histograms and ordered by high to low sensitivity in the figure . This calculation revealed carnitine palmitoyltransferase-1 ( CPT1 ) activity to be the most sensitive with HCR ( Fig 9 ) , while lactate transport ( LACT ) was the most sensitive with LCR ( Fig 10 ) . Exercise fuel selection in HCR and LCR were also both highly sensitive to glucose transport ( GLUT ) , hexokinase ( HK ) , and the combination of complex 3 and 4 ( Complex 3+4 ) activity ( Figs 9 and 10 ) . The main difference between HCR and LCR with respect to fuel selection enzyme sensitivity was with FA utilization enzymes , such that HCR was sensitive to these activities and LCR was not ( Figs 9 and 10 ) . Thus , HCR is predicted to have more control of FA utilization relative to LCR , FA transport in particular . To help combine the information collected by computing numerous enzyme activity ratios ( Fig 8 ) and sensitivity coefficients ( Figs 9 and 10 ) , we used a simple expression ( Eq 6 , Methods ) to calculate a median score for the relative importance of each enzyme activity ( Fig 11 ) . The purpose of this score was to assess the major differences between HCR and LCR enzyme exercise activities regarding fuel selection , while also accounting for their sensitivity . This calculation is based on the non-minimal fitting of LCR data ( Fig 7 ) . The enzyme score calculation reveals higher importance for glycolytic enzymes for LCR and FA catabolic enzymes for HCR , although our minimal approach to fitting LCR data ( Fig 4 ) showed that glycolytic enzyme activities do not have to change ( Fig 5 ) to fit this data . Interestingly , the importance of CPT1 and ACAD4 was also revealed in this calculation , which agrees with conclusions drawn from the minimal approach to fitting LCR data ( compare Fig 5 and Fig 11 ) .
HCR and LCR rats are models of two extremes of exercise aerobic capacity that differ primarily in skeletal muscle [29] fuel selection [30] and also demonstrate different susceptibilities to insulin resistance [36 , 37] . Therefore , HCR and LCR rats provide an interesting means to study skeletal muscle metabolic remodeling , regarding fuel selection in exercise endurance , capacity , and metabolic disease . Our main objective was to identify the minimal difference in enzyme activities between HCR and LCR rats , as they were subjected to graded treadmill exercise , to understand how HCR rats better sustain aerobic exercise compared to LCR rats . To accomplish this , we constructed a thermodynamically constrained model combining constraint-based analysis and ordinary differential equation modeling . We hypothesized that the model would show that LCR only differ from HCR by a moderate decrease in mitochondrial density ( total mitochondrial activity ) . We also asked the question if a model completely based on mass-action kinetics and thermodynamic constraints , lacking detailed enzyme kinetic modeling , could still reproduce fuel switching dependent on ATP demand . Constraint-based modeling , rooted in flux balance analysis [38] , was first used to estimate the metabolic fluxes of a model explicitly accounting for glycolysis , the TCA cycle , mitochondrial electron transport reactions , and mitochondrial FA transport and β-oxidation ( Figs 1 and 3 ) during HCR and LCR aerobic exercise ( Fig 2 ) . The estimation of these metabolic fluxes ( Fig 3 ) allowed us to then estimate individual enzyme activities based on a simple generalized enzyme flux expression ( Eq 3 , Methods ) and simulate the time-dependent data ( Fig 4 ) in a minimal way . Our analysis revealed that to explain the minimal difference between HCR and LCR data , we needed to decrease both total mitochondrial enzyme activities ( ~50% ) with , at least , an additional decrease in mitochondrial FA transport and oxidative activities ( about an additional 5-fold decrease ) ( Fig 5 ) . It has been previously shown that LCR have similar mitochondrial density in red gastrocnemius muscle [34 , 37] , but are reduced in white [34] , which corroborates the idea that LCR aerobic exercise capacity could be simply attenuated by a decrease in mitochondrial density . However , HCR and LCR muscle proteomic data during exercise [30] suggested additional differences . These experiments demonstrated significantly greater acetylation/phosphorylation of LCR FA transport and β-oxidative enzymes , among others , with respect to HCR during exercise [30] . These increases in posttranslational modification ( PTM ) are believed to decrease enzyme activities and hinder FA catabolism . Furthermore , HCR have also been shown to be enriched in oxidative phosphorylation and FA metabolism proteins [30 , 37] , thus enzyme expression levels also appear to be a factor . Our model does not distinguish between enzyme activity effects induced by PTM or expression levels , however , it does support the need to invoke combined changes in both total mitochondrial activity ( mitochondrial density ) and a specific decrease in FA transport . Additional decreases in FA β-oxidation enzyme activities ( Fig 5 ) were also invoked to better simulate LCR data , which are also supported by proteomics data [30] . According to model sensitivity analysis , enzymatic control over fuel selection during exercise differs between HCR and LCR due to HCR’s increased control over FA transport enzymes such as CPT1 and FAT ( CD36 ) ( Figs 9 and 10 ) . Our model is simplified in that it does not account for amino acid catabolism , although amino acid data were provided in the data set we analyzed [30] . This simplification is justified by our goal to gain insight into glucose and FA catabolism , which account for the bulk of the energy demand ( 85–90% [39] ) . However , the addition of amino acid catabolism could provide additional insight . Despite the need to decrease HCR FA enzyme activities to simulate LCR data , it is important to understand that these data ( Fig 4 ) were collected during a transient catabolic state . When these data are normalized for exercise intensity ( %VO2max ) and compared to steady-state data at 75% VO2max ( Fig 13A ) there is a discrepancy between the LCR transient and steady-state data . The steady-state respiratory quotients at 75% VO2max are similar between HCR and LCR ( Fig 13A ) . Thus , it appears that the difference between LCR and HCR FAO diminishes with sustained normalized exercise intensity ( Fig 13 ) . This result suggests that LCR may transition from attenuated fat catabolism during transient intense exercise to a more active fat catabolism when allowed longer time periods to acclimate to the exercise intensity . The transition between initial and steady-state activities may be achieved by PTM , as previously proposed [30] . Furthermore , the model also leads to the conclusion that FA transport is critical for fuel selection , recently demonstrated with CD36 KO and overexpression mice [27 , 40] . Finally , it is interesting that the simple kinetic model developed here , for the HCR rat , can switch between FA and carbohydrate substrates in a physiological manner , as demonstrated by simulating the metabolic response to exercise . The model does not include allostery , such as required for the Randle cycle [20 , 21] or calcium mediated activation of mitochondrial dehydrogenases . The model does not necessarily exclude these mechanisms as contributors to fuel selection in vivo , but does show that simple kinetic modeling can effectively capture this phenomenon without involving these regulatory processes .
The computer model was initialized by building a stoichiometric matrix S ( 98 reactants by 87 reactions; Eq 1 ) accounting for all of the reactions shown in Fig 1 , using previously developed computer code [32] . A full list of the reactions and their definitions can be found in S1 Table . As a first approximation of internal reaction fluxes , a steady-state approximation was implemented ( Eq 1 ) . In Eq 1 , ( S ) is the stoichiometric matrix and ( J¯ ) is a vector of fluxes for each of the 87 reactions plus 6 transport fluxes . The transport fluxes are defined by the input of glucose , FA , O2 , and the output of lactate , CO2 , and H2O . Transport fluxes were determined using respiration and indirect calorimetry data shown in Fig 2 from HCR and LCR rats during a graded treadmill running exercise protocol [30] . Eq 1 was solved for ( J¯ ) using the FMINCON function in MATLAB 2016a , by applying ab initio thermodynamic cycle constraints [33] , and maximizing mitochondrial ATP production as an objective function for each time point shown in Fig 2 . Fig 3 shows an interpolated surface of the combined solutions of Eq 1 for HCR ( Fig 3A ) and LCR ( Fig 3B ) using the data in Fig 2 as transport fluxes at each time point . To obtain a thermodynamically feasible concentration vector needed to simulate the metabolic network ( Fig 1 ) , we first collected a standard transformed Gibbs free energy vector ( ΔG′0¯ ) for the 87 reactions in the network at 25°C and pH 7 . Therefore , all reactions treat pH as a fixed entity throughout the course of the simulations . ΔG′0¯ was obtained primarily from the Goldberg [41] , Li [42] , and Alberty [43] databases , or calculated using the Equilibrator [44] server . ΔG′0¯ values can be found in S1 Table . A Monte Carlo method was applied to randomly choose metabolite concentrations that were consistent with literature concentration boundaries and satisfied Eq 2 ( An expression of the 2nd law of thermodynamics discussed in [45] ) , where R is the gas constant , T is absolute temperature , and Q¯ is the mass action ratio vector . The resulting concentration vector was slightly adjusted to match the data shown in Fig 4 for HCR and LCR . The final concentration vectors used to simulate HCR and LCR can be found in S2 Table . The model was simulated by solving the ordinary differential equation system in Eq 3 , where ( C ) is the concentration vector , ( P ) is a partition matrix , ( S ) is the stoichiometric matrix , and ( Jcalc ) is the calculated reaction flux vector . The partition matrix is a diagonal matrix that compartmentalizes the system into extracellular , cytosolic , and mitochondrial spaces with partition coefficients of 0 . 2 , 0 . 75 , and 0 . 05 , respectively , based on the fractional volume of skeletal muscle [46] . Here we have used skeletal muscle tissue spaces because this tissue type represents the dominant tissue for whole body metabolism during exercise . To account for the water volume of skeletal muscle , we used a value of 755 mL water per kg of muscle mass [46] . Reaction fluxes ( Jcalck ) for each kth reaction were calculated via a general flux expression ( Eq 4 ) derived previously [32] . In Eq 4 , ( X ) is the enzyme activity and ( Ct ) is a concentration dependent term where μ and ν are the stoichiometry’s of the substrates and the products of reaction k , respectively . The Ct term is unitless due to individual terms being divided by the reference state of 1 M . The rate of ATP hydrolysis , required for work , throughout the exercise protocol was estimated by using the ATPase flux ( Fig 3C ) determined from the constraint-based solution for HCR . These determined fluxes were then fitted to a polynomial to estimate the ATPase rate at any time . This ATPase rate was then used as an input to drive the system and simulate work . Model simulations were conducted using ode15s in MATLAB 2016a with an absolute tolerance of 10−12 and relative tolerance of 10−10 , with the non-negative option on . Enzyme activities ( X in Eq 4 ) were treated as constants throughout the course of the simulations for transient exercise data shown in Figs 4 and 7 . However , long-term simulations , such as those shown in Fig 13 , required transitioning the activities from resting activities ( Xrest ) to exercise activities ( Xexercise ) . Activities were transitioned as a function of %VO2max using a general monoexponential equation ( Eq 5 ) with a transition constant ( Tc ) . X ( %VO2max ) =Xexercise+ ( Xrest−Xexercise ) e− ( %VO2max−%VO2rest ) Tc ( 5 ) Fuel utilization percentages , as shown in Fig 13D–13F , were calculated as follows: % FA utilization = ( 1-RQ ) / ( 1–0 . 7 ) ; carbohydrate utilization = 100-% FA utilization; where RQ is the calculated respiratory quotient . Exercise enzyme activity parameters ( Xexercise ) from 103 parameter sets that were fitted to HCR and LCR data , and their corresponding sensitivity coefficients ( ϕ ) , were used to calculate a normalized enzyme activity score to assess the greatest differences in enzyme activity while accounting for their sensitivity . Enzyme activities ( X in Eq 4 ) were treated as adjustable parameters when trying to fit the HCR data ( blue ) in Fig 4 . Initial guesses for these activities were derived by solving for them algebraically by setting Eq 4 equal to fluxes from the constraint-based solution and plugging in the initial concentration vector . Simulations utilizing enzyme activities ( X in Eq 4 ) derived using the initial resting fluxes from the constraint-based solution tended to fail prematurely at higher ATPase rates because these activities were too low . We arbitrarily increased enzyme activities to allow the simulations to withstand higher ATPase rates . From here , to fit HCR data , enzyme activities were adjusted to minimize the difference between the HCR data ( Fig 4 , blue ) and the simulation using simulated annealing and Monte Carlo approaches , along with the FMINCON function in MATLAB 2016a . Error function values reported in the text were computed using Eq 7 . LCR parameters were obtained either by minimally changing HCR parameters ( individual enzyme activities ) to fit LCR data ( Fig 4; red ) , or by allowing all enzyme activities to change to fit the LCR data ( Fig 7; red ) . Total mitochondrial activity was adjusted from HCR to LCR by a multiplicative factor . For example , a 30% decrease in mitochondrial activity from HCR to LCR was defined as: XLCR ( mito ) = XHCR ( mito ) * ( 1–0 . 3 ) . Further decreases in HCR activities , to achieve fitness to the LCR data , were explored by randomly adjusting different enzyme activities starting from small differences ( Figs 4 and 5 ) with the goal of adjusting a minimal number of enzyme activity differences between model parameterizations representing the LCR versus the HCR data . With this minimal fitting approach , 10 LCR activity parameter sets were obtained starting from 10 HCR activity parameter sets . Additionally , a non-minimal approach to fitting LCR data ( Fig 7; red ) was implemented that allowed for all enzyme activities to change relative to HCR . This approach applied both global and local optimization methods to achieve fitness .
|
Our bodies consume carbohydrates , fats , and amino acids as fuels , utilizing various catabolic pathways to transfer the energy required for normal physiological functions . The way these pathways function can have an important impact on overall health . While most catabolic pathways are known , we are still striving to understand how these pathways interact , are controlled , and change during exercise and in disease . Here , we have used computer modeling as a tool to understand fuel utilization differences during exercise for two animal models . High capacity running rats ( HCR ) were used as a healthy , fit cohort , and low capacity running rats ( LCR ) were used as a sedentary and disease-prone cohort . Our computer model results show that the HCRs are superior at fat utilization compared to LCRs because of their increased ability to transport and catabolize fatty acids . We postulate that these differences depend on exercise intensity and duration , such that longer acclimation periods may minimize fuel utilization differences between these rats .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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"enzymology",
"carbohydrates",
"physical",
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"oxidation",
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] |
2018
|
Systems-level computational modeling demonstrates fuel selection switching in high capacity running and low capacity running rats
|
For many pathogens , including most targets of effective vaccines , infection elicits an immune response that confers significant protection against reinfection . There has been significant debate as to whether natural Mycobacterium tuberculosis ( Mtb ) infection confers protection against reinfection . Here we experimentally assessed the protection conferred by concurrent Mtb infection in macaques , a robust experimental model of human tuberculosis ( TB ) , using a combination of serial imaging and Mtb challenge strains differentiated by DNA identifiers . Strikingly , ongoing Mtb infection provided complete protection against establishment of secondary infection in over half of the macaques and allowed near sterilizing bacterial control for those in which a secondary infection was established . By contrast , boosted BCG vaccination reduced granuloma inflammation but had no impact on early granuloma bacterial burden . These findings are evidence of highly effective concomitant mycobacterial immunity in the lung , which may inform TB vaccine design and development .
There has been significant debate as to whether natural Mtb infection confers protection against reinfection . Epidemiologic studies from the pre-antibiotic era suggest that primary Mycobacterium tuberculosis ( Mtb ) infection provides up to 80% protection against TB disease due to secondary exposure[1] , although assessing protection against actual reinfection is not possible . However , up to ~20% of patients who complete drug treatment develop TB again , in part due to reinfection[2–6] . Recent studies also suggest that mixed infections ( two or more Mtb isolates ) are detectable in 2–18% of individuals with active TB[4 , 7 , 8] , although some of these studies are in HIV+ individuals . In mice , ongoing or treated Mtb infections only reduce bacterial burdens in the lung by ~10-fold , roughly equivalent to BCG vaccination[9 , 10] . These data are often used to inform the field’s understanding of the extent of protection that a primed immune response can provide against Mtb infection , which is a critical question for vaccine development . However , these conclusions are confounded by uncertainties regarding host immune status and prior exposure in the human studies , outcome measures of disease rather than establishment of a secondary infection , and the relevance of the small animal models to human infection . Here , we sought to quantitatively assess the effect of a concurrent Mtb infection on rechallenge in the cynomolgus macaque model[11–13] , which recapitulates nearly all aspects of human Mtb infection . To probe the dynamics of reinfection , we used serial [18F]-fluorodeoxyglucose ( FDG ) -PET-CT imaging to track timing of granuloma formation following secondary exposure[14–16] , which allowed all granulomas to be retrieved at necropsy . The outcomes of primary and secondary challenges were defined with Mtb libraries marked with unique DNA identifiers that were tracked by sequencing and/or a custom direct hybridization ( NanoString ) assay[14 , 17 , 18] . Our findings indicate that primary ongoing infection provides robust protection against infection upon secondary exposure to Mtb .
Eight cynomolgus macaques received a primary challenge with Mtb Erdman library A ( <15 CFU ) ( Fig 1A ) . As expected based on our published work[12 , 13 , 19] , this infection resulted in a range of outcomes by 16 weeks as assessed by PET-CT[13] , from minimal to progressive disease ( Fig 1B and S1 Table ) . Sixteen weeks after primary infection , animals were rechallenged with Mtb Erdman library B ( <15 CFU ) . Six naïve control animals were challenged with library B in parallel ( Fig 1A ) . Granuloma formation after library B challenge was tracked for ~4 weeks by PET-CT imaging ( S1 Table ) ( Fig 1C ) . The number of granulomas detectable by PET-CT imaging at 4 weeks post-infection in naïve animals is one correlate of the number of bacteria that successfully establish infection[14 , 15] . Individual granulomas and lymph nodes were obtained at necropsy ( 4 weeks post-library B ) for bacterial and immunologic analyses . At this time point , which is just prior to the onset of adaptive immunity in naïve animals , granuloma bacterial burdens are relatively uniform and at their highest levels with minimal bacterial killing in naïve animals [14 , 20] , [21] . Thus , comparing granulomas at 4 weeks post-library B in naïve and reinfected animals allows a direct comparison of early bacterial control . Using PET-CT to identify formation of new granulomas , there was no aggregate difference between new granuloma formation after library B challenge in the presence or absence of ongoing infection ( S1A Fig ) . However , this metric alone cannot distinguish new granuloma formation due to library B challenge from granulomas formed by ongoing dissemination from sites of primary infection ( library A ) . Indeed , three animals had apparent dissemination just prior to or during secondary infection , based on imaging ( monkey IDs: 19415 , 19515 , 19615 ) . Moreover , imaging alone fails to capture the potential for library B seeding sites of existing infection as described in fish , frogs , and mice[22 , 23] . Therefore , we deconvoluted the identity of library tags in granulomas formed after primary and secondary infections . Tags were identifiable both from bacteria cultured from granulomas and , in most cases , from tissue homogenates including the homogenates of sterile lesions . As expected , DNA tags from sampled granulomas in naïve animals mapped entirely to library B ( Fig 1D and S2 Table ) . In animals challenged during ongoing primary infection , there was no significant difference in total number of granulomas containing library B as compared to naïve animals ( p = 0 . 1525 ) ( S1B Fig ) . Nine granulomas ( of 95 total analyzed ) from reinfected monkeys contained both library A and library B DNA ( S2 Table ) , suggesting that occasionally library B seeded pre-existing sites of infection . However , concurrent infection did reduce the formation of new granulomas attributable only to library B ( Fig 1D , p = 0 . 0083 ) . The number of granulomas attributable only to library B at 4 weeks was also significantly lower than the number of granulomas established by library A granulomas at 4 weeks ( as determined by PET CT ) in the same animals ( p = 0 . 0156 , S1C Fig ) . Indeed , there was complete protection in one animal with no detectable library B DNA in any tissues ( monkey ID: 19815 ) ( Figs 1D and S1A and S1B ) . To assess growth of the secondary challenge strain , we evaluated the bacterial burdens of individual granulomas in both cohorts and used the library tags to attribute these bacterial loads to library A and/or library B ( Fig 2A ) . In naïve animals , the distribution of granuloma bacterial burdens ( library B ) was consistent with our previous studies[14] with a median bacterial load of 8300 and few sterile granulomas . By contrast , most granulomas from reinfected animals had lower bacterial loads than in naïve animals , with many sterile granulomas ( Fig 2A , p<0 . 0001 ) . Strikingly , in concurrently infected animals , the few library B granulomas that did form had markedly lower bacterial burdens than in naïve macaques where these granulomas were assessed at the same time post-library B infection ( Figs 2A and 3C ) . In addition to the one animal that had no library B DNA ( monkey ID: 19815 ) , four animals had no viable library B bacteria; in these animals library B DNA tags were only found in homogenates of sterile granulomas ( S3 Table ) . Only 1 of the 9 granulomas with both library A and B DNA tags grew library B bacteria . Thus , primary infection fully protected 5 out of 8 animals against productive ( CFU+ ) infection with the challenge strain ( Fig 2A ) . Collectively , these data suggest that primary Mtb infection initiates an immune response which leads to rapid neutralization of the challenge strain . Note that the bacterial loads in granulomas containing library A , delivered 20 weeks prior to necropsy , were also lower than library B granulomas from naïve animals analyzed ~4 weeks post infection . However , this decrease in bacterial load over time is consistent with our previously published studies[14] and data from historical macaques infected with Mtb Erdman ( S2 Fig ) , where CFU/granuloma decreases after the onset of adaptive immunity , and did not support the hypothesis that rechallenge altered the course of the primary infection . To further investigate this question , we assessed inflammation in individual library A granulomas by PET CT prior to and after library B challenge and compared this to similar time points in historical macaques challenged with Mtb Erdman , and again saw no evidence that secondary infection altered the inflammatory dynamics of the preexisting infection ( S3 Fig ) . We next sought to distinguish whether the lower bacterial burden in granulomas formed after reinfection reflected restriction of bacterial growth and/or true enhancement of bacterial killing . We assessed granuloma bacterial genome counts ( CEQ ) attributable to library B in naïve and rechallenged animals and then quantified killing of the challenge strain by relating viable library B live bacteria counts ( CFU ) to library B genome counts ( CEQ ) , as described[14 , 24] ( Fig 2B ) . In rechallenged animals , library B granulomas had significantly lower CEQ than in naïve animals , indicating reduced replication of the infecting bacteria . Library B granulomas had concomitantly lower CFU ( Fig 2B ) , which also reflected significantly increased killing ( as reflected by CFU/CEQ ) of the library B in granulomas from rechallenged animals relative to naïve animals ( Fig 2B and 2C median log killing = -1 . 41 ( naïve ) vs . -3 . 19 ( reinfected ) , p = 0 . 0002; ~1 . 75 log increase in killing ) . Interestingly , there was no correlation between bacterial killing of library B Mtb and host lung inflammation at the time of second challenge ( Fig 2D , r = 0 . 03 , p = 0 . 8832 ) , nor was there any association between total thoracic bacterial burden at necropsy in those macaques who had few library B+ granulomas and those who had none ( S5 Fig ) . Thus , the extent of disease at time of secondary exposure does not appear to affect the protection against reinfection . To assess the protection provided by concurrent infection in the context of current vaccine strategies , we compared the bacterial loads from granulomas in our naïve and reinfection monkeys to those from macaques vaccinated with BCG boosted with an adjuvanted fusion protein ( H56 in CAF01[25 , 26] ) . We previously showed that BCG+H56 provides protection against reactivation , reduces pathology and improves survival of Mtb-infected macaques[27 , 28] . Moreover , the size and FDG avidity of early granulomas in BCG+H56 vaccinated animals were reduced compared to unvaccinated animals , as was found in the granulomas formed in the setting of reinfection ( Fig 3A and 3B ) . However , at the early time points assessed here , the bacterial control engendered by primary Mtb infection was dramatically superior to that found in the vaccinated animals ( Fig 3C ) . In addition , primary infection prevented dissemination of the reinfection strain to thoracic lymph nodes while BCG+H56 did not have a similar effect ( Fig 3D ) ; the number of granulomas at 4–5 weeks post-challenge in BCG-vaccinated macaques was similar to contemporaneous control macaques ( S1D Fig ) . By contrast , in aggregate primary infection provided ~10 , 000 fold protection against Mtb reinfection as assessed by granuloma bacterial burdens ( Fig 3C ) , reflecting the combined effects of restricted establishment of infection , limited bacterial growth , and increased bacterial killing . To provide insight into the local immunologic landscape that may contribute to the protection seen with reinfection , we first assessed uninvolved lung tissue from reinfected monkeys using Luminex ( S4A Fig ) compared to responses in an uninfected monkey , where it was only possible to euthanize one animal for analysis of normal lung tissue . These data suggested that even in uninvolved tissue , infection is associated with the expression of innate cytokines and chemokines . Though this analysis was limited by the availability of uninfected animals , the data suggest increased IL-8 in lung tissue from infected monkeys compared to uninfected control monkeys , possibly implicating increased neutrophil migration in infected tissues , and a decrease in IL-1 in infected tissues , with a trend towards increased IL-1RA . CXCL9 , a chemokine that binds CXCR3 was also slightly higher in infected lung tissues , suggesting possible increased T cell migration , while CXCL13 , which is chemotactic for B cells , was reduced . We also assessed uninvolved lung tissue from a separate set of Mtb-infected monkeys ( not reinfected ) at similar time points for Mtb-specific ( ESAT6/CFP10 ) T cell responses ( S4B Fig ) . Mtb-specific T cell responses were higher in infected lung tissue , compared to uninfected lung tissue , indicating the presence of T cells resident within lung tissue that could rapidly activate macrophages upon encountering a new Mtb bacillus . Thus , a reinfecting bacillus encounters innate and adaptive immune responses in lung tissue , which may underlie the more rapid killing of the bacterium that we observed . We next assessed T cell responses in the few library B granulomas that did establish in the reinfected monkeys and compared these to library A granuloma in the same animals and library B granulomas that established in naïve animals ( Fig 4 ) . In general , T cell responses in library A and B granulomas in reinfected macaques were similar , and the data reflect the normal variability seen in immune responses in granulomas[20] . There were no significant differences in the frequency of T cells making TH1 cytokines among library B granulomas from naïve or reinfected macaques , or library A granulomas in reinfected macaques . However , IL-10 was significantly higher in both library A and B granulomas in reinfected macaques compared to granulomas in naïve macaques . Our prior data suggested that the combination of T cells expressing IL-10 and T cells expressing a pro-inflammatory cytokine in granulomas was associated with the sterilization of Mtb granulomas[20] . The higher levels of IL-10 in granulomas with lower bacterial loads as compared to granulomas in naïve animals is consistent with this finding . More broadly , production of inflammatory cytokine and chemokines ( measured in granuloma supernatants ) was lower in library B granulomas in animals with primary infection relative to those formed in naïve animals ( Fig 5 ) . TNF , IL-1β , IL-18 , IL-1RA , IL-8 , MCP-1 , and MIG were all present at significantly ( p<0 . 05–0 . 0001 ) lower levels in secondary granulomas , with a trend towards lower IFN-γ . This likely reflects the low bacterial burden in the reinfection granulomas and again may indicate a healing response as those granulomas rapidly kill the bacteria . Further study into the precise kinetics and cellular organization of these granulomas is needed to help inform intervention strategies .
In this study , we present evidence for robust concomitant immunity in the cynomolgus macaque model of TB , using a combination of PET CT imaging and molecular analysis of DNA-tagged strains of M . tuberculosis in a macaque model . We found complete protection against productive secondary infection in five macaques with ongoing infection ( Figs 1D and 2A ) , almost no productive dissemination to lymph nodes ( Fig 3D ) , and a ~10 , 000-fold decrease in live Mtb in library B ( reinfection ) granulomas compared to age-matched granulomas in naïve animals ( Figs 2B , 2C and 3C ) . One reinfected monkey had no trace of library B DNA despite receiving a secondary challenge dose of 10 CFU . The number of new granulomas that were seen by PET CT and attributed to library B by Q-tag analysis at 4 weeks post-reinfection was significantly lower in macaques with ongoing primary ( library A ) infection , compared to the number of library B granulomas at 4 weeks post-infection in naïve ( i . e . no primary infection ) macaques . The new library B granulomas that were established in the reinfected animals were often sterile or had very low bacterial burden , in stark contrast to 4 week granulomas in naïve macaques , where the bacterial burden is generally quite high . Using CEQ analysis , we determined that the library B Mtb bacilli did not grow to the same extent in reinfected macaques as in naïve macaques , and that bacterial killing was increased . Thus , reduced new granuloma formation , reduced growth and increased killing resulted in a 10 , 000 fold decrease in live Mtb library B bacilli in reinfected macaques , compared to the bacterial burden of library B Mtb in naïve macaques at the same time point . The extent of protection in the setting of reinfection as compared to that provided by intradermal BCG followed by a fusion protein boost suggests that there is a fundamental difference between the immune profile elicited by primary Mtb infection and that generated by BCG intradermal vaccination . We suspect that this reflects the difference in immunity expressed by local ( i . e . lung ) resident T effector cells maintained by ongoing infection versus the systemic response promoted by a distal boosted BCG vaccination . Our data suggest that T cells specific for Mtb proteins are present in uninvolved lung tissue of infected macaques , which supports this hypothesis . In addition , we found modestly increased innate cytokines in uninvolved lung tissue from infected macaques , which may also contribute to reducing initial establishment of infection . Further studies are required to determine which factors are necessary or sufficient for protection against re-infection . Immunologic assessment of the few library B granulomas that were established following reinfection showed increased IL-10+ T cell responses compared to those from naïve macaques . The IL-10+ T cell responses in reinfection granulomas were similar to those in the primary ( library A ) infection granulomas in the same macaques . We previously published that IL-10+ T cells in conjunction with T cells producing a proinflammatory cytokine ( i . e . IL-17 ) in individual granulomas was associated with lower bacterial burdens , including sterility[20] . We interpret this to mean that either an immune balance of pro- and anti-inflammatory cytokines is a robust pathway to sterilization in granulomas , or that the IL-10 signal is a sign of granuloma healing once bacteria have been killed . At this point , we cannot distinguish between those possibilities . Nonetheless , the fact that the 20 week library A granulomas ( most of which have succeeded in killing many of the bacteria within them[14 , 17] ) and the 4 week library B granulomas in the same animals shared this increased IL-10+ T cell profile suggests that the Library B granulomas are primed to quickly dispense with the infection , with IL-10 production being one factor associated with that clearance . The data presented here have implications for TB vaccines . The extent of protection that we find against rechallenge suggests that robust protection via a vaccine is possible . This level of protection would be truly remarkable for a TB vaccine , and suggests that a protective vaccine for TB may have to induce long lived , likely local , immune responses that mimic those induced by primary infection . The recent study showing substantial protection in rhesus macaques by a CMV vector expressing multiple Mtb antigens suggests that sustained high level T cell responses are important for immunity but the correlate of protection analysis also pointed to the potential importance of an activated innate immune response in mediating bacterial clearance[29] . We could not formally define a correlate of protection conferred by concurrent infection since all concurrently infected animals were robustly protected against reinfection; defining a correlate requires failure of protection in some animals . There were no immunologic or disease parameters that segregated animals that fully sterilized the challenge from those that sterilized many but not all sites of infection ( S5 Fig ) . However , our immunologic analysis does provide evidence of an activated innate response and Mtb specific T cells in the uninvolved lung tissue of infected animals that could participate in clearance . In the current study , the primary infection and the reinfection strains were the same: virulent Mtb Erdman . Whether a primary infection with one strain could provide such robust protection against a heterologous strain remains to be tested . Given the broad immune responses induced by Mtb against multiple antigens , and the absence of data in human-like models indicating that immune responses against a single or a few antigens provide robust protection , we suspect that a heterologous re-challenge would be well-controlled . Nonetheless , such experiments are necessary to address this clinically relevant point . Concomitant immunity has been described in other systems , e . g . tumor rejection models[30] . In terms of infectious diseases , this is best characterized for leishmaniasis , where the presence of a live but contained Leishmania infection prevents establishment of a new infection . In the Leishmania model , this protection depends on the presence of high levels of T effector cells rather than central memory T cells , and is lost when the original infection is cleared[31] . Our study supports concomitant immunity in Mtb infections , although it remains to be determined whether complete clearance of primary Mtb infection with drug treatment will abrogate the extraordinary protective effects shown here[32] . While the precise immune mechanisms underlying the protection described here are not yet fully characterized , this study provides exciting clues for revised TB vaccine strategies to achieve both sterilizing immunity and protection from infection .
University of Pittsburgh IACUC reviewed and approved the study protocol . The protocol assurance number for our IACUC is A3187-01 . Specific Approval number: 15066174 . The IACUC adheres to national guidelines established in the Animal Welfare Act ( 7 U . S . C . Sections 2131–2159 ) and the Guide for the Care and Use of Laboratory Animals ( 8th Edition ) as mandated by the U . S . Public Health Service Policy . All macaques used in this study were housed at the University of Pittsburgh in rooms with autonomously controlled temperature , humidity , and lighting . Animals were singly housed in caging at least 2 square meters apart that allowed visual and tactile contact with neighboring conspecifics . The macaques were fed twice daily with biscuits formulated for nonhuman primates , supplemented at least 4 days/week with large pieces of fresh fruits or vegetables . Animals had access to water ad libitem . Because our macaques were singly housed due to the infectious nature of these studies , an enhanced enrichment plan was designed and overseen by our nonhuman primate enrichment specialist . This plan has three components . First , species-specific behaviors are encouraged . All animals have access to toys and other manipulata , some of which will be filled with food treats ( e . g . frozen fruit , peanut butter , etc . ) . These are rotated on a regular basis . Puzzle feeders foraging boards , and cardboard tubes containing small food items also are placed in the cage to stimulate foraging behaviors . Adjustable mirrors accessible to the animals stimulate interaction between animals . Second , routine interaction between humans and macaques are encouraged . These interactions occur daily and consist mainly of small food objects offered as enrichment and adhere to established safety protocols . Animal caretakers are encouraged to interact with the animals ( by talking or with facial expressions ) while performing tasks in the housing area . Routine procedures ( e . g . feeding , cage cleaning , etc ) are done on a strict schedule to allow the animals to acclimate to a routine daily schedule . Third , all macaques are provided with a variety of visual and auditory stimulation . Housing areas contain either radios or TV/video equipment that play cartoons or other formats designed for children for at least 3 hours each day . The videos and radios are rotated between animal rooms so that the same enrichment is not played repetitively for the same group of animals . All animals are checked at least twice daily to assess appetite , attitude , activity level , hydration status , etc . Following M . tuberculosis infection , the animals are monitored closely for evidence of disease ( e . g . , anorexia , weight loss , tachypnea , dyspnea , coughing ) . Physical exams , including weights , are performed on a regular basis . Animals are sedated prior to all veterinary procedures ( e . g . blood draws , etc . ) using ketamine or other approved drugs . Regular PET/CT imaging is conducted on most of our macaques following infection and has proved very useful for monitoring disease progression . Our veterinary technicians monitor animals especially closely for any signs of pain or distress . If any are noted , appropriate supportive care ( e . g . dietary supplementation , rehydration ) and clinical treatments ( analgesics ) are given . Any animal considered to have advanced disease or intractable pain or distress from any cause is sedated with ketamine and then humanely euthanatized using sodium pentobarbital . Fourteen adult cynomolgus macaques ( Macacca fasicularis ) were obtained from Valley Biosystems ( Sacramento , California ) and screened for Mtb and other comorbidities during a month-long quarantine . Each macaque had a baseline blood count and chemical profile and was housed according to the standards listed in the Animal Welfare Act and the Guide for the Care and Use of Laboratory Animals . All procedures were approved by the Institutional Animal Care and Use Committee at the University of Pittsburgh . The animals were separated into two cohorts: 8 macaques were assigned to reinfection and 6 were assigned to naïve 4-week only controls . All animals were infected with barcoded strain Erdman Mtb via bronchoscopic instillation as previously published[11 , 12] . The infection schema is provided in Fig 1A; 8 macaques were infected with Mtb library A , followed 16 weeks later by Mtb library B; 6 naïve macaques were infected with Mtb library B in a series of matched infections . All animals received an inoculum of <15 CFU ( determined by plating a sample of the inoculum and counting CFU after 3 weeks ) with the details listed in S1 Table . The animals were further subdivided such that 4 reinfection animals were directly paired with 2 , naïve animals; 2 additional naïve animals were infected separately ( S1 Table ) . Each macaque was followed with serial 2-deoxy-2-[18F]-fluoro-D-glucose ( [18F]-FDG ) PET-CT imaging as previously described[14–16] to identify and track lesion formation and progression over time . PET-CT scans were performed monthly during the primary infection , and as noted in S1 Table after reinfection . Total FDG activity in lungs was used to estimate thoracic bacterial burden prior to reinfection , as previously published[13 , 33] . Granulomas were individually characterized by their date of establishment ( scan date ) , size ( mm ) , and relative metabolic activity as a proxy for inflammation ( [18F]-FDG standard uptake normalized to muscle [SUVR][13 , 33] ) . Granulomas ≥ 1mm can be discerned by our PET-CT imaging analysis ( Fig 1B ) . All macaques were necropsied at ~4 weeks post-library B infection . The pre-necropsy PET-CT scan was used to map new and old granulomas . To avoid barcode cross-contamination , individual granulomas were separately excised and processed , along with all thoracic lymph nodes . Each sample was homogenized to a single cell suspension , plated for CFU on 7H11 agar supplemented with oleic albumin dextrose catalase ( OADC ) , and frozen aliquots were stored for DNA extraction . For the BCG+H56 vaccine study , 6 cynomolgus macaques were vaccinated with BCG ( 5x105 ID ) followed by an intramuscular injection of the fusion protein H56 ( composed of ESAT-6 , Ag85B , and Rv2660c ) in the adjuvant CAF01 at 10 and 14 weeks post-BCG . Six cynomolgus macaques were unvaccinated controls . Six months after BCG , all 12 macaques were infected with M . tuberculosis strain Erdman ( not barcoded ) ( S4 Table ) . PET-CT scans were performed at 4–5 weeks post-infection , just prior to necropsy ( S4 Table ) , and analyzed as in the reinfection study . All granulomas and lymph nodes were obtained using the PET-CT scan as a map , homogenized and plated for bacterial burden . A small portion of granuloma homogenate was frozen for qTag sequencing and chromosomal equivalent ( CEQ ) analysis . For analysis of bacteria that grew from the granulomas , bacterial colonies from granuloma and lymph node plates were scraped to obtain all colonies , and frozen . Genomic DNA was extracted as previously published[14 , 24] . In brief , gDNA was twice extracted with phenol:chloroform:isoamyl alcohol ( 25:24:1 , Invitrogen ) with an intermediate bead beating step using 0 . 1mm zirconia-silica beads ( BioSpec Products , Inc . ) . To identify DNA tags from each library , genomic DNA was diluted to 10 ng/μL and amplified with Q5 polymerase ( New England Biolabs ) with two rounds of PCR of 8–15 cycles each , using the primers described in Martin et al[17] . Samples were then sequenced on an Illumina MiSeq using v2 chemistry . Barcodes were identified using custom scripts as described in Martin et al . To identify qTags , genomic DNA was diluted to 100 ng/μL and amplified with 24–36 cycles of PCR , using the primers listed in S3 Table . PCR product was used as input in the NanoString nCounter assay ( NanoString Technologies ) with custom-designed probes to determine qTag identity . We attributed the bacteria in any mixed lesion to library B , a conservative assumption that would lead us to overestimate the success of library B in the setting of rechallenge . Supernatants from granuloma and uninvolved lung tissue homogenates were frozen at -80°C until time of assay . After thawing , samples were filtered using a 0 . 22um syringe filter to remove any infectious bacteria and kept on ice . Thirty cytokines and chemokines were assayed from the granuloma supernatants in duplicate using a ProcartaPlex multiplex immunoassay ( Invitrogen ) specific for nonhuman primate samples according to manufacturer’s instructions , with an additional dilution of the supplied standard curve to extend sample detection range . Multiplex results were read and analyzed by BioPlex reader ( BioRad ) . Flow cytometry was performed on individual granulomas from naïve and reinfected macaques and a random sampling of lung tissue without any disease pathology from 6 Mtb infected macaques ( with no reinfection ) and an uninfected macaque . For granulomas , no restimulation was performed because of the high level of antigens in the granulomas , as previously noted[20] . Single cell suspension of the lung tissue was stimulated with peptide pools of Mtb specific antigens ESAT-6 and CFP-10 ( 10ug/ml of every peptide ) in the presence of Brefeldin A ( Golgiplug: BD biosciences ) for 3 . 5 hours at 37°C with 5% CO2 . The cells were then stained for Viability marker ( Invitrogen ) , surface and intracellular cytokine markers . Flow cytometry for cell surface markers for T cells included CD3 ( clone SP34-2; BD Pharmingen ) , CD4 ( Clone L200 , BD Horizon ) and CD8 ( clone SK1 , BD biosciences ) . Intracellular cytokine staining panel included pro-inflammatory cytokines: Th1 [IFN-γ ( Clone B27 ) , IL-2 ( Clone: MQ1-17H12 ) , TNF ( Clone: MAB11 ) ] and Th17 [IL-17 ( Clone: eBio64CAP17 ) . Data acquisition was performed using an LSR II ( BD ) and analyzed using FlowJo Software v . 9 . 7 ( Treestar Inc , Ashland , OR ) . A dimension reduction technique was performed on data extracted from PBMCs sampled just prior to reinfection ( 15 weeks post infection ) . Principal components analysis ( PCA ) was utilized here to investigate whether protected animals cluster separately from unprotected animals using blood signatures . Unfortunately , with such a small sample size ( n = 8 macaques ) PCA is not stable , so these results should be interpreted with caution . Graphs were created in Graphpad Prism and JMP and all statistical analysis was performed in Graphpad Prism . In datasets that included zeroes , data were transformed by adding either 1 or 0 . 01 so that zeroes could be graphed on a log-scale . The D’Agostino and Pearson test was used to test for normality . If data were found to be normal , groups were compared using t-tests; otherwise , groups were compared using the non-parametric Mann-Whitney test for two groups or the Kruskal-Wallis test for three groups ( with Dunn’s multiple comparison adjustment ) . All tests were two-sided with significance defined as p<0 . 05 .
|
Tuberculosis ( TB ) , a lung disease caused by the bacterial pathogen Mycobacterium tuberculosis , is endemic in many developing countries . This infection is transmitted from a person with active tuberculosis through coughing , talking , and singing . Exposure to this bacterium can result in a spectrum of infection outcomes , including in the majority of persons asymptomatic infection , known as latent TB . However , re-exposure to those with active disease occurs frequently , particularly in crowded conditions . Here we demonstrate that ongoing Mtb infection in a non-human primate model provides robust protection against reinfection and disease . This has important implications for vaccine development against this infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
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2018
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Concurrent infection with Mycobacterium tuberculosis confers robust protection against secondary infection in macaques
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Alternative splicing controls the expression of many genes , including the Drosophila sex determination gene Sex-lethal ( Sxl ) . Sxl expression is controlled via a negative regulatory mechanism where inclusion of the translation-terminating male exon is blocked in females . Previous studies have shown that the mechanism leading to exon skipping is autoregulatory and requires the SXL protein to antagonize exon inclusion by interacting with core spliceosomal proteins , including the U1 snRNP protein Sans-fille ( SNF ) . In studies begun by screening for proteins that interact with SNF , we identified PPS , a previously uncharacterized protein , as a novel component of the machinery required for Sxl male exon skipping . PPS encodes a large protein with four signature motifs , PHD , BRK , TFS2M , and SPOC , typically found in proteins involved in transcription . We demonstrate that PPS has a direct role in Sxl male exon skipping by showing first that loss of function mutations have phenotypes indicative of Sxl misregulation and second that the PPS protein forms a complex with SXL and the unspliced Sxl RNA . In addition , we mapped the recruitment of PPS , SXL , and SNF along the Sxl gene using chromatin immunoprecipitation ( ChIP ) , which revealed that , like many other splicing factors , these proteins bind their RNA targets while in close proximity to the DNA . Interestingly , while SNF and SXL are specifically recruited to their predicted binding sites , PPS has a distinct pattern of accumulation along the Sxl gene , associating with a region that includes , but is not limited to , the SxlPm promoter . Together , these data indicate that PPS is different from other splicing factors involved in male-exon skipping and suggest , for the first time , a functional link between transcription and SXL–mediated alternative splicing . Loss of zygotic PPS function , however , is lethal to both sexes , indicating that its role may be of broad significance .
Understanding tissue- and stage-specific gene regulation remains one of the central issues in developmental biology . Studies of developmentally important genes , such as those that specify and maintain cell fate , have revealed that many genes are regulated post-transcriptionally . The Drosophila sex-determination gene Sex-lethal ( Sxl ) is a prime example of a developmental switch gene regulated by alternative splicing . Throughout most of development and in adult tissues , Sxl is controlled by sex-specific alternative splicing to produce mRNAs with different coding potentials [1] . In males , all transcripts include the translation-terminating third exon leading to the production of mRNAs that encode truncated , inactive proteins . In females , the third exon is always skipped to generate protein encoding mRNAs . The mechanism leading to exon skipping is autoregulatory and depends on the SXL protein binding to multiple intronic sites located both upstream and downstream of the regulated exon . Current models , based on both biochemical and genetic studies , suggest that SXL forces the male exon to be skipped by interacting with and antagonizing a set of general splicing factors , including the U1 snRNP , the U2AF heterodimer , FL ( 2 ) d and SPF45 [2]–[4] . Because Sxl controls both its own expression and the expression of a set of downstream target genes , this autoregulatory splicing loop serves as a heritable and irreversible molecular switch for the developmental pathways controlling both somatic sex determination and X-chromosome dosage compensation . Initiation and stable engagement of the Sxl autoregulatory splicing loop requires the coordinated use of two alternative promoters [5]–[7] . Throughout most of development , Sxl is expressed from the non-sex specific “maintenance” promoter , SxlPm . SxlPm is first expressed during the maternal to zygotic transition , but prior to that time Sxl is transiently expressed from the female-specific “establishment” promoter , SxlPe . The SxlPe-derived transcripts , unlike the transcripts produced from SxlPm , are spliced by default to produce SXL protein . Thus the SXL protein present in XX embryos when SxlPm is first activated serves to drive the initiating round of exon skipping which leads to a self-sustaining splicing loop . In XY animals , on the other hand , SxlPe is not activated , there is no SXL protein , and all SxlPm-derived transcripts are spliced in the male mode . While coordinated promoter switching is critical for successful establishment of the Sxl autoregulatory splicing loop in early embryogenesis , it has been generally assumed that transcription plays little , if any , role in sex-specific regulation after this point . Here we report the identification and analysis of a previously uncharacterized protein , named Protein Partner of Sans-fille ( PPS , CG6525 ) , as a novel component of the machinery that controls Sxl alternative splicing . PPS , a large multidomain protein classified as a transcription regulator based on the presence of 4 distinct and conserved sequence motifs , was identified in a yeast two hybrid screen for proteins that interact with Sans-fille ( SNF ) , the Drosophila homolog of the U1 snRNP protein , U1A . We provide compelling evidence that PPS has a direct role in Sxl male exon skipping by showing first that the loss of pps function interferes with Sxl function , and second that PPS can form a complex with the U1 snRNP , SXL and the Sxl pre-mRNA . In addition , we mapped the association of PPS , SXL and SNF along the Sxl gene by chromatin immunoprecipitation ( ChIP ) , providing evidence that these proteins , like many other splicing factors , bind their RNA targets while in close proximity to the DNA . While we found that SXL and SNF associate with their predicted binding sites , PPS has a distinct pattern of accumulation along the Sxl gene which suggests that PPS is loaded onto the RNA at the promoter . Finally , we show that PPS function is not restricted to Sxl splicing regulation , indicating that PPS is likely to be more broadly involved in development .
CG6525 was identified in a yeast two hybrid screen for SNF-interacting proteins , giving the gene its name protein partner of sans-fille ( pps; Figure 1A ) . To demonstrate that the PPS/SNF interaction also occurs in Drosophila cell extracts , we assayed for complex formation by pull-down experiments in which a GST fusion protein containing the C-terminal end of PPS ( amino acids 1370–2016 ) was expressed in E . coli , bound to glutathione sepharose beads , and incubated with protein extracts made from embryos . The presence or absence of SNF in the complex formed on the beads was assayed by Western blot analysis ( Figure 1B ) . In control studies , we used a GST::SXL fusion protein since it is known to form a complex with SNF [2] . As predicted by the two hybrid data , we found that GST::PPS , but not GST alone , was capable of selecting SNF out of extracts as efficiently as GST::SXL . These data therefore confirm that PPS and SNF associate in vivo . PPS is located on the 3rd chromosome ( 87B ) and , in agreement with the predicted gene structure , we found that the pps transcription unit extends over 6 . 7 kb . and the 11 constitutively spliced exons are predicted to encode an uncharacterized 2016 amino acid protein ( Figure 1C and 1D ) . The pps open reading frame contains 4 conserved motifs: PHD finger ( plant homeodomain ) , BRK ( Brahama and Kismet ) , TFS2M ( transcription elongation factor S-II middle ) and SPOC ( Spen paralogue and orthologue C-terminal ) . According to the Gene Ontology Database , which assigns functions to uncharacterized proteins based the presence of sequence motifs , PPS is likely to function in transcriptional regulation ( see discussion ) . To gain insight into the biological role of PPS , we generated a molecular null allele using an FRT-based targeted deletion strategy [8] , [9] . Briefly , we induced recombination in animals heterozygous for two FRT-bearing piggyBac insertions with controlled expression of the FLP recombinase and identified a deletion with the desired endpoints using a PCR based strategy . The resulting deletion , depicted in Figure 1D , removes the entire coding sequence of pps as well as the adjacent gene , Scg-β . Animals homozygous for this two gene deletion die during the third instar larval stage . Two critical experiments demonstrate that the lethality is due to the loss of pps and not Scg-β . First , lethality was fully rescued by one or two copies of P{pps+} , a genomic transgene that carries just the pps gene ( 90% , n = 554 ) . Second , all aspects of the mutant phenotype remained unchanged by the addition of multiple copies of the adjacent P{Scg-β+} genomic transgene ( see Materials and Methods for details ) . Thus , these data provide strong evidence that disruption of PPS is responsible for the larval lethal phenotype and the two gene deletion we have isolated behaves as a pps null allele . Based on these genetic data , we have named this deletion pps1 . Homozygous pps1 mutant animals fail to survive to adulthood , although all animals reach the third instar larval stage . Consistent with the failure to pupate , mutant third instar larvae were found to have a number of defects , including small , underdeveloped imaginal discs , abnormal polytene chromosome morphology and melanized patches of tissue that resemble melanotic tumors ( data not shown ) . Although pps null mutants complete embryogenesis without any apparent defects , we cannot rule out an earlier function in embryogenesis . PPS is a maternally provided protein and the extended stability common to many maternally provided proteins typically result in the rescue of homozygous mutant animals into the larval stages . Thus , pps mutant animals may survive until the maternal stores of protein are depleted , masking a potential requirement in embryogenesis . During the course of this analysis , we noted that , while either one or two copies of the P{pps+} transgene was sufficient to rescue the lethality of pps1 homozygous mutant females , two copies were necessary to rescue the females to fertility . An examination of the ovaries isolated from these sterile mutant females revealed that the ovaries contained tumors ( Figure 2A ) . Ovarian tumor phenotypes are also observed in partial loss of function snf mutant backgrounds , where the phenotype is caused by defects in Sxl splicing regulation [2] , [10] . To investigate the possibility that the pps tumor phenotype is also correlated with Sxl misregulation , we used RT-PCR to assay the Sxl RNA products present in isolated ovarian tissue . Using a single primer pair capable of detecting the female and the larger male spliced products , we found that in ovarian tissue isolated from sterile mutant females , a significant proportion of the spliced products contained the male-specific exon ( Figure 2B and 2C ) . Thus , based on these partial loss of function mutant phenotypes , we conclude that pps , like snf , is required to achieve stable Sxl activity in the female germline . Activation of Sxl in the embryo is a multi-step process , starting with the coordinated use of two promoters and culminating with successful engagement of the autoregulatory splicing loop . Thus , perturbation of any single step in the process can lead to a defect in alternative splicing . As a consequence , embryos heterozygous for the normally recessive null allele of Sxl ( Sxlf1/+ ) are particularly sensitive to the supply of specific splicing and transcription factors deposited into the egg by the mother ( e . g . [2]–[4] ) . We therefore reasoned that if maternally provided PPS protein is important for any aspect of Sxl regulation , we might expect the viability of Sxlf1/+ females to be affected if their mothers were heterozygous for pps ( pps1/+ ) . However , we found that these Sxlf1/+ females were as viable as their control siblings ( data not shown ) . To increase the sensitivity of this assay , we introduced a mutant allele of daughterless ( da2 ) into the genetic background . da encodes a maternally supplied transcription factor required to activate Sxl [11] , [12] . We chose da2 to sensitize the genetic background because we have previously shown that the genetic interaction between snf and da is particularly strong [13] . In control crosses , we found that 57% of the expected Sxlf1/+ daughters from da2/+ mothers survived to adulthood ( n = 275; Figure 3 ) . However , when the mothers were heterozygous for both pps1 and da2 , there was a significant reduction in viability with only 7% of the expected Sxlf1/+ daughters surviving to adulthood ( n = 222 ) . Restoration of female viability by the genomic rescue construct P{pps+} indicates that this female-lethal synergistic interaction is due to the loss of pps function ( 26%; n = 517 ) . To confirm the genetic relationship between pps and Sxl , we looked for synergistic interactions with mutant alleles of fl ( 2 ) d , U2af38 and spf45 . Mutations in these three genes were picked because they encode core spliceosomal proteins known to play an important role in Sxl autoregulation [2]–[4] . These data show that pps1 in combination with mutations in each of these spliceosomal genes exerts a detrimental synergistic effect on the viability of Sxlf1/+ females ( Table 1 ) . Together , these data indicate that the maternally provided PPS protein contributes , in some way , to Sxl regulation . Previous studies have shown that SXL interacts with SNF in the context of the U1 snRNP [2] . We reasoned , therefore , that if pps has a direct role in Sxl splicing autoregulation , then we might be able to detect physical interactions between PPS , the U1 snRNP and SXL . To test this , we generated an antibody against the C-terminal end of PPS ( amino acids 1370–2016 ) for co-immunoprecipitation assays . PPS is predicted to encode a single polypeptide of 222 kD , and as predicted , we found that on Western blots , the wild type protein migrates at about 220 kD in extracts made from adults of both sexes , embryos and third instar larvae ( Figure 4A , and data not shown ) . In contrast , no immunoreactivity was detected in extracts made from third instar larvae homozygous for pps1 , demonstrating the specificity of this antibody . Using this antibody for co-immunoprecipitation experiments , we were able to confirm that PPS and SNF associate in vivo ( Figure 4B ) . As expected , RNase addition did not abrogate the SNF/PPS interaction , even though the RNase treatment was sufficient to disrupt the known RNase-sensitive interaction between SNF and U2A' ( Figure 4B ) . To test whether PPS associates with SNF as a component of the U1 snRNP , we asked whether we could detect an interaction between PPS and another core U1 snRNP protein , U1-70K . Our data shows that we were able to co-immunoprecipitate PPS and U1-70K ( Figure 4C ) , although we noted that PPS seems to preferentially associate with the more slowly migrating U1-70K species , among the major U1-70K isoforms observed in whole cell extracts . U1-70K is a phosphorylated protein , and studies in mammalian cells that have shown that dephosphorylation of U1-70K is necessary for the splicing reaction to proceed [14] . Thus , if PPS does in fact preferentially associate with the highly phosphorylated form of U1-70K , our data would lead to the conclusion that PPS , unlike SNF , only transiently associates with the U1 snRNP . Direct support for this conclusion comes from our more detailed analysis of PPS's role in Sxl splicing autoregulation described below . Finally , we asked whether PPS associates with the SXL protein and found that antibodies against the PPS protein can in fact immunoprecipitate SXL ( Figure 5A ) . Interestingly , this interaction was weakened when we carried out these experiments in the presence of RNase . This suggests that the SXL/PPS interaction is mediated and/or stabilized by RNA . Because the SXL protein exerts its effect by binding directly to its own pre-mRNA , we postulated that PPS might also associate with the unspliced Sxl pre-mRNA . To test this idea , we asked whether Sxl pre-mRNA is detectable in PPS immunoprecipitates . The results of these RNA immunoprecipitation assays ( RIP ) , which were carried in nuclear extracts without fixation , clearly shows that the unspliced Sxl RNA is detectable by RT-PCR using an intron 3-exon 4 primer pair ( Figure 5B ) . In control reactions , we found that Sxl RNA was also detected in SXL immunoprecipitates , but not in extracts treated with antibodies against the chromatin binding protein Polycomb ( PC ) or in pre-immune serum . To determine whether the SXL protein is required for the association between PPS and the Sxl pre-mRNA , we carried out RIP assays in nuclear extracts made from embryos collected from mothers homozygous for a viable allele of daughterless , da1 . da1 mutant mothers produce eggs that lack SXL protein because SxlPe is not activated [12] . SxlPm , however , is activated , and the resulting transcripts are therefore spliced in the male mode . As illustrated in Figure 5C , PPS was able to co-immunoprecipitate unspliced Sxl RNA in these SXL-deficient mutant extracts . In control reactions , we found that Sxl RNA was detected in SNF immunoprecipitates , but not in controls . Thus , we conclude that the PPS/Sxl pre-mRNA association does not depend on the presence of SXL protein in the extract . To gain a better understanding of the functional relationship between PPS , SXL and SNF , we compared the dynamics of their recruitment to the nascent Sxl transcript by combining genetic analysis with chromatin immunoprecipitation ( ChIP ) assays ( Figure 6 ) . Splicing factor-ChIP assays , which have been used in both yeast and mammalian cells , are possible because many splicing factors are recruited to their RNA targets while still in close contact with template DNA [15]–[17] . To validate this approach , ChIP analysis was first carried out with antibodies against SNF in a sexually mixed population of wild type 8–12 hour embryos . ChIP studies in mammalian cells have shown that U1 snRNP proteins specifically target regions of genes that include 5′ splice sites of recognized exons [17] . This predicts that SNF will accumulate on a region that includes the male-specific third exon ( Ex3 ) , but not on the SXL binding site which is located ∼250 bp away in the third intron ( In3 ) . As a specificity control , we assayed for SNF accumulation on the first exon of the SxlPe transcripts ( E1 ) because in 8–12 hour embryos E1 is treated as an intron , and thus should not be recognized by the splicing machinery . In agreement with our expectations , we found that SNF was present at the third exon ( Ex3 ) , but not at the other two locations . Additional controls for specificity include our demonstration that these three regions of the Sxl gene were not precipitated in controls or in ChIP assays carried out with the DNA binding Heat Shock Factor ( HSF ) . As a final control for specificity , ChIPs were also carried out with the 8WG16 antibody against the hypophosphorylated form of RNA polymerase II ( Pol IIa ) , because previous studies have shown that Pol IIa does not accumulate within the body of actively transcribed genes [18] , [19] . Having shown that recruitment of SNF to the Sxl gene can be detected by ChIP , we next asked whether we could use this methodology to view SXL and PPS recruitment . In agreement with in vitro RNA binding assays [20] , we found that SXL was present at the intronic SXL binding site , In3 . PPS , on the other hand , was not only present on the third exon ( Ex3 ) but also localized to the intronic E1 and In3 regions . Together these results argue that PPS , in contrast to both SNF and SXL , is uniformly distributed across the Sxl transcription unit . Next we asked whether the pattern of recruitment is different on nascent transcripts destined to be spliced in the female or male mode . Males do not express SXL protein; therefore , SXL-ChIP of chromatin isolated from a mixed sex population of embryos resulted in the analysis of only female embryos . PPS and SNF , on the other hand , are expressed in both male and female embryos , thus the analysis of chromatin from wild type embryos would mask any sex-specific differences , should they exist . To circumvent this issue , we repeated the SNF and PPS ChIP experiments in two mutant populations of embryos . To exclusively assay Sxl transcripts destined to be spliced in the female mode , chromatin was prepared from embryos collected from a stable stock in which all females carry an attached X chromosome and all males carry Sxl7BO , an X-linked deletion allele of Sxl . As there is no Sxl DNA present in the male embryos , this analysis is limited to Sxl chromatin isolated from female embryos . To generate a population of embryos where all nascent Sxl transcripts are destined to be spliced in the male mode , we prepared chromatin from embryos from da1 mothers . As described above , maternal DA protein is required to initiate SxlPe transcription early in embryonic development , therefore all eggs laid by homozygous mutant females fail to produce SXL protein . As shown in Figure 6 , we found that the pattern of PPS and SNF accumulation was not dependent on the source of the chromatin: PPS accumulated at all three sites , whereas SNF was only detected on the third exon . We therefore conclude that the recruitment pattern of PPS and SNF along the Sxl gene is the same in males and females . The uniform distribution of PPS on the Sxl transcription unit , together with its classification in the Gene Ontology Database as a protein involved in transcription , suggested to us that PPS might initially be recruited near SxlPm . We therefore repeated the ChIP experiments using two different primer sets targeting sequences upstream of the SxlPm transcription start site ( P1 and P2 ) and one that includes the first exon ( P3 ) . ChIP studies in Drosophila and mammalian cells have shown that the hypophosphorylated form of RNA polymerase II ( Pol IIa ) , detected by the 8WG16 antibody , is highly concentrated at the start of actively transcribed genes [18] , [19] . In agreement with these studies , we found that Pol IIa specifically accumulates at P1 , P2 and P3 ( Figure 7 ) . SNF , as expected , only accumulates on P3 , the region that overlaps with the first exon . As shown in Figure 7 , we found that PPS accumulates on P1 , P2 and P3 and that this distribution is not sex-specific . Taken together , these results suggest that PPS associates with the Sxl promoter . In addition to its autoregulatory function , the SXL protein also binds the tra pre-mRNA to regulate its sex-specific expression [21] . To determine whether PPS is involved in tra pre-mRNA splicing , we first carried out RIP assays and found that tra pre-mRNA is detectable in PPS immunoprecipitates , as well as in control SXL and SNF immunoprecipitates ( Figure 8A ) . We then carried out ChIP experiments to determine whether PPS is recruited to the tra promoter region ( Figure 8B ) . To demonstrate that we had targeted the promoter region , ChIP experiments with antibodies against the hypophosphorylated form of RNA polymerase II ( Pol IIa ) 8WG16 were used as a positive control . Antibodies against SNF are used here as a negative control . In accordance with our expectations , we found that PPS does in fact associate with the tra promoter region . While these studies clearly suggest that PPS has an additional role in tra splicing regulation , it is unlikely that PPS is globally associated with all actively transcribed genes , as we fail to detect associations with the intronless U2A gene and the intron containing snf gene ( Figure 8A and 8B ) . On the other hand , PPS is clearly not limited to SXL-mediated splicing events because loss of PPS function is lethal to both sexes . What these additional functions are remains to be determined .
Genetic studies have established that SXL protein is both necessary and sufficient to engage the Sxl autoregulatory splicing loop [22] . Mechanistically , however , SXL does not act alone and collaborates with components of the general splicing machinery , including the U1 snRNP , to block inclusion of the male exon [2] . In this study , ChIP assays showed that SNF and SXL are specifically recruited to their predicted binding sites on the nascent transcript: SNF to 5′ splice sites and SXL to its intronic binding sites . These data , together with our observation that the recruitment of SNF is not influenced by the presence or absence of SXL , support the current model in which SXL blocks male exon inclusion by interacting with general splicing factors bound to authentic splice sites ( Figure 9 ) . Splicing could be blocked immediately , or spliceosome assembly could continue , stalling only later in the pathway . The U1 snRNP , however , is only transiently associated with the spliceosome as it assembles on the splicing substrate and is released before the spliceosome is catalytically active [23] . Therefore it is likely that SXL acts by interrupting spliceosome assembly at some point after splice site recognition by the U1 snRNP , but before catalysis begins . In studies begun by screening for SNF-interacting proteins , we identified PPS , a conserved and previously uncharacterized Drosophila protein , as a novel component of the machinery required for skipping the Sxl male exon . We were able to establish this connection by demonstrating that ( 1 ) animals carrying loss of function pps mutations are compromised in their ability to regulate Sxl splicing , ( 2 ) PPS associates with the U1 snRNP via a direct interaction with SNF and ( 3 ) PPS associates with the SXL protein and the unspliced Sxl RNA . Although physically associated with the U1 snRNP , PPS does not appear to be a general splicing factor because it does not associate with all spliced transcripts ( this study ) , it is not found in affinity-purified Drosophila spliceosomal complexes [23] and it is not a homolog of a previously identified human splicing protein [24] . Thus , PPS stands apart from the other proteins known to facilitate proper Sxl splicing , all of which are known to be components of the splicing machinery . The results of our ChIP analysis also distinguishes PPS from known splicing factors , as it reveals a strikingly distinct pattern of accumulation along the Sxl gene , including occupancy at the SxlPm promoter region . This pattern of accumulation suggests that PPS is loaded onto the RNA at the promoter and/or that it has a role in transcription . Numerous studies have documented physical interactions between the transcriptional machinery and splicing factors [25] . Thus , PPS may well act in concert with the transcription machinery to promote SXL-mediated exon skipping ( Figure 9 ) . For example , PPS could serve as a bridging protein to accelerate recruitment of SXL to the nascent transcript , or it could facilitate the formation of the inhibitory SXL/U1 snRNP interaction . Whether PPS is physically coupled to the transcription machinery and/or has a role in controlling transcription will require additional studies . However , the fact that PPS contains 4 signature motifs typically found in proteins with known functions in transcription adds credence to this idea . Of these 4 motifs , the PHD finger is the most extensively studied . Numerous studies have shown that PHD fingers have histone methylation binding activity . Indeed , PPS is likely to have histone binding activity , as the PHD domains of both the S . cerevisiae ( BYE1 ) and mammalian ( DIDO ) PPS homologs preferentially bind to tri-methylated H3K4 ( H3K4me3 ) in vitro [26] , [27] . The possibility of a PPS–histone link is further strengthened by the presence of the metazoan specific BRK motif , a domain that is found in only two other Drosophila proteins–Brahma and Kismet–both of which are known to be chromatin binding proteins [28] , [29] . A connection to transcription is also suggested by the presence of the TFS2M motif . This motif is named after its founding member located in the center of the transcription elongation factor S-II , where it is essential for binding Pol II [30] . Finally , SPOC domains have been identified in a variety of proteins linked to transcription , the best characterized of which is the human SHARP nuclear hormone co-repressor [31] , [32] . A conserved function in transcription is particularly compelling in light of the current view that transcription and splicing are mechanistically coupled . In this regard , there are a few well-documented examples of mammalian chromatin binding proteins that affect alternative splicing [33] . For example the H3K4me3 binding protein , CHD1 , associates with the spliceosome and is required for efficient splicing [34] . In another example the BRK domain containing chromatin remodeling protein , BRAHMA/BRG1 , influences the alternative splicing of several transcripts [35] . Although still speculative , a mechanism linking transcription to splicing regulation is likely to be of major importance in early embryogenesis . Engagement of the autoregulatory splicing loop requires that the initiating source of SXL protein , produced from the transiently expressed SxlPe derived transcripts , be present when SxlPm is activated so that its transcripts can be alternatively spliced to produce more SXL protein . The changeover from SxlPe to SxlPm is tightly coordinated and uncoupling these events leads to disruptions in Sxl regulation [6] , [7] . While these studies suggest that transcriptional regulation of SxlPm is important for the switch to autoregulation , our studies lead us to propose that PPS contributes to the success of this switch by concurrently facilitating SxlPm transcription and promoting male-exon skipping . PPS function is not restricted to Sxl splicing regulation . In studies designed to test for specificity , we discovered that PPS also associates with the SXL-regulated tra pre-mRNA . In addition , we found that pps function is essential for viability of both sexes , indicating that pps function is not limited to SXL-mediated splicing events and is involved in other developmental pathways . In humans , the PPS homolog DIDO has been linked to a blood disorder called myeloproliferative disease ( MPD ) [36] . The relevance of this connection is suggested by our finding that homozygous pps mutant larvae contain melanotic tumors , tumors that often result from over-proliferation and aggregation of blood cells [37] . Thus , the discovery of PPS' role in controlling alternative splicing may be of significance to additional developmental pathways .
Using the entire SNF protein as bait , we screened 9 . 8×107 clones from Drosophila embryonic and adult cDNA libraries and identified 78 positive clones , all of which included the C-terminal end of the pps ( CG6525 ) gene . PPS was also reported to be a binding partner of CDK7 ( CG3319 ) [38] . However , we have not been able to verify the authenticity of this interaction ( data not shown ) , and suspect that this interaction is based on an annotation error because the snf and cdk7 genes partially overlap [39] . Mutant alleles and deficiencies used in this study include: Sxlf1 , Sxl7BO da1 , da2 , fl ( 2 ) d2 , U2af38ΔE18 , Df ( 2Lh ) D1 ( designated as spf45Δ in Table 1 ) , Df ( 3R ) Exel7316 , PBac{WH}Dip-Cf00706 and PBac{WH}CG17202f01979 [2]–[4] , [8] , [12] , [40]–[42] . We generated pps1 by FRT-mediated recombination between PBac{WH}Dip-Cf00706 and PBac{WH}CG17202f01979 using the conditions described previously [8] , [9] . Throughout this analysis we found that the phenotypes of pps1/pps1 and pps1/Df ( 3R ) Exel7316 , animals to be identical , indicating the absence of confounding background mutations on the pps1 mutant chromosome . The P{pps+} and P{Scg-β+ , CG17202+} genomic rescue constructs were generated by standard methods in the pCaSpeR4 transformation vector and transgenic flies were produced at Genetic Services ( http://www . geneticservices . com ) . Functional P{Scg-β+ , CG17202+} transgenes ( abbreviated as P{Scg-β+} in the text ) were selected based on their ability to complement a known point mutation in CG17202 . Each transgenic line was then tested for its ability to rescue the different pps mutant phenotypes , including the lethality of pps1/Df ( 3R ) Exel7316 and pps1/pps1 animals . The data presented in this paper are obtained with P{pps+} line # 10 . Additional marker mutations and balancers used in this study are described on Flybase ( http://www . flybase . org ) . The antibody against PPS was raised in guinea pig by Covance ( http://www . covance . com ) against a glutathione S-transferase ( GST ) tagged C-terminal domain PPS fragment ( amino acids 1370–2016 ) purified from bacteria . We note here that this PPS antibody has not proven to be useful for immunohistochemistry . The other antibodies used in this study include mouse anti-SNF-4G3 [43] , [44] , guinea pig anti-U2A' [45] , rabbit anti-U170K-151 [2] , mouse anti-SXL-M114 [46] , guinea pig anti- HSF [47] , rabbit anti-PC [48] , and mouse anti-RNA Pol IIa-8WG16 ( Millipore , #05-952 ) . Crude extracts for GST-pull down experiments ( Figure 1 ) and Western blots ( Figure 4 ) were prepared from 3–8 hour old embryos , sexed and genotyped third instar larvae or sexed adults in NET buffer ( 150 mM NaCl , 50 mM Tris , pH 7 . 5 , 5 mM EDTA ) supplemented with 0 . 5% NP-40 and Complete Mini Protease Inhibitor Cocktail Tablets ( Roche ) . Nuclear extracts for co-immunoprecipitation experiments were prepared from 3–18 hour old embryos as described previously [49] using NET buffer supplemented with 0 . 5% NP-40 for the co-IPs in Figure 4 and 0 . 05% NP-40 for the co-IPs in Figure 5 . For experiments in which the extracts were pretreated with RNase , 1/10 volume of RNase A ( 10 mg/ml ) and 1/20 volume of RNase T1 ( 100 , 000 units/ml ) were added directly to the extract and incubated overnight at 4°C . Co-immunoprecipitations , Western blot analysis and GST pull down assays were carried out according to standard protocols , using the conditions described previously [2] , [4] , [50] . Total RNA was isolated from ovaries , adults or embryos using TRIzol ( Invitrogen ) as directed by the manufacturer . To analyze the endogenous Sxl splicing products , the first strand synthesis was carried out with 1 µg of RNA , 500 ng/µl random hexamers with the SuperScript II Reverse Transcriptase System ( Invitrogen ) . The PCR reactions , using the High Fidelity Taq system ( Roche ) , were performed in 50 µl volume with 2 µl of the RT reaction with the following primers: GTGGTTATCCCCCATATGGC and GATGGCAGAGAATGGGAC . The PCR conditions were as follows: 94°C for 1 min , followed by 30 cycles of 94°C for 1 min , 55°C for 1 min , and 72°C for 2 min , and a single final step at 72°C extension for 10 min . Products were detected on a 2% agarose gel by staining with ethidium bromide . RNA/protein complexes were immunoprecipitated from nuclear extracts and diluted to 5 µg/µl in NET buffer ( 150 mM NaCl , 50 mM Tris , pH 7 . 5 , 5 mM EDTA ) , supplemented with 0 . 05% NP-40 , Complete Mini Protease Inhibitor Cocktail Tablets ( Roche ) and RNase inhibitor ( 100 U/ml ) using the conditions described previously [50] . RNA was isolated from the RNA/protein complexes using TRIzol ( Invitrogen ) as directed by the manufacturer . RNA was resuspended in 20 µl RNase-free water and DNase-treated . cDNA was synthesized with the SuperScript II Reverse Transcriptase System ( Invitrogen ) using 4 µl of the eluted RNA with a Sxl gene specific primer to exon 4 ( GATGGCAGAGAATGGGAC; Figure 6 ) or random hexamers ( Figure 8 ) . The PCR reactions , using the High Fidelity Taq system ( Roche ) , were performed in 50 µl volume with 2 µl of the RT reaction with the following primers–Sxl: GAGGGTCAGTCTAAGTTATATTCG and GATGGCAGAGAATGGGAC; snf: GGGATGTGCGAATGACTAG and GACTGGAGTTGCGTTCAC; tra: GATGCCGACAGCAGTGGAAC and GATGGCACTGGATCAGAATCTG; U2A: GGTGAAACT AACGCCGGAGC and CTCAGCTCCTGCAGGTTGTTG . PCR conditions were as follows:: 94°C for 1 min , followed by 30 cycles of 94°C for 1 min , 55°C for 1 min , and 72°C for 2 min , and a single final step at 72°C extension for 10 min . 2 µl of the first-round PCR amplification was subjected to a second round of PCR . . Products were detected on a 2% agarose gel by staining with ethidium bromide . Live embryos were dechorionated with 50% bleach and fixed for 15 min in a 1 . 8% paraformaldehyde/heptane fixative solution . Chromatin was prepared from 1–2 gram of fixed 8–12 hour old embryos using the conditions described previously [51] and sonicated for a total of 80 seconds ( 20 sec pulses with a 1 min rest on ice ) to produce sheared products of 300 to 400 bp . ChIP assays were performed with a commercially available ChIP assay kit ( #17–295; Millipore ) . Antibodies used for the IP step were diluted 1∶40 ( Pol IIa , HSF , PC and PPS ) and 1∶20 ( SXL and SNF ) . After purification , the ChIPed DNA samples were resuspended in 30 µl water . Enrichment of specific DNA fragments was analyzed by PCR on 2 µl ChIP material with the following primer sets: For Sxl–P1: CGGGGCTCAAAAGACATAAA and GCGTTAGTTAAGACTCAC TCCATTT; P2: CCGTTACGAATCAAGCGAAG and GGCTGGTCACAC TGTTCATT; P3: CAGCCGAGTGCCTAGAAAAA and ACTTTCCTTCTTCGGCAACA; E1: CAAGTCCAACTTGTGTTCAGA and TCGAACAGGGAGTCACAGTAT; Ex3: CGAAAAGCGAAAGACACTC and GTG TCCTCGATTCAAAAACAT; In3: ACATCATGCTTTTCTTAAGTGC and AACGATCCCCCAGTTATATTC . For U2A–GGCAGCGAATTG TTTTTCTG and GAATCTTATAGCCGCGCAAA; For tra–TGGTCTCCATGGAAAACGAG and TGCAAACACGGTTTCATTTC; For snf–AAACACCGGTGCGATAACAT and CGTTTGGTTGGGTAGCATCT . The PCR conditions for Sxl primers P1 , P2 , P3 , E1 and Ex3 , tra and snf were as follows: 94°C for 2 min , followed by 25 cycles of 94°C for 30 sec , 53°C for 30 sec , and 72°C for 1 min . The PCR conditions for Sxl In3 and U2A were as follows: 94°C for 2 min , followed by 25 cycles of 94°C for 30 sec , 55°C for 30 sec , and 72°C for 1 min . Products were detected on a 3% agarose gel by staining with ethidium bromide .
|
In Drosophila the sex-specific ON/OFF regulation of Sex-lethal ( Sxl ) is controlled by an autoregulatory splicing mechanism that depends on the SXL protein interacting with general splicing factors . Here we identify PPS as a novel component of the machinery required for Sxl splicing autoregulation by showing that the lack of pps function interferes with Sxl expression and that the PPS protein is physically linked to the Sxl pre–mRNA , the SXL protein and components of the general splicing machinery . PPS , however , stands apart from all other proteins known to control Sxl splicing because it is not a general splicing factor . Furthermore , PPS has a distinct pattern of accumulation along the Sxl transcription unit that suggests PPS is loaded onto the RNA at the promoter . Together with the observation that the PPS protein contains four signature motifs typically found in proteins that function in transcriptional regulation , our data suggest that linking transcription to splicing regulation is important for controlling Sxl expression . This idea is especially intriguing because it indicates that the coupling of transcription and splicing seen in vitro and in cell culture studies is likely to be pertinent to developmentally controlled patterns of gene expression in the living animal .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"molecular",
"biology/post-translational",
"regulation",
"of",
"gene",
"expression",
"genetics",
"and",
"genomics/gene",
"discovery",
"genetics",
"and",
"genomics/gene",
"expression",
"genetics",
"and",
"genomics/functional",
"genomics",
"molecular",
"biology/rna",
"splicing",
"developmental",
"biology/developmental",
"molecular",
"mechanisms"
] |
2010
|
PPS, a Large Multidomain Protein, Functions with Sex-Lethal to Regulate Alternative Splicing in Drosophila
|
Morphological transitions and metabolic regulation are critical for the human fungal pathogen Candida albicans to adapt to the changing host environment . In this study , we generated a library of central metabolic pathway mutants in the tricarboxylic acid ( TCA ) cycle , and investigated the functional consequences of these gene deletions on C . albicans biology . Inactivation of the TCA cycle impairs the ability of C . albicans to utilize non-fermentable carbon sources and dramatically attenuates cell growth rates under several culture conditions . By integrating the Ras1-cAMP signaling pathway and the heat shock factor-type transcription regulator Sfl2 , we found that the TCA cycle plays fundamental roles in the regulation of CO2 sensing and hyphal development . The TCA cycle and cAMP signaling pathways coordinately regulate hyphal growth through the molecular linkers ATP and CO2 . Inactivation of the TCA cycle leads to lowered intracellular ATP and cAMP levels and thus affects the activation of the Ras1-regulated cAMP signaling pathway . In turn , the Ras1-cAMP signaling pathway controls the TCA cycle through both Efg1- and Sfl2-mediated transcriptional regulation in response to elevated CO2 levels . The protein kinase A ( PKA ) catalytic subunit Tpk1 , but not Tpk2 , may play a major role in this regulation . Sfl2 specifically binds to several TCA cycle and hypha-associated genes under high CO2 conditions . Global transcriptional profiling experiments indicate that Sfl2 is indeed required for the gene expression changes occurring in response to these elevated CO2 levels . Our study reveals the regulatory role of the TCA cycle in CO2 sensing and hyphal development and establishes a novel link between the TCA cycle and Ras1-cAMP signaling pathways .
The ubiquitous tricarboxylic acid ( TCA ) cycle is a central pathway for the metabolism of carbon sources , lipids , and amino acids , and provides a major energy source for the cell under aerobic conditions . It is composed of a set of enzymes , which are required for the generation of NADH and FADH2 electron donors for use in the electron transport chain ( ETC ) . The TCA cycle is also involved in the regulation of a wide range of other biological processes [1] and it is known that mutations in enzymes of the TCA cycle are associated with several neurological disorders and cancers in humans [2] . Due to its importance in energy metabolism and cellular functions , the TCA cycle has been intensively investigated in many different organisms including microbes , humans , plants , and model organisms [3–6] . Little is known , however , about the roles of the TCA cycle in the context of the biology and pathogenesis of the human fungal pathogen Candida albicans . C . albicans causes not only superficial diseases , but also systemic and disseminated infections in immunocompromised individuals [7 , 8] . It has the capacity to colonize virtually every human tissue , but typically exists as a benign commensal in the mouth , gut , and genitourinary tracts of healthy adults [8] . Metabolic plasticity is critical for both the pathogenic and commensal life styles of this fungus . Lorenz and Fink ( 2001 ) demonstrated that the glyoxylate cycle regulates macrophage phagocytosis and virulence of C . albicans , whereby disruption of the glyoxylate pathway prevents the growth of C . albicans inside macrophages by blocking nutrient availability [9] . During mucosal infections and invasive growth , the TCA cycle and fatty acid β-oxidation-related genes are upregulated [10 , 11] . White and opaque cells , which represent two heritable cell types and exhibit distinct virulence profiles in mucosal and systemic infections , differ in their metabolic profiles [12] . Opaque cells , which adopt an oxidative metabolic profile , are more virulent in mucosal infections , whereas white cells , which adopt a fermentative metabolic profile , are more virulent in systemic infections [12 , 13] . In addition , a recent proteomics study indicates that the TCA cycle is involved in the control of antifungal tolerance and biofilm formation [14] . The ability to form hyphae is another important biological feature of C . albicans [15 , 16] . The mitogen-activated protein kinase ( MAPK ) and cAMP signaling pathways are two major players in the control of hyphal growth in C . albicans [15–17] . Indeed , deletion of RAS1 , which encodes a small GTPase upstream of the two pathways , leads to attenuation in virulence and defects in hyphal growth under specific culture conditions [18 , 19] . Deletion of CYR1 , which encodes the sole adenylyl cyclase in C . albicans , completely blocks hyphal growth and leads to a complete loss of infectivity [20] . We recently found that both the catalytic and regulatory subunits of the cAMP-dependent protein kinase A ( PKA ) are not essential for cell viability in C . albicans [21 , 22] . However , similar to the disruption of CYR1 , inactivation of the catalytic subunit of PKA by generation of a tpk2/tpk2 tpk1/tpk1 double mutant , completely blocked hyphal development [22] . The two isoforms of the PKA catalytic subunit , Tpk1 and Tpk2 play redundant and distinct roles in a number of biological processes , such as filamentous growth and responses to cellular stresses [23 , 24] . Transcription factors Efg1 and Flo8 are downstream of the cAMP signaling pathway and are essential for filamentous growth under a number of conditions [25 , 26] . It is also known that alterations of the cAMP signaling pathway have a remarkable influence on the transcriptional profile of metabolism [22 , 27] . Moreover , the activation of the Ras1-cAMP signaling pathway is associated with increased cellular ATP levels and mitochondrial activity in both C . albicans and Saccharomyces cerevisiae [28 , 29] . Host-related environmental cues , such as temperature and CO2 , are important factors in regulating morphological transitions in C . albicans [15 , 30]; for example , high temperatures and elevated levels of CO2 promote hyphal growth . There is evidence in support of the idea that cAMP-dependent and -independent pathways are involved in the regulation of CO2-induced hyphal growth [31] , however the cAMP-independent pathway is yet to be identified . It has been shown that the AGC kinase Sch9 is involved in the regulation of hypoxia and CO2 sensing through the control of the transcription factors Czf1 and Ace2 and lipid/Pkh1/2 signaling in C . albicans [32–34] . The bZIP transcription factor Rca1 regulates the expression of the carbonic anhydrase-encoding gene NCE103 , which may represent a cAMP-independent pathway of CO2 sensing in C . albicans [35] . Sfl1 and Sfl2 , two conserved heat shock factor-type transcription factors , function antagonistically to control morphological transitions in C . albicans [36–40] . Sfl1 represses filamentous growth , whereas Sfl2 acts as a positive regulator of filamentous growth . Sfl1 and Sfl2 can also act as both transcriptional repressors and activators of certain target genes . Together , Sfl1 and Sfl2 coordinately regulate hyphal development by controlling the expression of hyphal specific genes ( HGS ) and other regulators , such as Efg1 and Ndt80 , in C . albicans [40] . As a Crabtree-negative and commensal organism , it is critical for C . albicans to control metabolic and transcriptional processes to adapt to the host environment . As shown in Fig 1 , eight enzymes encoded by fifteen genes are involved in the TCA cycle , and isocitratelyase ( Icl1 ) , malate synthase ( Mls1 ) , and malate dehydrogenase ( Mdh1-3 ) function in the glyoxylate bypass , for a total eighteen genes involved in this major metabolic pathway in C . albicans . To systemically characterize the roles of the TCA cycle and the glyoxylate bypass in adaption to the host environment , we generated nineteen deletion mutants of the related genes . Our results indicate that through the coordination of the cAMP signaling pathway and the heat shock-type transcription factor Sfl2 , the TCA cycle regulates hyphal development and CO2 sensing in C . albicans .
To systemically investigate the biological functions of the TCA cycle and the glyoxylate bypass in C . albicans , we generated 17 homozygous deletion mutants of genes encoding related metabolic enzymes using traditional fusion PCR strategies ( Fig 1 ) [41] . In addition , we also deleted PCK1 and PYC2 , which encode the phosphoenolpyruvate carboxykinase and pyruvate carboxylase , respectively , and control the cellular level of oxaloacetate , an intermediate of the TCA cycle . Since the TCA cycle is the central pathway for carbon and cellular energy metabolism , we examined the growth of these mutants on YNB media containing different carbon sources using serial dilution assays . As shown in S1 Fig , mutants of CIT1 , ACO1 , and MDH1-1 , encoding citrate synthase , aconitase , and malate dehydrogenase , respectively , had no obvious growth on all tested media . Deletion of α-ketoglutarate dehydrogenase-encoding genes , KGD1 and KGD2 , and succinate dehydrogenase-encoding genes , SDH2 and SDH3 , decreased growth rates on fermentable carbon source-containing media ( YNB + glucose , GlcNAc , sucrose , and fructose ) but completely blocked cell growth on YNB , YNB + amino acids , YNB + glycerol , or YNB + ethanol media . Deletion of the isocitrate dehydrogenase-encoding genes IDH1 and IDH2 , the putative succinate dehydrogenase-encoding gene SDH4 , and the fumarate hydratase-encoding gene FUM12 decreased growth on YNB , YNB + amino acids , YNB + glycerol , and YNB + ethanol media . Inactivation of the TCA cycle resulted in the increased activity of the glyoxylate bypass and pyruvate carboxylase . Q-RT-PCR assays indicate that compared to that in the WT control , the expression levels of ICL1 and MLS1 were elevated 1 . 5 to 3 . 0-fold in the idh1/idh1 and idh2/idh2 mutants and the expression of PYC2 was increased in the cit1/cit1 mutant 1 . 5 to 3 . 0-fold . However , deletion of ACO2 and the glyoxylate bypass-specific enzyme encoding genes MLS1 or MDH1-3 had no obvious effects on the utilization of different carbon sources . To further quantitate the growth rates of the mutants , we cultured the strains in several liquid medium conditions at both 30°C and 37°C . The growth curves are presented in S2 and S3 Figs and the growth abilities are summarized in S1 Table . Our results indicate that the TCA cycle , but not the glyoxylate bypass , plays a critical role in the utilization of both fermentable and nonfermentable carbon sources for energy metabolism in C . albicans . Hyphal development is one of the most important features of C . albicans and is associated with virulence [16] . Taking advantage of the TCA cycle mutants generated in this study , we performed hyphal growth assays under twelve culture conditions in air and in the presence of 5% CO2 ( Table 1 ) . All TCA and glyoxylate cycle-related mutants were able to grow on Spider and YPD media , although some mutants exhibited a reduced growth rate ( Table 1 and S1 Table , S2 and S3 Figs ) . Therefore , neither the TCA nor glyoxylate cycle is essential for cell growth in C . albicans in rich media or in the presence of all essential nutrients . To elucidate the TCA-dependent CO2 sensing mechanism in C . albicans , we examined the transcriptional levels of key genes of the TCA cycle and Ras1-cAMP pathways . As shown in Fig 3A and 3B , the relative expression levels of the TCA cycle-related genes ( CIT1 , ACO1 , IDH1 , IDH2 , KGD1 , KGD2 , SDH2 , SDH3 , and MDH1-1 ) and the cAMP signaling pathway genes ( RAS1 , CYR1 , TPK1 , and TPK2 ) were increased in 5% CO2 relative to air on YPD medium , suggesting that CO2 has an activating effect on both pathways . As expected , the relative expression levels of ECE1 and HWP1 , two hyphal-specific genes , were increased in the WT strain but not in the cit1/cit1 , aco1/aco1 , sdh3/sdh3 , and mdh1-1/mdh1-1 mutants in response to 5% CO2 relative to that in air ( Fig 3C and 3D ) . The cellular energy state regulates many biological processes including morphologic transitions through the Ras1-cAMP pathway in C . albicans [29] [17] . The TCA cycle is a central metabolic pathway that produces the reducing factors , NADH and FADH2 , for the subsequent production of ATP through the ETC . We , therefore , examined intracellular ATP levels in the WT and TCA cycle mutants . As demonstrated in Fig 4A , the TCA cycle mutants ( such as kgd1/kgd1 , kgd2/kgd2 , sdh2/sdh2 , and sdh3/sdh3 ) , which had decreased hyphal growth abilities under several culture conditions , also showed relatively low levels of intracellular ATP compared to the WT . However , the idh2/idh2 mutant , which showed a slightly reduced hyphal growth , had a relatively high level of intracellular ATP in air . The intracellular ATP level is correlated with the activation of Ras1 in C . albicans [29]; the GTP-bound Ras1 protein represents an activated form . Western blot and IP assays demonstrated that the level of GTP-Ras1 is notably lower in the TCA cycle mutants compared to that of the WT control ( Fig 4B ) . Consistently , a reduction of intracellular cAMP levels was observed in the corresponding TCA cycle mutants , including cit1/cit1 , idh1/idh1 , idh2/idh2 , kgd1/kgd1 , kgd2/kgd2 , sdh2/sdh2 , sdh3/sdh3 , and mdh1-1/mdh1-1 ( Fig 4C ) . To further characterize the regulatory relationship between the Ras1-cAMP pathway and the TCA cycle , we generated a set of Ras1-cAMP pathway-constitutively active strains by overexpressing the activating form of RAS1 ( RAS1V13 ) or by deleting the high-affinity cyclic nucleotide phosphodiesterase-encoding gene , PDE2 , in the TCA cycle mutants . We successfully obtained the RAS1V13-overexpressing strains in the kgd1/kgd1 , kgd2/kgd2 , and sdh2/sdh2 mutants and successfully deleted PDE2 in five mutants ( idh1/idh1 , idh2/idh2 , sdh2/sdh2 , sdh3/sdh3 , and mdh1-1/mdh1-1 ) . However , we were unable to overexpress RAS1V13 or to delete PDE2 in the remaining TCA mutants . It is possible that the constitutive activation of the Ras1-cAMP pathway may be lethal in these mutants . As shown in S7A and S8A Figs , overexpression of RAS1V13 in the kgd1/kgd1 , kgd2/kgd2 , and sdh2/sdh2 mutants had no notable effects on hyphal growth in air or in 5% CO2 . Deletion of PDE2 in the idh1/idh1 and idh2/idh2 mutants triggered hyphal growth to similar levels to that of the WT strain ( S7B Fig ) , whereas deletion of PDE2 in the sdh2/sdh2 , sdh3/sdh3 , and mdh1-1/mdh1-1 mutants had no obvious effect on the induction of hyphal growth in air or in 5% CO2 ( S7B and S8B Figs ) . These results demonstrate that some components of the TCA cycle are required for Ras1-cAMP pathway-mediated hyphal growth in C . albicans . Taking advantage of a set of homozygous deletion mutants recently generated in our lab [22] , we evaluated the role of the Ras1-cAMP pathway in CO2-induced hyphal growth on YPD medium . As shown in Fig 5A , the cyr1/cyr1 , tpk1/tpk1 , and double tpk2/tpk2 tpk1/tpk1 ( t2t1 ) mutants failed to undergo hyphal growth under both conditions , while the ras1/ras1 and tpk2/tpk2 mutants behaved as the WT control . These results suggest that the adenylyl cyclase , Cyr1 , and the PKA catalytic subunit , Tpk1 , are required for CO2-induced hyphal growth under this culture condition in C . albicans . Given the similar phenotypes of the TCA cycle and the Ras1-cAMP pathway mutants in response to elevated CO2 levels , we next examined the transcriptional levels of three representative genes of the TCA cycle , CIT1 , IDH1 , and MDH1-1 , in the WT , ras1/ras1 , cyr1/cyr1 , tpk1/tpk1 , tpk2/tpk2 , and double tpk2/tpk2 tpk1/tpk1 mutants by Q-RT-PCR . As shown in Fig 5B , deletion of TPK2 had no significant effects on the CO2-induced expression of CIT1 , IDH1 , and MDH1-1 , whereas deletion of RAS1 , CYR1 , TPK1 , or both TPK genes severely reduced ( and in some cases completely abolished ) the CO2-induced expression of CIT1 , IDH1 , and MDH1-1 . These results suggest that Tpk1 , but not Tpk2 , of the Ras1-cAMP pathway , plays a major role in the regulation of the TCA cycle and CO2 sensing in C . albicans . The TCA cycle and Ras1-cAMP pathways inter-regulate each other and may control hyphal growth and CO2 sensing in a coordinate manner . To reveal the transcriptional regulatory mechanisms of the TCA cycle and CO2-induced hyphal growth , we examined approximately 30 homozygous transcription factor deletion mutants for morphological changes in air and in 5% CO2 . As shown in Fig 6A , we identified five transcription factor mutants ( brg1/brg1 , efg1/efg1 , flo8/flo8 , ndt80/ndt80 , and sfl2/sfl2 ) that were unable to undergo filamentous growth in 5% CO2 . Q-RT-PCR assays demonstrated that the transcriptional levels of BRG1 , EFG1 , FLO8 , SFL2 , but not NDT80 , were significantly increased under the high CO2 condition , relative to those in air ( Fig 6B ) . The relative expression levels of SFL2 increased in response to 5% CO2 after 8 or 24 hours of growth at 30°C ( Fig 6C ) . Further experiments demonstrated that the transcriptional levels of three TCA cycle-related genes , CIT1 , IDH1 , and MDH1-1 , were significantly increased in response to 5% CO2 in the WT and brg1/brg1 strains , but not in the ndt80/ndt80 , efg1/efg1 , and sfl2/sfl2 mutants ( Fig 7 ) . CIT1 was also significantly increased in 5% CO2 in the flo8/flo8 mutant . Compared to the WT strain , the strains overexpressing EFG1 and SFL2 showed more robust hyphal growth and increased expression of CIT1 and MDH1-1 in 5% CO2 , whereas overexpression of BRG1 promoted hyphal growth , but did not induce the expression of the TCA cycle-related genes ( Fig 8A and 8B ) . Actually , overexpression of BRG1 had a suppressing effect on the transcription of CIT1 , IDH1 , and MDH1-1 ( Fig 8B ) . These results indicate that Efg1 and Sfl2 play major roles in the transcriptional regulation of TCA cycle and CO2-mediated hyphal growth . Overexpression of TPK1 increased the transcriptional expression of MDH1-1 ( Fig 8B ) and had a notable stimulating effect on hyphal growth in the presence of 5% CO2 ( Fig 8A ) . These results confirm that Tpk1 plays major roles in the regulation of the TCA cycle and CO2 sensing , possibly through the transcription factors Efg1 and Sfl2 . The adenylyl cyclase Cyr1 is an important sensor of CO2 and Efg1 is a downstream transcription factor of the Ras1-cAMP pathway [25 , 42] . It is , therefore , reasonable that Efg1 may play key roles in TCA cycle- and CO2-mediated hyphal growth in C . albicans . To establish a link between the Ras1-cAMP pathway and the Sfl2 transcription factor , we performed Q-RT-PCR assays on a set of overexpressing and deletion strains of this pathway . As demonstrated in Fig 8C , the expression of SFL2 was induced in the WT , cyr1/cyr1 , and tpk2/tpk2 strains but not in the ras1/ras1 , tpk1/tpk1 , tpk2/tpk2 tpk1/tpk1 ( t2t1 ) , and efg1/efg1 mutants in response to 5% CO2 . These results suggest that the Ras1-cAMP pathway directly or indirectly regulates CO2-induced SFL2 expression and that Tpk1 and Efg1 play major roles in this regulation . We next performed RNA-Seq analysis to elucidate the function of Sfl2 in CO2 sensing in C . albicans . As mentioned earlier , CO2 is a potent inducer of hyphal formation [42] . To identify CO2-regulated genes in the early phase of hyphal induction , prior to cell fate commitment to the hyphal form , we incubated C . albicans cells of the WT and sfl2/sfl2 mutants on YPD medium in air or 5% CO2 for 22 hours at 37°C ( Fig 9A ) . This time point was chosen since cells at this stage are in early exponential growth and are not yet beginning to form hyphae . Therefore , most genes identified here should be CO2-responsive , and gene alterations resulting from hyphal growth should be trivial . As shown in Fig 9B , there were 122 CO2-upregulated and 213 CO2-downregulated genes in the WT , whereas there were only 25 CO2-upregulated and 11 CO2-downregulated genes in the sfl2/sfl2 mutant ( using a 1 . 5-fold cut-off ) . This remarkable difference in the number of differentially expressed genes between the WT and sfl2/sfl2 mutant strains suggests that Sfl2 plays a fundamental role in the transcriptional control of CO2-regulated genes . CO2-upregulated genes in the WT include the following ( using a 1 . 5-fold cut-off ) : ( 1 ) Genes related to the TCA cycle ( e . g . , CIT1 , ACO1 , ACO2 , SDH2 , and SDH3 ) . This result is consistent with our Q-RT-PCR analysis in which C . albicans cells were incubated in 5% CO2 for an extended period of time ( three days , Fig 3 ) . ( 2 ) Genes involved in cell adhesion and filamentation ( e . g . , orf19 . 5126 , MET4 , IHD1 , MSB1 , MSB2 , and CCC1 ) . ( 3 ) Genes responsive to stress and drugs ( e . g . , GPX2 , ERG10 , SSA2 , GRX3 , and AHA1 ) . ( 4 ) Amino acid synthesis-related genes ( e . g . , ARO10 , ARO3 , SAM4 , PRO2 , and HIS7 ) . ARO genes are associated with the ehrlich pathway and aromatic amino acid synthesis; the TCA cycle may regulate these processes through its intermediate metabolites . ( 5 ) Genes encoding transcription factors ( e . g . , WOR2 , WOR3 , ZCF27 , TEC1 , and EFG1 ) . Wor2 , Wor3 , and Efg1 are key regulators of white-opaque switching in C . albicans . Tec1 and Efg1 are well known for their involvement in the regulation of hyphal growth [30] . We also identified a set of CO2-downregulated genes in the WT . Carbonic anhydrase catalyzes the hydration reaction of CO2 . As expected , the carbonic anhydrase-encoding gene , NCE103 , was downregulated in 5% CO2 . A number of metabolism-related genes were downregulated in 5% CO2 , for example , the glyoxylate cycle-specific genes ( MLS1 and ICL1 ) , fermentative metabolism-related genes of sugars ( HGT1 , HGT8 , HGT19 , PCK1 , ADH5 , IFE1 , and IFE2 ) , and fatty acid metabolism-related genes ( POX1-3 , ACB1 , FDH1 , POT1 , and PEX11 ) . Consistent with the filament-inducing role of CO2 , several transcriptional repressor genes ( CUP9 , NRG1 , and RFG1 ) were downregulated in 5% CO2 . Many of these differentially expressed genes , especially transcription factor-encoding genes , have been reported as Sfl2-binding targets [40] , suggesting that Sfl2 may function through the direct regulation of these hyphal growth regulators . In the sfl2/sfl2 mutant , genes of known function in response to elevated levels of CO2 include the following: ( 1 ) Energy and fatty acid metabolism-related genes ( ATP6 , ATP8 , IMG2 , and FAD3 ) and two stress and drug response genes ( CDR4 and ARC18 ) were upregulated . ( 2 ) Interestingly , cell wall and hyphal growth-related genes ( PGA62 , GPD2 , ALS1 , and CHT2 ) were downregulated . The expression of these genes may be independent of the regulation of Sfl2 in C . albicans . We next compared the differentially expressed genes between the WT and sfl2/sfl2 mutant ( Fig 9B and 9C ) . Using a 1 . 5-fold cut-off , there are 1 , 419 and 1 , 749 genes differentially expressed between the WT and sfl2/sfl2 mutant in air and in 5% CO2 , respectively . However , when a 2-fold cut-off is used , the numbers are dramatically decreased to 400 and 607 , in air and in 5% CO2 , respectively ( S1 Dataset ) . We note that in general , there are about 30% more differentially expressed genes in 5% CO2 than in air . This difference is likely due to the different responses between the WT and sfl2/sfl2 mutant to elevated CO2 levels . Indeed , the elevated CO2-levels had a much weaker effect on the global gene expression profile of the sfl2/sfl2 mutant compared to WT ( Fig 9B ) . To further characterize the regulatory mechanisms of Sfl2 , we performed ChIP-qPCR assays to identify target genes directly regulated by Sfl2 . The promoters of all TCA cycle genes were examined . We found that Sfl2 specifically bound to the promoters of CIT1 and SDH2 in 5% CO2 but not in air ( Fig 10A ) . The enrichment levels for Sfl2 binding in the promoters of IDH1 and MDH1-1 were weak both in air and in 5% CO2 ( Fig 10B ) . We further found that Sfl2 bound to the promoters of EFG1 , SFL1 , and NRG1 both in air and in 5% CO2 ( Fig 10C ) . Overall , the enrichment for binding by Sfl2 in 5% CO2 was higher than that in air . We also found some potential Sfl2-binding sites in the promoters of CIT1 , SDH2 , IDH1 , MDH1-1 , EFG1 , NRG1 , and SFL1 according to the consensus sequence ( AATAGAA ) identified by Znaidi et al . ( 2013 ) [40] . Our results suggest that Sfl2 not only directly binds to the promoters of TCA cycle-related genes , but also indirectly regulates the TCA cycle and CO2-induced hyphal development by binding to the promoters of other transcription factors .
The TCA cycle is the second stage of respiration after glycolysis . It produces ATP and the electron carriers , NADH and FADH2 , for the ETC . We found that disruption of key proteins of the TCA cycle ( e . g . , Cit1 , Aco1 , Kgd1 , Kgd2 , or Mdh1-1 ) led to severe growth defects on non-fermentative carbon sources ( S1 , S2 and S3 Figs ) , which can only be metabolized to produce energy through respiration . Some metabolic enzymes of the TCA cycle are encoded by two or three genes . For example , IDH1 and IDH2 encode two subunits of isocitrate dehydrogenase , and SDH2 , SDH3 , and SDH4 encode three succinate dehydrogenase subunits ( Fig 1 ) . The idh1/idh1 and idh2/idh2 mutants displayed similar growth rates to the WT strain in all tested media . However , both the iron-sulfur subunit of succinate dehydrogenase , Sdh2 , and the flavoprotein subunit , Sdh3 , are required for efficient utilization of non-fermentative carbon sources , whereas Sdh4 does not appear to play a role in this regulation ( S1 , S2 and S3 Figs ) . Of note , the SDH complex is also a component of the ETC . These results suggest that different subunits or isoforms of TCA cycle enzymes may play redundant and distinct roles in C . albicans . Deletion of CIT1 and ACO1 genes , encoding citrate synthase and aconitase enzymes , respectively , resulted in major growth defects even in media containing fermentative sugars , such as glucose and sucrose ( S1 Fig ) . This growth defect could be due to the accumulation of toxic intermediate metabolites , such as acetic acid . Our results suggest that the TCA cycle regulates carbon source utilization and energy metabolism in C . albicans . Consistent with a previous study , deletion of MCU1 , which encodes a mitochondrial protein required for the function of the TCA cycle , also caused severe defects in carbon source utilization and hyphal growth in C . albicans [47] . In minimal media , most C . albicans TCA cycle mutants exhibited similar growth phenotypes to their orthologous mutants in S . cerevisiae , indicating the conserved features of the TCA cycle . However , the idh1/idh1 , idh2/idh2 , sdh4/shd4 , fum11/fum11 , and fum12/fum12 mutants of C . albicans were able to grow on amino acid or non-fermentable carbon source media ( minimal media , S1 Fig ) , whereas the idh1 , idh2 , sdh4 , and fum1 mutants of S . cerevisiae exhibited severe growth defects under similar culture conditions [48 , 49] . These results imply that , as a commensal of humans , C . albicans is better equipped at utilizing diverse carbon sources than S . cerevisiae . Moreover , given its central position in cellular metabolism , including its roles in lipid and amino acid synthesis , the TCA cycle may also regulate hyphal development through other metabolic intermediates and pathways . For example , the enzymes citrate synthase , aconitase , and isocitrate dehydrogenase are responsible for α-ketoglutarate synthesis , which is required for the production of glutamate , a precursor for the amino acids arginine , proline , and glutamic acid . Indeed , mutants lacking aconitase in S . cerevisiae exhibit growth defects in minimal media lacking glutamate [50] . Consistently , we observed that the cit1/cit1 and aco1/aco1 mutants of C . albicans were able to grow on rich medium ( YPD ) but were unable to grow on minimal medium ( Lee’s glucose and YNB , Fig 2 , S1 Fig and S1 Table ) . The Ras1-cAMP pathway is the central regulator of hyphal growth in C . albicans [17 , 51] . The adenylyl cyclase Cyr1 catalyzes the conversion of ATP to the second messenger cAMP . Grahl et al . ( 2015 ) demonstrated that the ATP pool serves as a “checkpoint” in the activation of Ras signaling under filament-inducing conditions [29] . When the intracellular ATP level is low , the activated form , GTP-Ras1 , turns over to the inactivated form , GDP-Ras1 , in a Cyr1-Ira2 dependent manner . The mitochondrial respiratory chain provides a major source of ATP for the cell . Mutants defective in the ETC are unable to establish a high intracellular ATP level and thus fail to undergo hyphal growth [29] . Consistently , here we showed that disruption of the TCA cycle leads to reduced intracellular ATP levels and defects in hyphal growth . This is not surprising since the TCA cycle generates NADH and FADH2 , which are required for ATP production during subsequent ETC-mediated oxidation events . The disruption of TCA cycle-related genes had notable effects on intracellular ATP levels and Ras GTP-binding ( Fig 4 ) . Decreased GTP-Ras1 levels are directly related to the inactivation of cAMP signaling and hyphal growth in C . albicans . The TCA cycle is required for utilizing non-fermentable carbon sources to generate energy . We observed that there is a correlation between the ability to undergo hyphal growth and the ability to utilize non-fermentable carbon sources ( Fig 1 , S1 , S2 and S3 Figs , Table 1 and S1 Table ) . Constitutive activation of the Ras1-cAMP signaling pathway by overexpressing RAS1V13 or by deleting PDE2 in TCA cycle mutants induced hyphal growth in the idh1/idh1 and idh2/idh2 mutants , but not in other TCA cycle mutants in air or in 5% CO2 . These results suggest that the TCA cycle regulates CO2 sensing and hyphal growth in C . albicans through modulation of intracellular ATP levels and through the activation of Ras1 signaling . Artificially activated-Ras1-cAMP signaling could not suppress the hyphal growth defect of the TCA cycle mutants , suggesting that this cycle is required for basal levels of hyphal development in C . albicans . An alternative possibility is that the TCA cycle and Ras1/cAMP signaling pathways may function independently on hyphal growth . Although disruption of the TCA cycle blocked or attenuated hyphal growth on Lee’s glucose medium at 37°C and Lee’s GlcNAc medium at 30°C , the TCA cycle mutants were still able to form hyphae on Lee’s GlcNAc , YPD + serum and Spider media at 37°C ( Table 1 and S4 Fig ) , suggesting that the observed hyphal growth defects are condition-dependent . CO2 is an end product of respiratory metabolism as well as a potent inducer of hyphal growth in C . albicans [42] . CO2 functions through the activation of adenylyl cyclase and through an unknown pathway [31] . Here we demonstrate that some components of the TCA cycle are required for CO2-induced hyphal growth in C . albicans ( Table 1 and Fig 2 and S5 Fig ) . CO2 promotes the transcriptional expression of TCA cycle genes possibly through the activation of the cAMP signaling pathway ( Figs 3 , 4 and 5 ) . The adenylyl cyclase Cyr1 and catalytic subunit isoform Tpk1 , but not Tpk2 , play critical roles in CO2-induced hyphal growth and expression of TCA cycle genes ( Fig 5 ) . In the model yeast S . cerevisiae , high levels of CO2 can also induce the transcription of respiratory metabolism-related genes and can cause an increase in intracellular ATP demand [52 , 53] , suggesting that the regulatory mechanisms of CO2-induced gene expression are conserved . This metabolic response to increased CO2 levels may benefit C . albicans as both a commensal and a pathogen . Given the relative levels of oxygen ( 1% or lower ) and high levels of CO2 ( 4 . 5–30% ) in host niches ( e . g . , the lower gastrointestinal tract ) , elevated CO2 levels would facilitate respiratory metabolism in this Crabtree-negative species , which may be an adaptive mechanism for existing as a commensal or pathogen in the host that depends on environmental cues . As mentioned earlier , the Ras1-cAMP pathway regulates the TCA cycle and mitochondrial metabolic activity in C . albicans . CO2 produced by respiratory metabolism could function as an intracellular and intercellular signal to activate the Ras1-cAMP pathway . Indeed , it has been demonstrated that CO2 can act as an intercellular signal for cell-cell communication and self-induced hyphal growth in C . albicans [43] . Therefore , we propose that CO2 functions to link the TCA cycle and Ras1-cAMP pathways . We identified Sfl2 and Efg1 as two major transcriptional regulators of CO2-induced hyphal growth and the TCA cycle in C . albicans ( Figs 6 , 7 and 8 ) . Efg1 is a downstream transcription factor of the Ras1-cAMP pathway and plays a global role in transcriptional regulation in a number of important developmental processes in C . albicans [24–26 , 54] . Deletion of EFG1 also has fundamental consequences on metabolism , likely due to perturbations of this global transcriptional profile . Moreover , Efg1 and Ace2 are also involved in the regulation of metabolism in C . albicans through Bcr1 and Brg1 [55] . It has been showed that Efg1 induces the expression of glycolytic genes and represses the expression of oxidative genes [56] . We have reported that Flo8 plays a critical role in CO2-induced hyphal growth and white-opaque switching in C . albicans [31] . In this study , we also found that deletion of FLO8 or BRG1 , encoding a GATA-type transcription factor , resulted in severe defects in hyphal growth in response to CO2 ( Fig 6 ) . However , deletion of BRG1 had no obvious effects on the transcriptional expression of TCA cycle genes ( Fig 7 ) . Since elevated CO2 levels promote the expression of SFL2 , which encodes a heat shock factor-type transcription factor [38 , 39] , we chose to explore the mechanisms of this regulation . Consistently , deletion of SFL2 led to severe hyphal growth defects and the failure to induce TCA cycle gene expression in high CO2 conditions ( Figs 6 and 7 ) . ChIP assays under these conditions demonstrated that Sfl2 bound to the promoters of CIT1 and SDH2 ( Fig 10 ) . RNA-Seq analysis further demonstrated that Sfl2 is essential for CO2-altered gene expression at the global transcriptome level . These results suggest that Sfl2 plays critical roles in CO2-induced responses in C . albicans . Transcriptional analysis demonstrated that the Ras1-cAMP pathway and Efg1 play important roles in the control of SFL2 expression in response to high CO2 levels ( Fig 8 ) . Our results indicate that the Tpk1 catalytic subunit , but not the Tpk2 subunit , plays a major role in this regulation . Znaidi et al . ( 2013 ) have shown that Sfl2 directly controls the expression of a series of positive hyphal growth regulators , such as UME6 and TEC1 , as well as negative hyphal growth regulators , such as NRG1 and RFG1 , in C . albicans [40] . Sfl2 also physically interacts with Efg1 [40] , a major transcriptional regulator of morphogenesis . The expression of SFL2 was significantly increased in the efg1/efg1 mutant in air ( Fig 8C ) , suggesting that Efg1 regulates SFL2 at the transcriptional level . We found that Sfl2 is highly enriched at the promoters of SFL1 , EFG1 and NRG1 and several TCA-related genes ( Fig 10 ) . Consistent with these results , previous studies found that deletion of SFL2 blocked CO2–induced hyphal growth [38] and overexpression of SFL2 promoted hyphal growth in a Flo8- and Efg1-dependent manner [39] . Interestingly , the SFL2 orthologue in C . dubliniensis , a species closely related to C . albicans , is highly divergent from CaSFL2 [38] . This divergence may account for the lack of observed CO2 responses in C . dubliniensis . In summary , the transcription factor Sfl2 plays a central role in the transcriptional control of global gene expression and hyphal growth in response to elevated CO2 levels . In addition , the TCA cycle , integrated with the Ras1-cAMP signaling pathway and specific transcription factors , is also important for CO2 sensing in C . albicans . Together , CO2 and ATP may function as molecular links between the TCA cycle and Ras1-cAMP signaling pathways . The conserved Ras1-cAMP pathway functions as an important regulator of respiratory activity in the model yeast S . cerevisiae [28 , 57 , 58] . Activation of this pathway increases the mitochondrial enzyme content and the transcriptional levels of genes encoding respiratory metabolism [57] . In turn , dysfunctional mitochondria modulate the Ras1-cAMP signaling pathway and affect morphological transitions in S . cerevisiae [58] . In this study , we demonstrate that the TCA cycle and Ras1-cAMP signaling pathways coordinately regulate filamentous growth and CO2 sensing in C . albicans . ATP generated from respiratory metabolism is required for the synthesis of the second messenger cAMP and for formation of GTP-Ras1 . Environmental CO2 or CO2-derived from the TCA cycle activates the Ras1-cAMP signaling pathway , which regulates the TCA cycle through the transcription factors , Efg1 and Sfl2 . These two transcription factors also control hyphal growth in C . albicans . Our results suggest that in C . albicans , the TCA cycle and Ras1-cAMP signaling pathways regulate each other , and that the transcription factors Efg1 and Sfl2 and the small molecules CO2 and ATP function as linkers between the two pathways ( Fig 11 ) . However , under hypoxic conditions , the regulatory mechanism could be different . It has been shown that Efg1 regulates the expression of a different set of genes under hypoxic conditions compared to those of normoxic conditions [55 , 56] .
All strains used in this study are listed in S2 Table . YPD medium ( 20 g/L glucose , 20 g/L peptone , 10 g/L yeast extract ) was used for routine growth of C . albicans and for intracellular ATP detection and Ras1-GTP activity assays . YPD , YPD + 10% fetal bovine serum , modified Lee’s glucose , Lee’s GlcNAc [59] , Spider [60] , and YPD agar + fetal bovine serum media were used to assess hyphal formation . For hyphal induction assays in S4 Fig , cells initially grown on YPD medium plates at 30°C were collected , washed , and inoculated into liquid YPD + 10% serum medium or plated onto solid YPD + serum medium plates . To make YPD + serum plates , about one mL of FBS was spread on the surface of YPD agar . For all solid media cultures , cellular morphologies were examined to assess hyphal growth . All experiments were performed under normoxic conditions . Media for spot growth assays: A ) yeast nitrogen base ( YNB with ( NH4 ) 2SO4 ) agar containing 2% GlcNAc , 2% glucose , 2% sucrose , 2% fructose , seven amino acids ( 1 mM of alanine or A , arginine or R , glutamine or Q , glutamic acid or E , asparagine or N , proline or P , and serine or S ) , 2% ethanol , or 2% glycerol . B ) Lee’s solid medium containing 1 . 25% GlcNAc , 1 . 25% glucose , 1 . 25% mannitol , 4% glycerol , 3% ethanol plus 2% glycerol , 2% sodium citrate . Media for growth rate assays: YPD , and YNB with ( NH4 ) 2SO4 plus 2% glucose , 2% glycerol , or 2% ethanol media . C . albicans cells of the WT strain , TCA cycle and glyoxylate bypass gene mutants were initially grown in liquid YPD to stationary phase at 30°C , and then collected and washed with PBS twice . 6 x 106 cells were inoculated into 3 mL of YPD , YNB + 2% glucose , YNB + 2% glycerol , YNB + 2% ethanol media . The cells were incubated at 37°C or 30°C with shaking at 200 rpm . Cell densities were detected at different time points . Three independent repeats were performed . Primers used in this study are listed in S3 Table . Fusion PCR strategies [41] were used to generate the TCA cycle and glyoxylate bypass gene deletion mutants . To delete the first allele , the strain SN152 was transformed with the fusion PCR product of CdARG4 flanked by 5’- and 3’-flanking fragments of the corresponding gene . The cells were plated onto SD-arginine medium for selective growth . The correct integration of transformants was verified by PCR using two pairs of oligonucleotides ( targeting gene-CHF and ARG4-CHR; ARG4-CHF and target gene-CHR ) . The heterozygous strains were then used for deleting the second allele of the corresponding gene . The cells were transformed with fusion PCR products of CdHIS1 flanked by the 5’- and 3’-fragments of corresponding genes . The transformants were selected on plates with SD medium lacking both arginine and histidine . The correct null mutants were first verified by PCR using two pairs of oligonucleotides ( target gene-CHF and HIS1-CHF; target gene-CHR and HIS1-CHR for correct genomic integration checking ) . Another pair of oligonucleotides ( target gene-orf-F and target gene-orf-R ) were used to confirmed the complete deletion of the ORF regions . A similar strategy was used to delete PCK1 and PYC2 . CdARG4 and CmLEU2 were used as the selective markers . Plasmids pSN69 , pSN52 or pSN40 ( carrying a CdARG4 , CdHIS1 and CmLEU2 gene , respectively [41] ) were used for amplification of the selective markers and C . albicans genomic DNA was used for amplification of the 5’- and 3’-flanking sequences of the gene of interest . To create the gene reconstituted plasmids , CaLEU2 was amplified from C . albicans genomic DNA and inserted into plasmid pBES116 [18] at the PstI/HindIII site , generating plasmid pBES116-LEU2 . A fragment containing the sequence of a complete corresponding gene ( 5’-UTR + ORF +3’-UTR ) was amplified and inserted into PstI-digested ( for CIT1 , ACO1 , KGD1 , KGD2 , SDH3 , SDH4 , MDH1-1 , FUM11 , FUM12 , and MLS1 ) , ClaI-digested ( for SDH2 and MDH1-3 ) , or HindIII and ClaI-digested plasmid pBES116-LEU2 ( IDH1 , IDH2 , and ACO2 ) , respectively . The gene-reconstituted plasmids were then linearized with AscI and transformed into the corresponding mutant to generate reconstituted strains . Linearized plasmids were integrated at the ADE2 locus . To construct Ras1-constitutively activated strains , plasmid pACT-RAS1V13 [61] was linearized with AscI and transformed into the strain SN152 , and TCA cycle mutants . Fusion PCR strategies were used to delete PDE2 in the WT and TCA cycle mutants [41] . To delete the first allele , the mutants were transformed with the fusion PCR product of CmLEU2 flanked by the PDE2 5’- and 3’-fragments . The second allele was deleted by transforming with caSAT1 , encoding a Candida-optimized nourseothricin-resistant gene [62] , flanked by 5’- and 3’-PDE2 fragments . A fragment containing the ORF region of SFL2 was sub-cloned into plasmid pACT1 [63] , generating overexpressing plasmid pACT-SFL2 . To construct SFL2-overexpressing strains , the plasmid were linearized with AscI and transformed into the strain SN152 . The linearized overexpressing plasmid was integrated into the ADE2 locus . For Sfl2-ChIP assays , a 13 x Myc-tagged Sfl2-expressing strain was constructed . PCR products containing the SFL2 ORF sequence and a C-terminal 13 x Myc-tag were prepared and subcloned into the EcoRV/KpnI site of pACT1 [63] , yielding plasmid pACT-SFL2-MYC . The strain SN152 was transformed with AscI-digested pACT-SFL2-MYC , generating the 13 x Myc-tagged Sfl2 strain . Intracellular ATP concentration in C . albicans cells was determined with an ATP Bioluminescence Assay Kit ( CellTiter-Glo Luminescent Cell Viability Assay , Promega , Inc . ) . C . albicans cells ( 4×106 ) were spotted onto YPD medium and cultured at 37°C in air or in 5% CO2 for 16 hours . Cells were harvested and homogenized in 1x PBS with a bead beater . A standard curve was determined using serial tenfold dilutions of ATP disodium salt ( Cat . #P1132 , Promega , Inc . ) . Results of the samples were normalized to the corresponding protein concentrations , determined by the Bradford assay ( BioRad , Inc . ) . Three independent replicates were included and the means ± standard deviations ( SD ) are presented . Student’s t tests were performed to assess the significant difference ( ** p <0 . 01 , *p <0 . 05 ) . Intracellular cAMP levels were measured with a Monoclonal Anti-cAMP Antibody Based Direct cAMP ELISA Kit ( Catalog No . 80203 , NewEastBio , Inc . ) following the manufacturer’s instructions . Briefly , 4×106 cells of C . albicans were spotted onto YPD medium and cultured at 37°C in air or in 5% CO2 for 16 hours . Cells were harvested and cell pellets were immediately frozen in liquid nitrogen . For cAMP extraction , frozen cells were thawed and resuspended in 1 ml of 0 . 1M HCl . Half of each sample was used for the determination of cell concentration and the other half was used to measure the cAMP level with the ELISA kit . Three independent replicates were included and the means ± standard deviations ( SD ) are presented . Student’s t tests were performed to assess the significant difference ( ** p <0 . 01 , *p <0 . 05 ) . Total Ras1 and GTP-bound Ras1 levels were examined according to a previous report [29] . C . albicans cells ( 4×106 ) were spotted onto YPD medium and cultured at 37°C in air for 16 hours . Cells were collected and homogenized in the Lysis/Binding/Wash Buffer ( Active Ras Pull-Down and Detection Kit , Pierce , Inc . ) . Protein concentrations were determined with the Pierce BCA Protein Assay Reagent ( Product No . 23227 ) . GTP-bound Ras1 protein was isolated using the Active Ras Pull-Down and Detection Kit ( Pierce , Inc . ) . 500μg of total protein was used for the active Ras1 pull-down assay . 20μl of the active Ras1 isolated from the pull-down assay and 10μg of total protein ( as the input control ) were separated by SDS-PAGE , and then transferred to a polyvinylidene difluoride ( PVDF ) membrane for Western blot assays with monoclonal anti-Ras clone 10 antibody ( Millipore , Inc . ) . α-Tubulin was used as a loading control . C . albicans cells were spotted or spread on YPD medium plates and cultured at 37°C in air or in 5% CO2 . Cells were harvested and total RNA was extracted for Q-RT-PCR assays . Briefly , 0 . 6 μg of total RNA per sample was used to synthesize cDNA with RevertAid Reverse Transcriptase ( Thermo Scientific , Inc . ) . Quantification of transcripts was performed in a Bio-Rad CFX96 real-time PCR detection system using SYBR green Mix ( TOYOBO , Inc . ) . The expression levels of each experimental sample were normalized to that of ACT1 . Cells of the WT and sfl2/sfl2 mutant were first grown at 25°C in liquid Lee’s glucose medium for 24 hours , then spread onto YPD medium plates and incubated at 37°C in air or in 5% CO2 for 22 hours . Colonies were harvested and total RNA was extracted as described above . RNA-Seq analysis was performed by the company Berry Genomics Co . ( Beijing ) . Approximately 10 million ( M ) reads were sequenced in each library of the samples . Briefly , mRNA was purified from total RNA using Oligo ( dT ) magnetic beads , and fragmented into small pieces ( 200–700 bp ) . The cleaved RNA fragments were primed with random hexamers and used to synthesize the first-strand and second-strand cDNA . Sequencing adapters were ligated to the cDNA fragments . The library products were then sequenced using an Illumina HiSeq 2500 V4 . Illumina software OLB_1 . 9 . 4 was used for base-calling . The raw reads were filtered by removing the adapter and low quality reads ( the percentage of low quality bases with a quality value ≤3 was >50% in a read ) . Clean reads were mapped to the genome of C . albicans SC5314 using TopHat ( version2 . 1 . 1 ) and Cufflinks ( version2 . 2 . 1 ) software [64] . Mismatches less than two bases were allowed in the alignments . Relative gene expression levelswere calculated using the FPKM ( Fragments Per kb per Million reads ) method; FPKM = 106C/ ( NL/103 ) , where “C” is the number of fragments that uniquely aligned to gene A , “N” represents the total number of fragments that uniquely aligned to all genes , and “L” is the number of bases of gene A . GO functional enrichment analysis was carried out according to GO terminology determined using the online CGD GO Term Finder tool ( http://www . candidagenome . org/cgi-bin/GO/goTermFinder ) . The Chromatin immunoprecipitation ( ChIP ) protocol was adapted from Nobile et al . ( 2012 ) [54] . C . albicans cells were grown in liquid YPD to stationary phase at 30°C , and then collected and washed with PBS twice . 5 x 106 cells were inoculated into 200 mL of YPD and cultured to OD600 = 0 . 4 . Cells ( 10 mL ) were transferred to a 9 mm-dish and treated in 5% CO2 at 37°C with shaking for 6 hours , and then fixed and cross-linked with 1% formaldehyde at room temperature . The cross-linking reaction was quenched after 20 min by adding glycine to a final concentration of 125 mM . The cells were harvested , resuspended in ice-cold lysis buffer , and homogenized with a bead beater . Sonication was performed with a Diagenode Biorupter ( 15 min , high setting , 30 sec on , 1 min off ) to obtain chromatin fragments of an average size of 500–1000 bp . The chromatin was immunoprecipitated with 2 μg of anti-Myc antibody ( Millipore , Inc . ) and protein A-Sepharose beads ( GE Healthcare ) . ChIP DNA was analyzed by quantitative real-time PCR assays . The RNA-seq dataset has been deposited into the NCBI Gene Expression Omnibus ( GEO ) portal ( accession# GSE102039 ) .
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Energy metabolism through the TCA cycle and mitochondrial electron transport are critical for the human fungal pathogen Candida albicans to survive and propagate in the host . This is , in part , due to the fact that C . albicans is a Crabtree-negative species , and thus exclusively uses respiration when oxygen is available . Here , we investigate the roles of the TCA cycle in hyphal development and CO2 sensing in C . albicans . Through the use of ATP and the cellular signaling molecule CO2 , the TCA cycle integrates with the Ras1-cAMP signaling pathway , which is a central regulator of hyphal growth , to govern basic cellular biological processes . Together with Efg1 , a downstream transcription factor of the cAMP signaling pathway , the heat shock factor-type transcription regulator Sfl2 controls CO2-induced hyphal growth in C . albicans . Deletion of SFL2 results in the loss of global transcriptional responses under elevated CO2 levels . Our study indicates that the TCA cycle not only occupies the central position of cellular metabolism but also regulates other biological processes such as CO2 sensing and hyphal development through integration with the Ras1-cAMP signaling pathway in C . albicans .
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2017
|
Integration of the tricarboxylic acid (TCA) cycle with cAMP signaling and Sfl2 pathways in the regulation of CO2 sensing and hyphal development in Candida albicans
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microRNAs ( miRNAs ) are a class of endogenous regulatory RNAs that play a key role in myriad biological processes . Upon transcription , primary miRNA transcripts are sequentially processed by Drosha and Dicer ribonucleases into ~22–24 nt miRNAs . Subsequently , miRNAs are incorporated into the RNA-induced silencing complexes ( RISCs ) that contain Argonaute ( AGO ) family proteins and guide RISC to target RNAs via complementary base pairing , leading to post-transcriptional gene silencing by a combination of translation inhibition and mRNA destabilization . Select pre-mRNA splicing factors have been implicated in small RNA-mediated gene silencing pathways in fission yeast , worms , flies and mammals , but the underlying molecular mechanisms are not well understood . Here , we show that SmD1 , a core component of the Drosophila small nuclear ribonucleoprotein particle ( snRNP ) implicated in splicing , is required for miRNA biogenesis and function . SmD1 interacts with both the microprocessor component Pasha and pri-miRNAs , and is indispensable for optimal miRNA biogenesis . Depletion of SmD1 impairs the assembly and function of the miRISC without significantly affecting the expression of major canonical miRNA pathway components . Moreover , SmD1 physically and functionally associates with components of the miRISC , including AGO1 and GW182 . Notably , miRNA defects resulting from SmD1 silencing can be uncoupled from defects in pre-mRNA splicing , and the miRNA and splicing machineries are physically and functionally distinct entities . Finally , photoactivatable-ribonucleoside-enhanced crosslinking and immunoprecipitation ( PAR-CLIP ) analysis identifies numerous SmD1-binding events across the transcriptome and reveals direct SmD1-miRNA interactions . Our study suggests that SmD1 plays a direct role in miRNA-mediated gene silencing independently of its pre-mRNA splicing activity and indicates that the dual roles of splicing factors in post-transcriptional gene regulation may be evolutionarily widespread .
miRNAs are a class of ~22–24 nt endogenous regulatory RNAs present in all cell types of multicellular organisms [1 , 2] . By regulating the expression of diverse target RNAs , miRNAs play a key role in myriad biological processes including development , homeostasis , and innate immunity . In Drosophila , canonical miRNA biogenesis starts with RNA polymerase II-mediated transcription of long stem-loop primary miRNA transcripts ( pri-miRNAs ) . They are processed in the nucleus by the Drosha/Pasha ribonuclease III ( RNase III ) microprocessor complex into ~60–70 nt precursor miRNAs ( pre-miRNAs ) , via a reaction referred to as cropping [3 , 4 , 5] . Precursor miRNAs are subsequently exported to the cytoplasm by Exportin5/Ran-GTP and further processed in a dicing reaction by a second RNase III complex , the Dicer 1 ( Dcr-1 ) /Loqs-PB complex , thereby liberating ~22–24 nt miRNA duplexes [6 , 7 , 8 , 9 , 10 , 11 , 12] . The mature miRNA strand of the duplex is predominantly incorporated into Argonaute 1 ( AGO1 ) -containing miRNA-induced silencing complexes ( miRISC ) . miRISC in turn engages target mRNAs via complementary base pairing between the seed region of miRNAs ( positions 2–8 ) and miRNA-binding sites ( primarily in the 3’ UTR of target mRNAs ) , and represses gene expression post-transcriptionally by promoting target mRNA destabilization and/or translation inhibition [13 , 14 , 15 , 16 , 17 , 18] . Over a decade of investigation has identified a collection of core components of the miRNA biogenesis and functional machineries , and delineated the framework of the molecular mechanism underlying the miRNA pathway . However , our knowledge of the miRNA pathways is far from complete , and many accessory factors that modulate miRNA biology await identification and functional characterization . A number of recent studies highlight extensive crosstalk between pre-mRNA splicing and small RNA-mediated gene silencing pathways . For example , the core RISC component AGO2 has been implicated in modulating pre-mRNA splicing both in mammals and in Drosophila [19 , 20] . Conversely , select splicing factors have been shown to impact small RNA-mediated gene silencing pathways . It has been reported that mutations in genes encoding a subset of splicing factors compromise RNAi in the fission yeast Schizosaccharomyces pombe [21] , and that in plants , mutations in splicing factor genes compromise small RNA biogenesis [22] . In addition , the multifunctional human RNA-binding protein hnRNP A1 , which regulates alternative splicing , impacts the processing of miR-18a and let-7a [23 , 24] . Furthermore , the KH-type splicing regulatory protein ( KSRP ) has been shown to positively regulate the biogenesis of miR-155 and let-7 [25 , 26] . Moreover , genome-wide RNAi screens conducted in C . elegans and cultured Drosophila cells show that depletion of certain splicing factors compromises RNAi [27 , 28 , 29] . Finally , a recent analysis of phylogenetic conservation of candidate RNAi factors suggests that select splicing factors are required for small RNA-mediated gene silencing [30] . SmD1 , together with six other small ribonucleoprotein particle ( snRNP ) proteins ( SmB , SmD2 , SmD3 , SmE , SmF and SmG ) , form a heptameric ring structure surrounding the U-rich small nuclear RNAs ( snRNAs ) [31] . These snRNP proteins constitute core components of the snRNP and play a key role in pre-mRNA splicing [32] . We recently showed that SmD1 depletion in cultured Drosophila cells compromises small interfering RNA ( siRNA ) biogenesis and function independently of its role in pre-mRNA splicing [33] . In the current study , we investigate the role of SmD1 in the miRNA pathway . We find that SmD1 depletion leads to a reduction in levels of mature miRNAs , which is accompanied by a derepression of the corresponding target messenger RNAs and a concomitant accumulation of primary miRNA transcripts . In addition , SmD1 associates with the microprocessor component Pasha and is required for optimal microprocessor activity . In contrast , SmD1 is dispensable for Dicer-mediated processing of pre-miRNAs into mature miRNAs . Furthermore , our analysis reveals that SmD1 is required for miRNA function besides its role in miRNA biogenesis . Specifically , SmD1 associates with the miRISC components AGO1 and GW182 , and is required for optimal miRISC function . Moreover , we show that select splicing factors such as SmD1 , but not pre-mRNA splicing per se , modulate the miRNA pathway , as defects in miRNA biogenesis and in pre-mRNA splicing can be uncoupled , and that SmD1 inactivation does not affect the expression of canonical miRNA pathway components . Finally , PAR-CLIP analysis identifies numerous SmD1-binding events across the transcriptome and reveals direct SmD1-miRNA interactions . Taken together , our study identifies SmD1 as a new modulator of the miRNA pathway at multiple levels , and provides direct evidence to support and extend the notion that select splicing factors are critical modulators of small RNA pathways in complex multicellular organisms , beyond the context of the spliceosome .
We first examined small RNA expression profiles in control S2 cells or cells depleted of Drosha , Dcr-2 or SmD1 ( Fig 1A and S1 Table ) . As expected , compared with control samples , depletion of Drosha led to a reduction in the proportion of miRNAs in the total small RNA population . As a consequence , the proportions of all classes of endogenous siRNAs expanded , including those derived from the Flock House Virus ( FHV ) , transposable element ( TE ) , convergently transcribed RNAs ( cis-NAT ) and hpRNAs . In contrast , depletion of the siRNA biogenesis enzyme Dcr-2 caused the opposite phenotype . Notably , SmD1 knockdown led to a shrinkage of the miRNA population and an artificial expansion of endo-siRNAs . Considering our previous findings showing that SmD1 is required for siRNA biogenesis and SmD1 depletion led to a reduction in levels of endo-siRNAs [33] , our data strongly suggest that SmD1 depletion can cause a comparable or even stronger degree of reduction in levels of miRNAs than in levels of siRNAs . To test this directly , we measured levels of endogenous siRNAs and miRNAs by Northern blot in SmD1 knockdown cells . Consistent with our recent finding [33] , SmD1 depletion led to a marked decrease in levels of the endogenous siRNA esi-2 . 1 ( Fig 1B and 1E ) . Importantly , levels of several miRNAs , including miR-33 , miR-34 , miR-276a , miR-317 , miR-2b , miR-184 and miR-bantam , were significantly reduced upon SmD1 knockdown ( Fig 1B–1G ) , reminiscent of the phenotype elicited by the loss of the canonical miRNA biogenesis enzyme Drosha . As a negative control , depleting canonical siRNA pathway components such as Dcr-2 or AGO2 predominantly affected levels of esi-2 . 1 , but not miRNAs ( Fig 1B–1E ) . To rule out potential off-target effects associated with dsRNAs , we tested an independent dsRNA against SmD1 and observed a similar impact on small RNA levels ( S1 Fig ) . We also detected a significant increase in steady-state levels of a subset of target mRNAs for several miRNAs implicated in cell proliferation and apoptosis ( Reaper , E2f1 and Socs36E as targets for miR-2b , miR-184 and miR-bantam , respectively ) ( Fig 1H ) [34 , 35] , consistent with the notion that miRNAs repress target gene expression by inhibiting mRNA translation and promoting target mRNA decay . We conclude that SmD1 is required for optimal miRNA biogenesis and/or stability . Besides the afore-mentioned miRNAs , which are constitutively expressed in S2 cells , we also examined levels of the miRNA let-7 , which is not expressed in naïve S2 cells but becomes highly induced upon treatment with 20-hydroxyecdysone ( 20-E ) [36] . We detected lower levels of let-7 in SmD1-depleted cells ( S2 Fig ) . These data reinforce the notion that SmD1 is required for optimal miRNA biogenesis . let-7 is highly expressed in the Drosophila heart , and is required for Drosophila heart function . Interestingly , depletion of SmD1 specifically in cardiac cells of adult Drosophila causes several defects in cardiac function ( S3 Fig ) . These observations suggest that the cardiac phenotype elicited by SmD1 depletion is linked , at least in part , to defects in let-7 biogenesis . miRNA biogenesis consists of multiple steps , including Drosha-mediated processing of pri-miRNAs into pre-miRNAs and Dcr-1-mediated conversion of pre-miRNAs into mature miRNAs , referred to as cropping and dicing , respectively ( Fig 2A ) . To further define the biochemical step ( s ) of miRNA biogenesis that require SmD1 , we examined the impact of SmD1 inactivation on levels of pri-miRNAs and pre-miRNAs . As expected , we detected a marked accumulation of several pri-miRNAs in S2 cells depleted of the microprocessor component Drosha ( S4 Fig ) . Importantly , SmD1 phenocopies Drosha , albeit to a moderate extent ( Fig 2B ) , suggesting that SmD1 is required for microprocessor-mediated processing of pri-miRNAs . To assess whether SmD1 is required for Dcr-1-mediated processing of pre-miRNAs into mature miRNAs , we treated S2 cells with dsRNAs targeting the firefly luciferase ( as control ) or SmD1 , together with dsRNAs targeting Dcr-1 ( to facilitate the detection of pre-miRNAs ) , and performed Northern blot to measure levels of pre-miRNAs . We found that compared to control samples , loss of SmD1 caused a reduction in levels of pre-miR-184 ( Fig 2C ) . These observations strongly suggest that SmD1 is dispensable for Dcr-1-mediated processing of pre-miRNAs into mature miRNAs , as otherwise we would have detected an accumulation of pre-miRNAs upon SmD1 inactivation . We note that it remains formally possible that SmD1 is required for the processing of pre-miRNAs into mature miRNAs , and the observed decrease in the overall pre-miRNA levels upon SmD1 knockdown is an accumulative effect of impaired microprocessor activity ( leading to less pre-miRNA production ) and less efficient Dcr-1-mediated pre-miRNA processing ( leading to accumulation of pre-miRNAs ) . Next , to definitively elucidate the requirement for SmD1 in different steps of miRNA biogenesis , we prepared total or cytoplasmic lysates from S2 cells treated with various dsRNAs , incubated lysates with radiolabeled pri-miRNAs or pre-miRNAs , and measured the microprocessor or Dcr-1 activities by monitoring the production of pre-miRNAs or mature miRNAs , respectively . Our analysis revealed that SmD1-deficient cell lysate is as competent as the control lysate in carrying out Dcr-1-mediated processing of pre-miRNAs into mature miRNAs ( Fig 2D ) . In contrast , SmD1-deficient cell lysate displays significant defects in Drosha-mediated conversion of pri-miRNAs into pre-miRNAs ( Figs 2E–2G and S5 ) . These data demonstrate that SmD1 is specifically required for cropping , but is dispensable not the dicing step during miRNA biogenesis . Having shown that SmD1 is required for optimal microprocessor activity , we next examined whether SmD1 associates with components of the microprocessor . Consistent with the requirement for SmD1 in the cropping step , we found that at Flag-tagged SmD1 , but not the control protein Ran , co-immunoprecipitated with the endogenous microprocessor component Pasha ( Fig 3A ) . In addition , the recovery of Pasha in the SmD1 complex is resistant to RNase A treatment , indicating RNA-independent protein-protein interactions . It remains to be determined whether the observed SmD1-Pasha interaction is direct or through protein intermediates . While we were unable to detect endogenous Drosha in the SmD1 complex by immunoblotting , most likely due to the low sensitivity of the Drosha antibody , moderate but clearly above background levels of microprocessor activity can be recovered from immunopurified endogenous SmD1 complex ( Fig 3B ) . These observations underscore the functional relevance of the observed SmD1-Pasha interaction . Next , we performed RNA immunoprecipitation ( RIP ) assays to assess whether SmD1 could associate with pri-miRNAs , the substrates for the microprocessor . Our analysis revealed significant enrichment in the SmD1 complex all six pri-miRNAs that we have examined , the degree of which matched or even exceeded that of cognate SmD1-binding small nuclear RNAs ( Fig 3C ) . In contrast , no significant enrichment of the control mRNA rp49 was observed . The observed interactions of SmD1 with Pasha and pri-miRNAs suggest that SmD1 might modulate miRNA biogenesis by serving as a molecular bridge to facilitate the recognition of pri-miRNAs by the microprocessor . To test this possibility , we performed RIP assay using a stable cell line expressing TAP-tagged Pasha and detected a significant enrichment of pri-miRNAs in immunopurified TAP-Pasha complex ( S6 Fig ) . Importantly , recovery of pri-miRNAs in the Pasha complex was severely blunted upon depletion of SmD1 ( Fig 3D ) . Interestingly , we also observed a moderate degree of enrichment of the control mRNA rp49 in the Pasha complex . This is consistent with the notion that the microprocessor complex potentially associates with and regulates the expression of a number of cellular mRNAs ( S6 Fig ) [37 , 38] . However , the association of the rp49 mRNA with Pasha seems to be largely unaffected by SmD1 depletion ( Figs S6 and 3D ) . To investigate the molecular detail of the SmD1-Pasha interaction , we next sought to map the protein domains responsible for this interaction . We generated a series of T7-tagged full length and truncated Pasha proteins and examined their capability of interacting with Drosha and SmD1 by performing co-immunoprecipitation assays . As expected , we found that full length Pasha was able to co-immunoprecipitate with endogenous Drosha in cultured Drosophila S2 cells ( Fig 3E , lane 7 ) . In addition , the C-terminal fragment of Pasha ( 334–642 ) is also capable of pulling down Drosha ( Fig 3E , lane 10 ) . Our data are consistent with previous reports showing that the C-terminal fragment of DGCR8 interacts with Drosha in mammals [39 , 40] . Note that T7-tagged Pasha127–642 was unable to co-immunoprecipitate with endogenous Drosha , possibly due to inefficient folding and/or presentation of the T7 epitope in native T7-Pasha127–642 protein in total cell lysate , as T7-Pasha127–642 was poorly recovered in the anti-T7 immunoprecipitate ( Fig 3E , lane 11 , lower panel ) . In contrast , T7-Pasha127–642 was readily detectable in input samples , most likely because the T7 epitope can be efficiently recognized by the anti-T7 antibody in denatured T7-Pasha127–642 ( Fig 3E , lane 5 , lower panel ) . Next , we examined whether various truncated Pasha proteins can co-immunoprecipitate with SmD1 . We found that Flag-tagged SmD1 was able to pull down both full length and a number of truncated Pasha mutants containing the region spanning amino acids 127–333 ( Fig 3F , lanes 7–9 , 11 ) . Thus , it appears that distinct regions of Pasha are required for the Pasha-Drosha and Pasha-SmD1 interactions ( Fig 3G ) . The stoichiometry of the SmD1-microprocessor complex is currently not clear , and it remains to be determined whether the observed Drosha-Pasha and SmD1-Pasha interactions are mutually exclusive , or all three proteins are present in the same complex . Collectively , these data demonstrate that SmD1 associates with both components of the miRNA biogenesis machinery and primary miRNA transcripts , and that SmD1 is required for optimal recognition of the pri-miRNAs by the microprocessor . Several lines of evidence point to a possible role of SmD1 in the effector phase of the miRNA pathway ( i . e . , miRISC assembly and function ) besides its involvement in miRNA biogenesis: 1 ) SmD1 modulates siRISC assembly and function , and associates with several siRISC components , including AGO2 [33]; 2 ) SmD1 , but not the control protein Ran , co-immunoprecipitates with miR-2b [33]; 3 ) in mammals SNRPD1 ( ortholog of Drosophila SmD1 ) and AGO2 ( a canonical miRISC component ) interact with each other [33]; and 4 ) a considerable fraction of SmD1 is present in the cytoplasm ( Fig 4A ) , where miRISC assembly and function primarily take place . To examine this possibility , we transfected SmD1-depleted S2 cells with a synthetic let-7 miRNA duplex together with a Renilla luciferase reporter construct carrying 8 copies of imperfect let-7-binding sites in the 3’ UTR . A firefly luciferase reporter lacking miRNA-binding sites serves as control . Defects in miRISC assembly/function are expected to be reflected as an increase ( de-repression ) in reporter activity compared to the negative control . It is worth noting that employing a synthetic mature miRNA duplex in the assay effectively circumvents the confounding factor that SmD1 is required for miRNA biogenesis . In addition , we chose let-7 because of its extremely low basal expression in S2 cells , thereby reducing background . Our analysis revealed that compared to control knockdown cells , SmD1-depleted cells display a marked de-repression of the let-7 reporter , resembling the phenotype elicited by depletion of the core miRISC component AGO1 ( Fig 4B ) . These data indicate that SmD1 is required for miRNA function . Consistent with this notion , we found that Flag-tagged AGO1 , but not the control protein Ran , is capable of co-immunoprecipitating with endogenous SmD1 ( Fig 4C ) . Furthermore , endogenous AGO1 as well as GW182 , another component of the miRISC , were detected in SmD1 complex , but not in the control Ran complex or the control immunoprecipitates using a non-immune serum ( Fig 4D and 4E ) . It appears that the SmD1-AGO1 and SmD1-GW182 interactions are not strongly affected by RNase treatment ( Fig 4D and 4E ) . These data demonstrate the interaction between SmD1 and components of the miRISC . Next , to determine the functional relevance of the SmD1-AGO1 interaction and to directly assess the role of SmD1 in miRISC assembly/function , we examined whether SmD1 depletion impairs the function of miRISC by measuring the slicer activity of AGO1-miRISC programmed by the let-7 miRNA duplex . To circumvent the confounding factor that AGO2 is a much more robust slicer than AGO1 and thus could mask the weak slicer activity of AGO1 , we first established stably transfected S2 cells expressing TAP-tagged AGO1 . Then we immunopurified and immobilized the AGO1 complex onto agarose beads and incubated the AGO1 complex with cytoplasmic lysates ( from either control cells or SmD1 knockdown cells ) together with the let-7 miRNA duplex . The beads were subsequently washed thoroughly and the slicer activity of the bead-bound let-7-AGO1 miRISC against an mRNA substrate carrying a perfect let-7 binding site was measured . This assay revealed a significantly weaker slicer activity of the AGO1-miRISC assembled in SmD1-depleted cell lysate than that assembled in control lysates ( Fig 4F and 4G ) , suggesting that SmD1 is required for efficient miRISC assembly and/or function . To examine whether SmD1 is required for the loading of miRNAs into AGO1 , which is the first step of miRISC assembly , we depleted SmD1 in TAP-AGO1-expressing S2 cells , and measured the levels of endogenous miRNAs in immuno-purified TAP-AGO1 complex ( Fig 4H ) . Note that as a control for the amount of TAP-AGO1 expressed from the transgene across different samples , we used identical amount of cell lysates in each immunoprecipitation . Compared with controls , the absolute levels of both miR-2b and miR-184 were markedly reduced in AGO1 miRISC recovered from SmD1-depleted cells ( Fig 4H and 4I ) . This is in part due to lower levels of miRNAs in input samples from SmD1 knockdown cells ( Fig 4H , compare the input samples ) . In addition , we calculated AGO1 loading index by normalizing levels of AGO1-bound miRNAs against those in the input . This analysis revealed a moderate decrease in AGO1 loading index upon SmD1 knockdown , suggesting that SmD1 is required for efficient loading of miRNAs into miRISC ( Fig 4J ) . Taken together , these data demonstrate that SmD1 is required for efficient miRISC assembly/function besides its role in miRNA biogenesis . To comprehensively identify direct SmD1-RNA interaction events across the transcriptome , we optimized the PAR-CLIP protocol in Drosophila S2 cells , recovered and deeply sequenced SmD1-bound RNAs ( S7A and S7B Fig ) [41 , 42] . Mapped reads are derived from various classes of RNAs ( S7C Fig ) . Our initial analysis identified 2180 SmD1 binding sites ( clusters ) across the transcriptome . Of these , 1729 unique peaks have passed non-adaptive filtration ( see Materials and Methods ) and were used for subsequent analyses ( S2 Table ) . Among them , 96 map to unannotated genomic regions . For the remaining 1633 clusters , 1553 ( 95% ) and 80 ( 5% ) , respectively , map to the annotated coding and non-coding RNAs ( Figs 5A and S8; S3 and S4 Tables ) . As expected , snRNAs , the cognate binding partners for SmD1 , were abundantly present in the dataset , so were sequences derived from the endogenous siRNA esi-2 . 1 precursor CG4068 , consistent with our previous report ( Fig 5B and S2 Table ) [33] . In addition , SmD1 binding events in the vicinity of splice junctions were found ( S5 Table ) , thereby providing supporting evidence for well-documented role of SmD1 in regulation of pre-messenger RNA processing . Interestingly , we also identified a substantial number ( 24 ) of SmD1-interacting snoRNAs . Importantly , sequences derived from several pri-miRNAs , including Bantam , miR-2 family , miR-11 , miR-33 and miR-34 were also recovered , thus demonstrating direct interactions between SmD1 and pri-miRNAs ( Figs 3C , 5C , 5D and S9; S6 Table ) . Interestingly , among the primary miRNA transcripts that we have examined so far , miR-33 and miR-34 are the top two highly enriched in immunopurified SmD1 complex ( Figs 3C , 5C and 5D ) . Notably , a major SmD1 binding peak directly overlaps with mature miR-34 ( Fig 5D ) , suggesting that SmD1 may directly associate with mature miRNAs ( in the context of miRISC ) . This is consistent with our previous findings that immunopurified SmD1 complex contains mature miRNAs [33] . An alternative and non-mutually exclusive possibility is that SmD1 could bind the sequence segment corresponding to mature miR-34 within the primary miRNA transcript . It is conceivable that SmD1 depletion indirectly impacts the miRNA pathway by modulating the expression of genes encoding canonical miRNA factors . We previously performed pair-end RNA-sequencing in both control cells and cells depleted of SmD1 [33] . Consistent with the role of SmD1 in pre-mRNA splicing , our analysis revealed that the splicing pattern of ~25% cellular mRNAs is altered in SmD1-depleted cells . Importantly , we found no significant changes in the mRNA levels of canonical miRNA factors except an increase in levels of Drosha and a decrease in loqs-RD , whose encoded product is dispensable for the miRNA pathway ( S10 Fig ) . Most importantly , immunoblotting assays revealed no significant changes in protein levels of canonical miRNA factors in SmD1-depleted cells except for an increase in levels of Loqs-PB and a concomitant reduction in Loqs-PD ( Fig 6A ) [33] . Given our findings that SmD1 impacts the cropping and miRISC assembly/function ( Figs 2E–2G , 4 and S5 ) , which do not require Loqs proteins , it is unlikely that the observed changes in levels of Loqs protein isoforms could account for the miRNA biogenesis and function defects elicited by SmD1 depletion . We conclude that SmD1 depletion does not functionally impact the expression of genes encoding canonical components of the miRNA pathway . To determine if a broader link exists between the miRNA pathway and splicing , we examined additional snRNP ( Sm ) proteins for their potential involvement in the miRNA pathway . We found that depletion of several snRNP proteins led a reduction in levels of miR-2b , reminiscent of the SmD1 knockdown phenotype ( Fig 6B ) . In contrast , levels of miR-2b remained unchanged in SmF knockdown cells . Furthermore , SmF knockdown did not impact in microprocessor activity either , even though SmF-depleted cells displayed obvious alteration in the splicing pattern of the CG13887 pre-mRNA , to the same extent as that observed in SmD1-depleted cells ( Figs S11 , 6C and 6D ) . These data clearly show that the miRNA defects elicited by SmD1 depletion can be uncoupled from pre-mRNA splicing defects , as the miRNA pathway appears to be intact in SmF-depleted cells , even though these cells display profound defects in pre-mRNA splicing . To further dissect the relationship between the miRNA and pre-mRNA splicing machineries , we examined whether additional snRNP proteins are capable of interacting with Pasha . We found that besides SmD1 , SmD2 is also capable of co-immunoprecipitating with Pasha ( Fig 6E ) . In contrast , no interaction can be detected between Pasha and SmB or SmF , even though both SmB and SmF are capable of pulling down endogenous SmD1 , most likely the SmD1 fraction in the spliceosome ( Fig 6E ) . Furthermore , upon examining levels of pri-miRNA and snRNA species in various immuno-purified Sm protein complexes , we found that SmD1 consistently outperforms SmF in binding to various pri-miRNAs . In contrast , we detected significantly higher levels of the U4 snRNA in the SmF complex compared to those present in the SmD1 complex ( Fig 6F ) . We note that Flag-tagged Sm proteins were employed in these assays and that these exogenous proteins have to complete with their endogenous counterparts for binding to their RNA partners . However , since we are measuring levels of various RNA cargos in the same sample , it allows us to make a direct comparison regarding the relative affinity between various Sm proteins and their RNA partners . These data suggest that compared with SmF , SmD1 appears to display a more prominent role in miRNA biogenesis , whereas SmF seems to be more dedicated to pre-mRNA splicing . In addition , these data also indicate that the spliceosome and miRISC are functionally distinct entities . To address this further , we immunopurified the microprocessor or the snRNP complexes by TAP-Pasha IP or SmD1 IP , respectively , and examined the presence of various snRNAs and pri-miRNAs in these complexes . As expected , snRNAs were highly enriched in the SmD1 complex ( Fig 3C ) . In contrast , snRNAs were largely absent in the microprocessor ( Fig 6G ) . On the other hand , several primary miRNA transcripts were highly enriched in the microprocessor ( Figs 3D and S6 ) . Taken together , these data demonstrate that select splicing factors , but not splicing per se , influence the miRNA pathway , and that the miRNA biogenesis machinery and the spliceosome are physically and functionally distinct .
Accumulating evidence suggests extensive crosstalk between pre-mRNA splicing and small RNA-mediated gene silencing pathways . For example , the core component of the RNAi effector machinery AGO2 plays a key role in the regulation of pre-mRNA splicing [19 , 20] . Conversely , a number of splicing factors have been implicated in modulating small RNA-mediated gene silencing [21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30] . We previously showed that the core snRNP splicing factor SmD1 is required for optimal biogenesis and function of siRNAs [33] . In the current study we report that SmD1 also plays a key role in modulating the miRNA pathway . Specifically , SmD1 interacts with the microprocessor component Pasha and with primary miRNA transcripts , and is selectively required for efficient recognition of primary miRNA transcripts by the microprocessor and the conversion of pri-miRNAs into pre-miRNAs . In addition , SmD1 associates with the miRISC components AGO1 and GW182 , and is required for miRISC assembly/function . We further show that only select splicing factors , but not pre-mRNA splicing per se , modulate the miRNA pathway , since defects in pre-mRNA splicing can be uncoupled from defects in the miRNA pathway , and that the molecular machineries executing pre-mRNA splicing and miRNA biogenesis and function are physically and functionally distinct entities . Our analysis reveals that SmD1 , but not a closely related snRNP protein SmF , is required for optimal miRNA biogenesis . These observations indicate that SmD1 belongs to a select group of splicing factors that modulate small RNA pathways beyond the context of the splicing machinery . SmD1 associates with the N-terminus of Pasha , whereas the C-terminal domain of Pasha is sufficient to interact with Drosha . It is currently unclear whether the SmD1-Pasha and Drosha-Pasha interactions take place in a mutually exclusive manner , or alternatively there exists a Drosha-Pasha-SmD1 complex . Our observation that the immunopurified SmD1 complex is capable of carrying out the conversion of pri-miRNAs into pre-miRNAs lends support to the latter possibility ( Fig 3B ) . Of note , several splicing factors have been shown to co-purify with the microprocessor [3] . Our study , together with a recent report that implicates FUS in miRNA biogenesis [43] , demonstrates that select splicing factors are functionally associated with the microprocessor in higher multicellular organisms . While it is possible that SmD1 couples splicing and processing of pri-miRNA transcripts by recruiting the microprocessor to nascent pri-miRNA transcripts that undergo co-transcriptional splicing , our observations that depletion of SmF , a related snRNP splicing factor , does not impact miRNA biogenesis ( Figs 6B and S11 ) , that neither SmB nor SmF is able to co-immunoprecipitate with Pasha ( Fig 6E ) , and that immunopurified SmD1 and Pasha complexes harbor overlapping yet distinct sets of cargo RNAs ( Figs 3C , 6F and 6G ) , argue against this possibility . While SmD1 is clearly required for miRNA biogenesis , it may operate in the context of multimeric protein complexes to execute this function . For example , our data show that SmD2 is as competent as SmD1 in pulling down primary miRNA transcripts and Pasha , and depletion of SmD2 led to a reduction in both miRNA levels and microprocessor activity ( Figs 6B , 6E , 6F and S11 ) . Together with previous studies that report the presence stable SmD1-SmD2 subcomplex , [31 , 44] , our data raise the possibility that the SmD1/D2 sub-assembly may execute a moonlighting function during miRNA biogenesis beyond the context of the spliceosome . We found that adding back purified recombinant SmD1 or lysates from cells over-expressing SmD1 was not sufficient to restore the microprocessor activity or miRISC assembly/function in SmD1-depleted cell lysate ( S12 and S13 Figs ) . These observations suggest that additional SmD1 co-factor ( s ) ( such as SmD2 ) in the context of multimeric complexes of appropriate stoichiometry may be necessary to functionally impact the miRNA pathway . An alternative possibility is that SmD1 depletion leads to altered expression of unknown protein ( s ) involved in miRNA biology , which underlies the defects in the miRNA pathway elicited by SmD1 knockdown . However , our findings lend strong support to the former scenario . Interestingly , our data uncover a differential dedication of various Sm proteins to the miRNA pathway and pre-mRNA splicing . For example , SmD1 and SmD2 consistently outperform SmF in binding to various pri-miRNAs , whereas the U4 snRNA is significantly more enriched in the SmF complex than in the SmD1 complex . ( Fig 6F ) This is consistent with our findings showing that SmD1 and SmD2 , but not SmF , is required for the miRNA pathway . These observations also indicate the presence of sub-spliceosomal assemblies or novel SmD1-containing complexes that impact the miRNA pathway . Further supporting this notion , our co-immunoprecipitation assay reveals that Flag-tagged SmD1 is capable of pulling down endogenous SmD1 ( Fig 6E , lane 8 ) . Most likely this interaction takes place beyond the context of the spliceosome , as the snRNP ring structure contains only a single copy of each Sm protein . Interestingly , depleting either SmB or SmD2 , immediate neighbors to SmD1 in the snRNP ring structure , led to a reduction in miRNA levels and microprocessor activity . However , only SmD2 , but not SmB , is capable of co-immunoprecipitating with Pasha ( Fig 6E ) . Identification of the complete collection of microprocessor-associated splicing factors and unraveling the stoichiometry of the microprocessor/SmD1-containing complexes should provide insights into the function of microprocessor-associated splicing factors in miRNA biogenesis . Besides its involvement in the initiation phase of the miRNA pathway ( miRNA biogenesis ) , SmD1 is also required for the effector phase of the miRNA pathway , as SmD1 depleted cells display defective miRISC assembly/function . This is manifested in part by defects in the loading of miRNAs into AGO1-miRISC ( Fig 4H–4J ) . It remains to be determined whether SmD1 is similarly required for additional steps of miRISC assembly , including miRNA duplex unwinding and miRNA star strand removal . We report here that the Drosophila SmD1 associates with the microprocessor and impacts the cropping step of miRNA biogenesis ( Fig 6H ) . Interestingly , in C . elegans the SmD1 ortholog SNR-3 co-purifies with Dcr-1 [45] . It would be informative to address whether SNR-3 similarly impacts miRNA biogenesis in worms . In addition , we show here that SmD1 associates with the core miRISC component AGO1 in flies and impacts miRNA function ( Fig 6H ) . An analogous observation has been made regarding the role of SmD1 in the siRNA pathway , where it associates with the siRISC component AGO2 and is required for siRISC assembly/function . Furthermore , we report previously that the human orthologs of SmD1 and AGO2 associate with each other [33] . These findings raise the possibility that the role of SmD1 in modulating small regulatory RNA biogenesis and Argonaute-RISC assembly and function may be evolutionarily conserved .
Drosophila S2 and S2-NP cells were maintained in Schneider’s medium ( Invitrogen ) supplemented with 10% fetal bovine serum ( FBS ) and 1% penicillin-streptomycin ( Invitrogen ) . S2-NP cells stably expressing Flag-SmD1 were generated by transfection with pRmHa-3-Flag-SmD1 and the selection marker plasmid pHS-neo using the calcium phosphate method , followed by selection in medium containing 400 μg/mL G418 ( Calbiochem ) . dsRNA treatment was performed as described previously [27 , 46] . Briefly , ~2 × 106 S2 or S2-NP cells were seeded in 6-well plates for 24 h and then transfected with 3 μg of the appropriate dsRNA . Two days later , the cells were harvested , replated in 6-cm plates for 24 h , and then treated again with 9 μg dsRNA . Three days later , the cells were harvested and used in assays . For Renilla luciferase reporter assays , transfections were performed in a 384-well format using HiPerFect ( Qiagen ) . DNA fragments encompassing the coding regions of SmD1 , SmB , SmD2 , SmF , Drosha , AGO1 , and full length and truncated Pasha , together with Flag , T7 or TAP epitope tags were amplified by PCR and cloned into pRmHa-3 or pMK33-NTAP vectors . Anti-SmD1 antibody was generated by immunizing rabbits with a synthetic peptide ( ProSci Inc . ) . Cells were lysed in lysis buffer ( 20 mM Tris-HCl ( pH 7 . 6 ) , 150 mM NaCl , 2 mM EDTA , 10% glycerol , 1% Triton X-100 , 1 mM DTT , 1 mM orthovanadate ) supplemented with protease inhibitor cocktail ( Roche ) . Cleared total lysates were immunoprecipitated with antibodies against Flag ( Sigma ) . Both input and immunoprecipitated samples were analyzed by SDS-PAGE followed by immunoblotting with antibodies against Flag ( Sigma ) , T7 ( Novagen ) , AGO1 ( Abcam ) , Pasha [5] or GW182 [47] . Other antibodies employed in this study include Drosha and Dcr-1 ( gift from Dr . Greg Hannon ) , Loqs [48] or Tubulin ( Sigma ) , as indicated . RNase treatment of the immunoprecipitates was performed as previously described [27 , 46] . To detect protein-RNA interactions , RNA was extracted from the immunoprecipitates by treatment with TRIzol and subject to RT-qPCR analysis using gene-specific primers . Northern blotting was performed as previously described [46 , 48] . In brief , total cellular or co-immunoprecipitated RNA was isolated with TRIzol ( Invitrogen ) . Samples of 15 μg RNA were separated on 15% denaturing polyacrylamide gels and transferred to Hybond-N+ membranes ( Amersham Biosciences ) in 1X TBE buffer . Small RNAs were UV crosslinked to the membranes , and the membranes were prehybridized in hybridization buffer for 2 h . DNA probes complementary to the appropriate strands were 5′ radiolabeled and incubated with membranes overnight at 37°C . Membranes were washed twice in 1X SSC with 0 . 1% SDS at 42°C , and then exposed to Phosphorimager screens for 12–48 h . Membranes were stripped by the addition of boiling 0 . 1% SDS solution and incubated for 30 min . Cropping , dicing and slicing assays were performed as previously described , with minor modifications [49 , 50] . Briefly , for the cropping assay , total S2-NP cell lysates were prepared by sonicating cell suspension in lysis buffer ( 30 mM HEPES-KOH , pH 7 . 0 , 100 mM potassium acetate , 2 mM magnesium acetate , 5 mM DTT , 20% glycerol , and 1X EDTA-free protease inhibitors ( Roche ) ) for 5 times ( 5 sec each with 2 min interval at 30% duty cycle ) . Primary miRNAs were synthesized using a T7 MEGAscript in vitro transcription kit ( Ambion ) with α-32P-GTP , and gel purified . Aliquots of 10 μl of cell lysates containing the same amount of total protein were incubated in a final volume of 20 μl reaction mixture ( 30 mM HEPES-KOH , pH 7 . 0 , 100 mM potassium acetate , 2 mM magnesium acetate , 5 mM DTT , 10% glycerol , 1 mM ATP , 10 mM creatine phosphate , 0 . 06 U/μl creatine kinase ( Roche ) , 0 . 1 U/μl ribonuclease inhibitor ( Promega ) , 10 ng/μl yeast tRNA , and 2000–10 , 000 cpm pri-miRNA substrate ) at 25°C for 2 . 5 h . For the dicing assay , cytoplasmic extracts from frozen S2-NP cells were prepared by thawing cells in a hypotonic buffer composed of 10 mM HEPES-KOH ( pH 7 . 0 ) , 2 mM magnesium acetate , 0 . 1% β-mercaptoethanol , and 1X EDTA-free protease inhibitors ( Roche ) . Radiolabeled pre-miRNA substrate was prepared by incubating the pre-let-7 synthetic RNA oligo with T4 polynucleotide kinase ( New England Biolabs ) and γ-32P-ATP and subsequently gel-purified . Aliquots of 6 μl of cell lysates containing the same amount of total protein were incubated in a final volume of 10 μl reaction mixture ( 20 mM HEPES-KOH , pH 7 . 0 , 2 mM DTT , 2 mM magnesium chloride , 1 mM ATP , 25 mM creatine phosphate , 0 . 06 U/μl creatine kinase ( Roche ) , 0 . 8 U/μl ribonuclease inhibitor ( Promega ) , and 2000–10 , 000 cpm pre-let-7 substrate ) at 25°C for 1 h . For the slicing assay , the capped Renilla luciferase mRNA substrate containing 1 copy of perfect let-7 binding site in the 3’ UTR was synthesized using a MEGAscript T7 in vitro transcription kit , incubated with Vaccinia virus capping enzyme ( New England Biolabs ) and α-32P-GTP , and gel purified . Minimal AGO1-miRISC was prepared by incubating TAP-AGO1 cell lysates with IgG beads with gentle rocking at 4°C overnight . The beads were thoroughly washed in hypotonic buffer and incubated with cytoplasmic lysates from either SmD1 knockdown or control cells in a final volume of 50 μl reaction mixture ( 8 mM HEPES-KOH ( pH 7 . 0 ) , 60 mM potassium acetate , 5 mM DTT , 1 mM ATP , 25 mM creatine phosphate , 0 . 03 U/μl creatine kinase , 0 . 2 U/μl ribonuclease inhibitor , and 1 mM let-7 miRNA ) at 25°C for 30 min . The beads were subsequently thoroughly washed in hypotonic buffer and incubated in a final volume of 50 μl reaction mixture ( 8 mM HEPES-KOH ( pH 7 . 0 ) , 60 mM potassium acetate , 5 mM DTT , 1 mM ATP , 25 mM creatine phosphate , 0 . 03 U/μl creatine kinase , 0 . 2 U/μl ribonuclease inhibitor , 10 ng/μl yeast tRNA , and 2000–10 , 000 cpm cap-labeled mRNA substrate ) at 25°C for 2 h . After the final incubation step , the cropping , dicing or slicing reaction mixtures were then added to 200 μl proteinase K buffer ( 200 mM Tris-HCl ( pH 7 . 5 ) , 25 mM EDTA , 300 mM sodium chloride , 2% w/v SDS , and 50 μg/mL proteinase K ) , incubated at 65°C for 30 min , and extracted with phenol/chloroform ( 1:1 ) . RNA was precipitated from the supernatant and resolved by 6% ( for cropping and slicing ) or 15% urea-PAGE ( for dicing ) . PAR-CLIP procedure and library construction were conducted as previously reported [41 , 42] . Sequenced reads were trimmed of 3’ and 5’ adaptors ( 3’ = "TGGAATTCTCGGGTGCCAAGG"; 5’ = "ATCTCGTATGCCGTCTTCTGCTTG" ) using flexbar package [51] . Reads that were less than 15 nucleotides in length were discarded . In order to accurately analyze each binding event without the confounding bias introduced by repetitive regions , we identified and removed reads that align to rRNA , tRNA and RepeatMasker sequences ( UCSC BDGP R5/dm3 and FlyBase FB2014_03 ) . Elimination of reads mapped to repetitive sequences has significantly affected the overall read yield available for further analyses , thus complicating discovery of SmD1 binding sites . The remaining reads were aligned to Drosophila genome with bowtie algorithm [52] . Mapped locations were only reported for the optimal mismatch-stratum for each read up to a maximum of ten different locations . The resulting alignment was processed with PARALYZER tool ( v1 . 1 ) [53] . All clusters that have two or more T to C conversion locations were reported . The discovered clusters were further filtered to exclude those where a ) read coverage was lower than 10 , b ) ModeScore< = 0 . 6 , and c ) number of unique locations having at least one conversion event exceeded 2 . The above non-adaptive filtration helped to remove potential false positive binding events in low coverage regions , where PARALYZER’s signal-to-noise estimation becomes less reliable . The location that a cluster mapped to , relative to a known transcript , was determined based on the FlyBase genome annotation ( release 5 . 57 ) . To assess the extent of SmD1 binding in miRNA precursor regions , ±10Kb around the known miRNA locus were examined and overlapping read clusters detected with BEDTools suite . To evaluate the role of SmD1 on regulation of mRNA splicing , coordinates of exon junctions annotated in FlyBase were extracted . Next , regions of interest around exon–intron junctions at the 5′ and 3′ ends of introns were determined . These loci included: a ) 15 bp region around 5’ splice site , of which 5bp were inside the intron , and b ) 28bp region around 3’ splice site , where only 3bp overlapped with the 3’ exon . Finally , the intersection between SmD1 binding and mRNA splice sites was computed . Small RNA libraries were constructed from gel purified 19–24 nt RNA samples using the TruSeq small RNA sample kit according to manufacturer’s manual ( Illumina ) , and sequenced on a GA-II machine . Reads were trimmed of 3’ and 5’ adaptors ( 3’ = "TGGAATTCTCGGGTGCCAAGG"; 5’ = "ATCTCGTATGCCGTCTTCTGCTTG" ) with cutadapt package ( http://dx . doi . org/10 . 14806/ej . 17 . 1 . 200 ) and mapped to the fly genome ( rel . 5 . 57 ) with Bowtie software suite ( v . 1 . 1 . 1 ) [52] in a sequential manner {e . g . progressively relaxing constraints for permissive number of mismatches until the limit of 2 was reached ( –v[0–2]-best ) } . The alignment was processed with HTSeq [54] and read abundances assigned to various genomic elements calculated . To assess read numbers mapping to transposable elements loci we used only LINE-like and LTR elements annotated in RepeatMasker ( UCSC BDGP R5/dm3 and FlyBase FB2014_03 ) . Annotation and genomic coordinates for 3p-CIS-NAT , esiRNA loci used to estimate siRNA abundances were obtained from Eric Lai ( personal communication ) . Reads that failed to map to the fly genome were aligned to the flock house virus ( FHV ) genome and counted . See S7 Table . SmD1 was knocked down in the Drosophila heart by cardiac-specific RNAi using the UAS/Gal4 system [55] . Female tinCΔ4-Gal4 flies [56] were crossed to UAS-shSmD1 ( Bloomington stock 34834 ) and UAS-shGFP ( gift from Dr . Norbert Perrimon ) respectively . The female F1 progeny was aged for 3 weeks at 25°C and heart function was analyzed using high-speed recordings of semi-dissected hearts [57] .
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microRNAs ( miRNAs ) are a class of small regulatory RNAs that fine-tune gene expression by reducing protein output from their target messenger RNAs and are implicated in myriad physiological and pathological processes . miRNAs are generated from long primary transcripts via sequential actions of the Drosha/Pasha and Dicer ribonucleases . Mature miRNAs are incorporated into the miRISC effector complexes that contain AGO family member proteins and serve as specificity determinants to guide miRISCs to their target RNAs . Previous studies suggested that select proteins implicated in the processing of messenger RNAs are required for the miRNA production/function , but the underlying molecular mechanism is not well understood . Here we show that SmD1 , an essential protein implicated in the processing of messenger RNAs , directly interacts with both Pasha and primary miRNA transcripts and is required for optimal miRNA production . Furthermore , SmD1 associates with multiple components of the miRNA effector machinery and is required for miRNA function . Finally , our analysis reveals that defects in the miRNA pathway can be uncoupled from those in messenger RNA processing , and that the miRNA biogenesis and messenger RNA processing machineries are physically and functionally distinct entities . Our data thus suggests that SmD1 modulates the miRNA pathway independent of its role in messenger RNA processing .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
SmD1 Modulates the miRNA Pathway Independently of Its Pre-mRNA Splicing Function
|
The innate immune system is critical in the response to infection by pathogens and it is activated by pattern recognition receptors ( PRRs ) binding to pathogen associated molecular patterns ( PAMPs ) . During viral infection , the direct recognition of the viral nucleic acids , such as the genomes of DNA viruses , is very important for activation of innate immunity . Recently , DNA-dependent protein kinase ( DNA-PK ) , a heterotrimeric complex consisting of the Ku70/Ku80 heterodimer and the catalytic subunit DNA-PKcs was identified as a cytoplasmic PRR for DNA that is important for the innate immune response to intracellular DNA and DNA virus infection . Here we show that vaccinia virus ( VACV ) has evolved to inhibit this function of DNA-PK by expression of a highly conserved protein called C16 , which was known to contribute to virulence but by an unknown mechanism . Data presented show that C16 binds directly to the Ku heterodimer and thereby inhibits the innate immune response to DNA in fibroblasts , characterised by the decreased production of cytokines and chemokines . Mechanistically , C16 acts by blocking DNA-PK binding to DNA , which correlates with reduced DNA-PK-dependent DNA sensing . The C-terminal region of C16 is sufficient for binding Ku and this activity is conserved in the variola virus ( VARV ) orthologue of C16 . In contrast , deletion of 5 amino acids in this domain is enough to knockout this function from the attenuated vaccine strain modified vaccinia virus Ankara ( MVA ) . In vivo a VACV mutant lacking C16 induced higher levels of cytokines and chemokines early after infection compared to control viruses , confirming the role of this virulence factor in attenuating the innate immune response . Overall this study describes the inhibition of DNA-PK-dependent DNA sensing by a poxvirus protein , adding to the evidence that DNA-PK is a critical component of innate immunity to DNA viruses .
The battle between host and pathogen has driven the evolution of the immune system and of pathogens . The result of this on-going fight is the development of sophisticated host detection and response systems and also of elegant pathogen subversion mechanisms [1] , [2] . As part of the innate immune response , pattern recognition receptors ( PRRs ) detect an invading pathogen and induce the production of cytokines and chemokines [3] , [4] . Not surprisingly evolution has produced PRRs that bind to conserved , essential molecules of pathogens ( pathogen-associated molecular patterns , PAMPs ) , making it hard for the pathogen to escape detection . For example , lipopolysaccharide ( LPS ) is an essential component of the outer membrane of Gram-negative bacteria and is detected by toll-like receptor ( TLR ) 4 [5] . Similarly , during virus infection , intracellular viral nucleic acids are detected by our innate immune system [4] . Since it is difficult to alter their genomes to escape detection , viruses have evolved proteins that counteract host detection mechanisms by binding and inhibiting signalling molecules [2] . Vaccinia virus ( VACV ) is a prime example of this evolutionary strategy because it encodes in its large double stranded ( ds ) DNA genome numerous proteins that inhibit the host innate immune system . It encodes , for example , at least 10 proteins which can block activation of nuclear factor kappa B ( NF-κB ) , for example proteins N1 [6] , [7] , A46 and A52 [8]–[10] , B14 [11] , [12] , K7 [13] , M2 [14] , K1 [15] , E3 [16] , C4 [17] , and A49 [18] and others that block activation of interferon regulatory factor ( IRF ) -3 such as A46 [10] , K7 [13] , C6 [19] and N2 [20] . In addition , protein B13 inhibits caspase 1 thereby blocking production of IL-1β downstream of AIM2-mediated detection of foreign DNA [21] . However , although VACV has a dsDNA genome that stimulates the innate immune system , there have been no descriptions of VACV proteins capable of directly inhibiting the detection of its DNA genome by PRRs . One reason for this is that , until recently , the PRRs that detect intracellular DNA of pathogens have been poorly understood . Recently , DNA-dependent protein kinase ( DNA-PK ) was identified as a PRR for DNA and DNA viruses and shown to activate IRF3-dependent innate immunity [22] . DNA-PK is best known as a large DNA repair complex consisting of Ku70 , Ku80 ( which together form the Ku heterodimer ) and the catalytic subunit DNA-PKcs . To promote DNA repair , Ku binds to free ends of DNA , which induces a conformational change leading to the recruitment of DNA-PKcs via the C-terminal domain of Ku80 [23]–[25] . However , in addition to its role in DNA repair , DNA-PK is a critical component of IRF3-mediated innate immune DNA sensing in murine embryonic fibroblasts ( MEFs ) and adult murine skin fibroblasts . This discovery added to a growing list of putative DNA sensors which have been identified following initial descriptions that DNA activates an IRF3-dependent pathway [26] , [27] These include DAI [28] , AIM2 [29]–[32] , RNA-polymerase III [33] , [34] , LRRFIP1 [35] , DHX9/DHX36 [36] , IFI16 [37] , DDX41 [38] , MRE11 [39] and cGAS [40] . Furthermore , there is an additional molecule , barrier to autointegration factor ( BAF ) , which has not been shown to activate IRF3 or other innate immune signalling pathways but nonetheless has a critical function as a cytoplasmic DNA-binding molecule that inhibits poxviral DNA replication , and this function of BAF is inhibited by the VACV B1 protein kinase [41] . It is only beginning to become clear , however , which sensors act in which cell types to detect which pathogens [42] . It is evident these DNA sensors have different patterns of cellular expression and have differential preferences for the type of DNA . For example , AIM2 responds preferentially to cytoplasmic DNA in macrophages by forming an inflammasome leading to IL-1β and IL-18 secretion or pyroptotic cell death . The importance of AIM2 in the response to poxviruses and cytoplasmic bacteria has been demonstrated by the observation that mice lacking AIM2 are more susceptible to these pathogens [43] , [44] . AIM2 does not , however , stimulate IRF3 activation . RNA-polymerase III binds to , and transcribes , AT-rich DNA and produces a 5′ triphosphate RNA molecule which acts as a stimulatory ligand for RIG-I [33] , [34] , although which cell types and pathogens this is most important for have not yet been identified . LRRFIP1 and IFI16 have little specificity for the type of DNA detected and have been characterised mostly in macrophage cell lines [35] , [37] . Conversely , DHX9/DHX36 and DHX41 function in plasmacytoid dendritic cells ( pDCs ) and myeloid dendritic cells respectively , and are stimulated principally by intracellular DNA bearing CpG motifs or by dsDNA respectively [36] , [38] . cGAS was identified following the identification that cyclic guanosine monophosphate-adenosine monophosphate ( cGAMP ) bound to , and activated , the adaptor molecule STING [45]–[49] . However , of the DNA sensors that lead to IRF3-mediated IFN production , only DNA-PK has been shown to function in vivo . Mice lacking DNA-PK infected with MVA or herpes simplex virus ( HSV ) type 1 were deficient in the upregulation of pro-inflammatory cytokines and chemokines [22] . The interest in VACV derives historically from its use as the vaccine that eradicated smallpox , caused by the related orthopoxvirus , variola virus ( VARV ) [50] . After eradication was achieved interest in VACV continued due to its development as an expression vector [51] , [52] that has application for development of new live vaccines [53]–[55] . More recently , VACV has been utilised as a tool for studying host-pathogen interactions that has shed light on immune system functions [56] and how VACV exploits cell biology for rapid dissemination [57] , [58] . VACV strain modified virus Ankara ( MVA ) is a promising vaccine vector [59] and is highly attenuated due to extensive passage in chicken embryo fibroblasts leading to several large genome deletions [60] . These deletions removed several immunomodulatory genes [61] , and smaller lesions in other genes have resulted in loss of protein function [62] . VACV strain Western Reserve ( WR ) protein C16 is an intracellular virulence factor and is conserved among orthopoxviruses , including VARV and MVA [63] . Mice infected with a virus lacking C16 ( vΔC16 ) had more leukocytes infiltrating infected tissue , lost less weight and showed fewer signs of disease compared with both wild-type and revertant viruses . However , the mechanism of action of the C16 protein was not understood [63] . In this study the mechanism by which VACV protein C16 influences the immune response has been investigated and it is shown that , by binding to the Ku70/80 complex , C16 blocks DNA sensing in fibroblasts . The discovery of the interaction between C16 and Ku led to the decision to investigate the potential role of DNA-PK in innate immunity , leading to description of DNA-PK as a PRR for cytoplasmic DNA [22] . The interaction between C16 and Ku is via the C-terminal region of C16 that interacts directly with Ku70/80 and thereby reduces its ability to bind to DNA . This C-terminal region is highly conserved in both the VARV and MVA C16 orthologues; however , although VARV C16 can interact with Ku70/80 , a small internal deletion in MVA C16 knocks out this binding activity . In vivo and compared to control viruses , vΔC16 caused greater induction of cytokines in the first 48 h of infection , consistent with C16 functioning as an inhibitor of the innate immune response . This study therefore highlights the in vivo importance of DNA-PK as a DNA sensor and describes how a DNA virus has evolved to inhibit DNA sensing as a way to subvert the detection of its genome by the host .
To investigate how C16 modulates the host immune response , C16 was tandem affinity purification ( TAP ) -tagged [64] , expressed inducibly in HEK293 TRex cells and the C16 protein complexes were purified and analysed by SDS-PAGE and mass spectrometry . C16 was purified using this method in parallel with a control protein , the intracellular IL-1 receptor antagonist ( icIL-1Ra ) that has a similar motif to C16 at the C-terminus [63] , [65] . C16 co-purified with two proteins of 70 and 80 kDa that were identified by liquid chromatography mass spectrometry ( LC/MS ) as the two components of the Ku heterodimer , Ku70 and Ku80 . These proteins did not co-purify with icIL-1ra-TAP and no proteins were detected from the non-induced C16 cell line or a cell line expressing the TAP-tag alone ( Figure 1A ) . Confirmation of this interaction was carried out in several ways . Firstly , C16 complexes were affinity purified from the HEK293 cell line and immunoblotted for Ku70 and DNA-PKcs showing that C16 binds to the Ku complex but not the third DNA-PK component , DNA-PKcs ( Figure 1B ) . Secondly , immunoprecipitation of endogenous Ku80 from cells infected with VACV WR , or vΔC16 as a control , confirmed that this interaction was observed during virus infection when both proteins were expressed at endogenous levels ( Figure 1C ) . Finally , to test whether the binding of C16 to Ku was direct , recombinant C16 protein was expressed and purified from E . coli and was then incubated with Strep-tagged Ku70/Ku80ΔC that had been purified from insect cells infected with recombinant baculoviruses . The Strep-tagged Ku70/Ku80ΔC complex was then re-purified on a Strep-Tactin matrix and analysed by SDS-PAGE . This showed that C16 co-purified with the Ku proteins ( Figure 1D ) and thereby confirmed that the interaction between Ku70/80 and C16 was direct . The Ku70/Ku80ΔC complex lacks the small C-terminal domain implicated in binding DNA-PKcs , suggesting that C16 does not bind Ku in direct competition with the catalytic subunit of DNA-PK . Collectively , these experiments showed that C16 interacts directly with the Ku complex , both in cells and in vitro , and can be observed with endogenous proteins in the context of VACV infection . To determine which region of C16 is needed to bind Ku , FLAG-tagged fragments of C16 ( Figure 2A ) were expressed in HEK293T cells and tested for binding to the Ku complex ( Figure 2B ) . Full-length C16 ( amino acid residues 1–331 ) co-precipitated with Ku70/80 , as did the C16 fragments containing amino acid residues 97–331 and 157–331 . In contrast , the N-terminal region comprising amino acid residues 1–214 , as well as the C-terminal amino acids 215–331 , did not co-precipitate with Ku . These data show that the C-terminal residues 157–331 of C16 are sufficient for binding Ku ( Figure 2B ) . Whilst VACV C16 is highly conserved among VACV strains , there are minor differences in the orthologues of C16 encoded by VARV and VACV strain MVA . In MVA the C16 orthologue has an internal deletion of 5 amino acids ( residues 277–281 ) ( Figure S1 ) but was detected at levels similar to VACV WR C16 during infection [63] . In comparison , the VARV-GBR46 differs by 6 ( 1 . 8% ) amino acids spread across the protein . To test if these changes affect the binding of C16 to the Ku complex , alleles of MVA and VARV C16 corresponding to VACV WR residues 157–331 were expressed in HEK293T cells and then assessed for binding to Ku70 ( Figure 2C ) . In this assay , the VARV C16 orthologue interacted with Ku70 but the MVA orthologue showed severely diminished binding . These data suggest not only that amino acids 277–281 are important for the interaction between C16 and Ku , but also that whilst VARV protein C16 targets Ku70 , that ability has been lost in the attenuated MVA strain of VACV . The consequence of C16 binding to Ku was analysed by testing the ability of C16 to interrupt the interaction between DNA and the Ku70/80 heterodimer . Biotinylated DNA was transfected into cells and DNA:protein complexes were isolated from the cytoplasm via the biotin tag . In whole cell lysates it was noted that the level of DNA-PKcs and Ku70 were similar in the presence or absence of transfected DNA , and whether or not C16 was expressed ( Figure 3A–C ) . In cells expressing C16 , however , the amounts of both Ku and DNA-PKcs that co-purified with DNA were reduced substantially compared with cells transfected with empty vector . This was not due to degradation of DNA-PK components because measurement of the levels of Ku70 and DNA-PKcs showed a slight , but statistically insignificant , increase in the expression level of DNA-PK components in the presence of C16 . These observation indicated that C16 inhibits the interaction of DNA-PK with DNA ( Figure 3A ) . Quantification of this result by immunoblotting from triplicate experiments confirmed a statistically significant reduction in DNA-PK components binding to DNA in the presence of C16 ( Figure 3B , C ) . It was also noted that C16 did not co-purify with DNA implying that C16 does not bind to DNA directly . To investigate if C16 was sufficient to block Ku binding to DNA , purified Ku70/Ku80 was incubated with DNA in the absence or presence of increasing concentrations of the purified C-terminal domain of C16 and DNA protein complexes were analysed by electrophoretic mobility shift assay ( EMSA ) ( Figure 3D , E ) . This showed that the C-terminal domain of C16 , inhibited the electrophoretic shift induced by Ku . Furthermore , C16 alone did not induce an electrophoretic shift ( Figure 3D ) , supporting the observation that C16 does not bind to biotinylated DNA ( Figure 3A ) . At a high molar C16∶Ku ratio of approximately 6∶1 , Ku was no longer able to shift DNA . Together , these data demonstrate that the C16 C-terminal domain is sufficient for inhibiting the interaction between Ku and DNA . Overall , these data show that C16 functions to inhibit the binding of Ku70/80 to DNA , thereby greatly reducing the interaction of the DNA-PK complex with foreign DNA in the cytoplasm . This proposed model is illustrated in Figure S2 . Since C16 interacted with Ku70/80 and inhibited its binding to DNA , we proposed that VACV C16 had evolved to inhibit Ku-mediated DNA sensing . C16 was therefore assessed for its ability to block the production of cytokines by MEFs in response to cytoplasmic DNA stimulation . Due to the difficulty of expressing C16 without the transfected DNA plasmid itself stimulating innate immune signalling , a plasmid expressing C16 was co-transfected simultaneously with larger molar quantities of linear immunomodulatory DNA and the amount of Cxcl10 and Il-6 produced were measured by ELISA 24 h later . Under the conditions tested , co-transfection of C16 , compared with a control plasmid , reduced the production of Cxcl10 and Il-6 in response to DNA by approximately 50 per cent , but not poly I∶C ( a dsRNA mimic ) ( Figure 4A , B ) . This indicated that C16 inhibited the innate immune activation of these cells by DNA but not RNA , consistent with the described function of Ku70/80 in DNA sensing [22] . This inhibition was investigated further by digesting the plasmid encoding the C16 ORF with the restriction enzymes BspMI , which disrupted the C16 ORF , or MluI that cut the plasmid without affecting the C16 ORF . These linearised plasmids were then transfected into MEFs such that the dsDNA stimulus was also responsible for expression of the gene of interest , rather like the situation during DNA virus infection . When the C16 ORF remained intact ( MluI digestion ) the level of Cxcl10 induced was lower than when it was disrupted ( BspMI digestion ) ( Figure 4C ) , supporting the hypothesis that C16 inhibits the innate immune response to DNA by MEFs . MEFs lacking the Ku heterodimer induce lower levels of cytokines and chemokines induced upon stimulation with DNA [22] . However , the abrogation is not complete and there is residual signalling . This is explained ( at least in part ) by DNA-PKcs having DNA-binding capability independent of Ku [66] , and also by the existence of other DNA sensing mechanisms . If C16 inhibited the production of Cxcl10 and Il-6 via its interaction with Ku , following DNA stimulation C16 might be expected to not influence the induction of these molecules in MEFs lacking Ku80 , gene Xrcc5 , and therefore lacking the Ku heterodimer [67] . This was tested and shown to be correct , although the overall level of cytokine induction was reduced as expected ( Figure 4D , E ) . This suggests that the inhibition of DNA sensing mediated by C16 was dependent on its interaction with the Ku heterodimer . Together , these data suggest that C16 inhibited DNA sensing , but not RNA sensing , and that this was mediated by its interaction with Ku . The hypothesis that C16 was disrupting DNA-sensing at the sensor level was tested further by overexpression of a molecule downstream in the signalling pathway . It was observed that , whilst C16 blocked DNA sensing when co-transfected with empty vector , this inhibition was overcome when TBK-1 was co-transfected with C16 ( Figure 4F ) . This shows that the inhibitory effect exerted by C16 is upstream of this component in the DNA-sensing pathway . The effect on IRF3 translocation was also studied . MEFs were infected with wild-type virus ( vC16 ) or a C16 deletion virus ( vΔC16 ) and the location of IRF3 was examined by immunofluorescence . This experiment showed that infection of MEFs with these WR-based viruses did not induce IRF3 translocation ( Figure S3 ) , in contrast to the ability of MVA to activate this innate immune signalling pathway [22] . This is likely to be explained by a number of VACV proteins which have evolved to inhibit IRF3-mediated signalling , independent of C16 [13] , [19] , [20] . To assess the contribution of C16 to the innate immune response in vivo , mice were infected intranasally with either a plaque purified wild type VACV WR , vΔC16 , or a revertant virus in which the C16L gene had been re-inserted into its original locus ( Figure 5 ) [63] . VACV infection induced the production of Cxcl10 and Il-6 into the bronchoalveolar lavage ( BAL ) fluid , however , infection with VACV vΔC16 lead to an enhanced production of these cytokines . Consistent with the function of C16 inhibiting the innate immune response to DNA , this effect was significant in the first 2 d post infection ( p . i . ) at 24 and 48 h p . i . for Cxcl10 , and at 24 h p . i . for Il-6 . C16 is a virulence factor , causing increased weight loss and reducing the number of leukocytes recruited to the lungs of mice infected with VACV [63] . Overall , data presented in this study , demonstrate that DNA-PK-mediated activation of the innate immune response to VACV is of biological significance in vivo and that C16 is capable of inhibiting this function .
The interactions between virus and host proteins have led to discoveries about the function of multiple cellular systems , including the innate immune system . VACV encodes many inhibitors of both extracellular molecules and intracellular signalling cascades to help dampen down immune responses . Examples of extracellular immunomodulators include protein A41 that inhibits binding of chemokines to glycosaminoglycans , thereby preventing establishment of the concentration gradient of these molecules [68] , [69] . Other examples include VACV proteins B18 and B8 as decoy receptors for type I and type II IFNs , respectively [70]–[74] . Examples of intracellular inhibitors of the innate immune system including the steroid biosynthetic enzyme 3β-hydroxysteroid dehydrogenase that reduces the VACV-specific CD8+ T cell response to infection [75] , [76] , B14 that binds to IKKβ and thereby inhibits activation of NF-κB [11] , C6 that inhibits activation of IRF3 by interacting with adaptor proteins involved in the activation of TBK1 [19] and which suppresses the immune responses to infection [77] , [78] . Therefore , VACV is a useful tool for studying the innate immune system both to study known signalling mechanisms and discover novel molecules . Here we define a viral inhibitor of DNA-PK , a protein complex described recently as a PRR that senses foreign DNA , including the genomes of DNA viruses [22] . Using an unbiased mass spectrometry approach , VACV protein C16 is shown to bind to the Ku70/80 heterodimer , part of the DNA-PK complex . This direct protein/protein interaction occurs in cells , during ectopic expression of C16 and during VACV infection , as well as in vitro using recombinant purified proteins . By binding Ku70/80 , C16 is able to inhibit DNA , but not RNA , sensing in fibroblasts . Mechanistically , C16 achieves this inhibition by preventing the binding of Ku to DNA . This interaction has been localised to the C-terminal domain of C16 , and is also independent of the C-terminal domain of Ku80 . Interestingly , whilst C16 does not bind DNA-PKcs directly , and does not appear to bind Ku70/80 in direct competition with DNA-PKcs , it reduces the amount of DNA-PKcs bound to DNA . These observations are consistent with previous findings that , although DNA-PKcs can bind DNA directly , this interaction is greatly enhanced by the presence of the Ku heterodimer [66] , [79] , and that Ku70/80 is important for DNA sensing by the DNA-PK complex [22] . C16 was demonstrated to inhibit DNA-mediated activation of the innate immune system . Under the conditions tested this resulted in approximately a 50% reduction in the production of the pro-inflammatory molecules Cxcl10 and Il-6 . The remaining DNA sensing capability is likely explained by both incomplete penetrance of MEFs with C16-encoding plasmid , the abundance of the DNA-PK and further Ku-independent DNA sensors , such as IFI16 and cGAS shown previously to be operational in MEFs [37] , [46] . C16 has therefore evolved as a viral countermeasure to the detection of the VACV genome by the host innate immune system , and , as such , the loss of C16 contributes to the attenuation of this virus in vivo . The influence of C16 on virus virulence and the immune response to VACV infection in murine models has been described previously [63] and data in the present study add to the findings of that report . Infection of mice with VACV vΔC16 caused enhanced production of the chemokine Cxcl10 and the cytokine Il-6 in the lungs . Given the chemoattractive properties of these molecules , this likely explains the increased numbers of infiltrating leukocytes during infection with vΔC16 observed previously [63] . As with other viruses , the detection of the VACV genome is important for the host response to infection [22] . The discovery of a VACV protein that inhibits this process re-enforces this fact and shows the relevance of DNA-PK in vivo as a sensor of poxvirus DNA . In addition , the observation that VARV C16 can also bind to Ku70/80 is a strong indication that the pathogen that caused smallpox also evolved to inhibit DNA-PK-dependent DNA sensing . In contrast , the C16 orthologue encoded by VACV strain MVA has an internal deletion of five amino acids from its C16 orthologue that results in loss of binding to Ku70 . Similarly , internal deletion of 6 amino acids from MVA protein 183 , the orthologue of VACV WR protein B14 , ablated its ability to inhibit NF-κB activation [62] . The failure of MVA to inhibit detection of its genome may be partly responsible for strong innate and adaptive immune response to this virus . The role of DNA sensing in disease is an emerging field and its relevance to pathological processes beyond viral infection is beginning to be explored . Conditions such as Aicardi-Goutières syndrome [80] and systemic lupus erythematosus [29] , [81] , [82] have shown association with DNA sensing mechanisms , such as AIM2 , and it is possible that DNA-PK , or other DNA sensors , contributes to the disease process . In the future it may be possible to exploit the interaction between C16 and Ku70/80 as a model for the development of small-molecule inhibitors to alleviate pathological processes caused by the accumulation of intracellular DNA . In summary , this paper demonstrates an interaction between a known viral virulence factor and the Ku complex . This discovery led to the decision to investigate the potential role of DNA-PK in innate immunity , and consequently to the demonstration that it was a cytoplasmic DNA sensor that activates IRF3-dependent innate immunity [22] . To our knowledge the inhibition of DNA sensing by C16 represents the first viral interference with a dsDNA sensor shown to have an in vivo effect and adds weight to the hypothesis that DNA-PK is an important component of innate immunity . This work also strengthens the case for investigating the roles of microbial virulence factors due to the potential to discover novel features of the immune system .
This work was carried out in accordance with regulations of The Animals ( Scientific Procedures ) Act ( United Kingdom ) 1986 . All procedures were approved by the UK Home Office and carried out under the Home Office project licence PPL 70/7116 . Groups of five female BALB/c mice between six and eight weeks old were anaesthetised and inoculate intranasally with 5×104 plaque-forming units ( PFU ) of VACV strain WR intracellular mature virus ( IMV ) that had been purified by sucrose density gradient centrifugation and was diluted in 20 µl PBS . Mice were sacrificed at the specified time points under terminal anaesthesia with isofluorane and were exsanguinated from the subclavian artery . Bronchoalveolar lavage ( BAL ) fluid was harvested using five 200 µl lavages of lungs via the trachea and centrifuged to remove cellular debris . The C16 ORF was cloned into the pcDNA4 T/O expression plasmid using BamH1 and Not1 sites . The TAP-tag sequence comprised one STREP ( WSHPQFEK ) and two FLAG ( DYKDDDDK ) sequences at the C terminus of the protein . C16 was codon optimised for expression in mammalian cells by GenScript ( New Jersey , USA ) . HEK 293T and 293TRex ( Life Technologies ) cells were maintained in DMEM containing 10% FBS 100 U/ml penicillin and 100 µg/ml streptomycin . The 293Trex cell lines inducibly expressing C16 , icIL-1ra and the TAP-tag alone were clonally selected using 5 µg/ml blasticidin and 100 µg/ml zeocin . MEFs were maintained in DMEM containing 15% FBS . HeLa cells were maintained in RPMI containing 10% FBS and 2 mM L-glutamine . Transfections were carried out with Lipofectamine 2000 ( Life Technologies ) . Tandem affinity protein purification ( TAP ) was performed using Strep-Tactin superflow beads ( IBA ) and FLAG M2 agarose beads ( Sigma-Aldrich ) as described elsewhere [64] . Coomassie stained bands from tandem affinity purification procedures were excised using a sterile scalpel and placed in 100 µl H2O ( Sigma-Aldrich ) . Samples were analysed by liquid chromatography mass spectrometry ( LCMS/MS ) at the Centre for Systems Biology at Imperial College London . Cell lysates were separated by electrophoresis and transferred onto Immobilon P membranes ( GE Heathcare ) . These membranes were blocked in 5% nonfat milk in TBS containing 0 . 1% Tween 20 for 1 h at room temperature . Membranes were probed with Abs against Ku70 ( AbCam ) , Ku80 ( Santa Cruz ) , DNA-PKcs ( Upstate ) or C16 ( Generated by Harlan Sera-Lab ) . Ku80 , or control Abs were used for immunoprecipitation from HeLa cell lysates . Chemiluminescence imaging was used to develop immunoblots and quantification was performed using a Licor Odyssey scanner and band intensity was analysed using Odyssey software ( Licor Biotechnology ) . Cells were seeded onto 15-mm glass coverslips , and subsequently infected with VACV WR at 5 pfu/cell for 3 or 6 h as indicated . Samples were fixed with 4% paraformaldehyde and permeabilised with PBS containing 0 . 2% Triton X-100 and blocked with 5% non-fat milk in PBS with 0 . 1% Tween for 1 h at 20°C . Incubation with anti-murine IRF3 ( Life Technologies , Grand Island , NY ) diluted in PBS with 1% non-fat milk for 1 h was followed by detection with alexa-fluor-conjugated secondary antibody ( Life Technologies , Grand Island , NY ) . Cells were counterstained with DAPI and mounted with Mowiol . Images were obtained using a Zeiss Pascal 510 microscope and processed with Zeiss LSM software ( Zeiss , Oberkochen , Germany ) Levels of Cxcl10 and Il-6 in cell supernatants or BAL fluid were measured using ELISA kits ( R&D systems ) according to the manufacturer's instructions . Double stranded oligonucleotide DNA ( sense sequence , TACAGATCTACTAGTGATCTATGACTGATCTGTACATGATCTACA ) was biotinylated at its 3′ end and transfected into HEK293T cells using PEI ( Sigma ) . After 30 min , cells were lysed with a buffer containing 100 mM Tris-Cl , pH 8 , 0 . 2% Triton X-100 , 2 mM MgCl2 , 1 mM EDTA , and centrifuged at 600 g in a microcentrifuge and the pellet was discarded . Crude cytoplasmic extracts were obtained by a further centrifugation at 20 , 000 g . Biotinylated DNA was then purified from the supernatant using Streptavidin beads . BL21 ( DE3 ) -R3-pRARE2 cells expressing C-terminal His-tagged C16 ( C16-His ) from pET28a ( Novagen ) were lysed in lysis buffer ( 50 mM HEPES pH 7 . 4 , 500 mM NaCl , 5% glycerol , 30 mM imidazole pH 7 . 5 , 0 . 5 mM TCEP , 1 tablet of complete protease inhibitor ( Roche ) , 0 . 1% Triton X-100 ) and cell debris was removed by centrifugation . His-C16 was affinity purified through a 1 ml His-TRAP column ( GE Healthcare ) using a step-wise gradient of imidazole as indicated . The eluted fractions were concentrated using a 10-kDa cut-off concentrator filter ( Amicon ) and further purified by size exclusion chromatography ( Superdex 200 16/60 , GE Healthcare ) . To generate pFBDM-Strep-Ku70/Ku80ΔC for insect cell expression of Ku heterodimer containing a C-terminally truncated Ku80ΔC ( lacking residues 591–732 ) , human cDNA sequence encoding Ku801–590 was cloned into the XhoI and NheI sites of pFBDM , downstream of the p10 promoter . cDNA sequence encoding full length human Ku70 was sub-cloned into the BamHI/NotI sites of the same plasmid , downstream of the polyhedron promoter and in frame with an N-terminal Strep tag II . Ku70/Ku80ΔC was expressed and purified as described [83] , changing the first affinity step to Strep-Tactin resin ( Qiagen ) . A 5′ Cy3-labelled oligonucleotide ( 5′ GAAAGCTATGGGCGCGGTT 3′ ) was annealed to its complementary oligonucleotide to generate a 19-bp blunt-ended duplex substrate . Recombinant Ku70/Ku80ΔC and/or C16 ( aa157–331 ) were incubated at the concentrations indicated in 10 ml binding buffer ( 20 mM Tris–HCl pH 7 . 5 , 50 mM NaCl , 0 . 5% glycerol , 0 . 1 mg/ml BSA ) containing 10 nM Cy3-labelled DNA substrate for 15 min at room temperature . After adding glycerol to 5% total volume , the protein∶dsDNA mixtures were fractionated on a 5% native PAGE gel ( 37∶1 acrylamide∶bis-acrylamide ) run in 0 . 4× TBE at room temperature and 10 mA . The gel was subsequently scanned on a Fujifilm FLA-500 instrument using a 532-nm laser and Cy3 filter . For the coprecipitation experiments , 300 µl of 26 µM purified Strep-tagged Ku70/Ku80ΔC protein was added to 200 µl Strep-Tactin Superflow Plus Beads ( Qiagen ) pre-equilibrated in PBS and was incubated on a roller for 1 h at 4°C . Beads were washed four times with buffer A ( PBS supplemented with 0 . 2% BSA , 5 mM DTT , and 0 . 1% NP-40 ) . Purified C16 in PBS was added ( 250 µl of 12 µM ) and incubated with the beads for 7 h at 4°C on a roller . Beads were then washed four times with buffer A and resuspended in 4× SDS loading buffer ( Invitrogen ) . As a control , purified C16 was also incubated with Strep-Tactin Superflow Plus Beads that had not been incubated previously with Strep-tagged Ku70/Ku80ΔC . The control sample was treated as described before . All samples were analysed by SDS-PAGE using 4%–12% NuPAGE Bis-Tris gels ( Invitrogen ) run in 1× MES buffer ( Invitrogen ) . Statistical analysis was carried out using student's t-test with Welch's correction where necessary .
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To mount an immune response to an invading bacterium or virus ( pathogens ) , the host must detect foreign molecules from the pathogen . Pathogens have conserved features called pathogen associated molecular patterns ( PAMPs ) that are distinct from host cells and which are recognised by the host using specific sensors ( called pattern recognition receptors , PRRs ) . One example of a PAMP is DNA in the cytoplasm . Cytoplasmic DNA activates the innate immune system , but the PRRs responsible remain incompletely understood . One such PRR , DNA-PK , was identified recently . Here we demonstrate that vaccinia virus ( VACV ) , the vaccine used to eradicate smallpox , encodes a protein called C16 which binds to the DNA-PK complex and prevents it from sensing foreign DNA and activating the immune response . A VACV strain lacking C16 showed reduced virulence and , consistent with this , the host mounted a stronger innate immune response to infection . This illustrates the importance of DNA-PK as a sensor for foreign DNA , and increases understanding of the interaction between VACV and the host . It also illustrates how the study of virulence factors of pathogens can lead to the identification of novel components of the immune system .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"&",
"Methods"
] |
[] |
2013
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A Mechanism for the Inhibition of DNA-PK-Mediated DNA Sensing by a Virus
|
By combining high-throughput sequencing ( HTS ) with experimental evolution , we can observe the within-host dynamics of pathogen variants of biomedical or ecological interest . We studied the evolutionary dynamics of five variants of Potato virus Y ( PVY ) in 15 doubled-haploid lines of pepper . All plants were inoculated with the same mixture of virus variants and variant frequencies were determined by HTS in eight plants of each pepper line at each of six sampling dates . We developed a method for estimating the intensities of selection and genetic drift in a multi-allelic Wright-Fisher model , applicable whether these forces are strong or weak , and in the absence of neutral markers . This method requires variant frequency determination at several time points , in independent hosts . The parameters are the selection coefficients for each PVY variant and four effective population sizes Ne at different time-points of the experiment . Numerical simulations of asexual haploid Wright-Fisher populations subjected to contrasting genetic drift ( Ne ∈ [10 , 2000] ) and selection ( |s| ∈ [0 , 0 . 15] ) regimes were used to validate the method proposed . The experiment in closely related pepper host genotypes revealed that viruses experienced a considerable diversity of selection and genetic drift regimes . The resulting variant dynamics were accurately described by Wright-Fisher models . The fitness ranks of the variants were almost identical between host genotypes . By contrast , the dynamics of Ne were highly variable , although a bottleneck was often identified during the systemic movement of the virus . We demonstrated that , for a fixed initial PVY population , virus effective population size is a heritable trait in plants . These findings pave the way for the breeding of plant varieties exposing viruses to stronger genetic drift , thereby slowing virus adaptation .
Evolution in isolated populations results from the interplay between several forces , including mutation , selection , and genetic drift . Mutation creates genetic diversity within a population . Subsequent selection and genetic drift drive the evolution of diversity within the population . Selection is a deterministic force that increases the frequency of the fittest variants at the expense of the weakest ones . It can be characterized by the selection coefficient s , commonly calculated , at a specific locus , as the relative difference in fitness conferred by two alleles . Genetic drift , unlike selection , acts equally on all variants . It is the outcome of random sampling effects between generations , resulting in stochastic fluctuations in variant frequencies [1] . The strength of genetic drift is frequently evaluated by determining the effective population size Ne [1] . Ne is defined as the size of an ideal panmictic population of constant size with non-overlapping generations that would display the same degree of randomness in allele frequencies as the population studied [2] . Ne is often much lower than the census population size [3 , 4] , but it can be seen as its evolutionary analog [5] . When Ne is small , sampling effects are magnified between generations , and allele frequencies therefore fluctuate strongly . For populations varying in size over time , the effective population size over a given number of generations can be approximated by the harmonic mean N ¯ e of effective population sizes at each generation . This approximation holds provided that the number of generations is much smaller than N ¯ e [6–8] and that mutation can be neglected [9] . Population size may vary over time due to bottlenecks , which are common in natural populations . As they greatly decrease population size , they have a disproportionate effect on the overall value of N ¯ e [1] . When selection and genetic drift act simultaneously , the probability of fixation of a new mutation ( with a selection coefficient s ) , and , more generally , its evolutionary dynamics , is controlled by the product Ne × |s| [1 , 10] . If Ne × |s| ≪ 1 , then genetic drift predominates over selection and evolution is mostly stochastic . If Ne × |s| ≫ 1 , then selection becomes effective and evolution is mostly deterministic [10] . This rule of thumb can be applied to the evolutionary dynamics of pathogen variants of biomedical or ecological interest , during the course of infection of a single host , for microbe variants escaping the immune response of their host , or becoming resistant to drug therapy ( e . g . [11] ) or , in the case of plant pathogens , for variants adapting to host resistance genes ( e . g . [12] ) . In this study , we combined high-throughput sequencing ( HTS ) with experimental evolution to measure the within-host dynamics of five variants of Potato virus Y ( PVY , genus Potyvirus , family Potyviridae ) in closely related plant genotypes [13] . It remains challenging to unravel the effects of genetic drift and selection in the absence of neutral markers , in studies of the adaptation dynamics of pathogens . This situation is frequently encountered for pathogens with small genomes , especially viruses [14 , 15] . Various approaches based on moment [16 , 17] or likelihood [18–20] methods have been proposed for estimating Ne , but all require the genetic markers studied to be neutral . Various methods have also been proposed for detecting selection and estimating selection coefficients . These methods require at least some prior information about Ne ( e . g . [21] ) or assume that genetic drift is negligible ( e . g . [22] ) . However , in the absence of neutral markers and without prior estimates of Ne , both selection and genetic drift must be taken into account , as these two forces act simultaneously on evolution . This greatly complicates the estimation of Ne and s . Only a few methods have been proposed for the joint estimation of Ne and s from time-sampled data ( see [11] and [23] for a review ) . For large effective population sizes ( typically Ne > 5000 ) and small selection coefficients ( typically |s| < 0 . 01 ) , several likelihood methods based on diffusion approximations of the Wright-Fisher model [1 , 11] are available [24–27] . In the situations in which these methods are valid , the ranges of Ne and s values obtained are rather restrictive for many microorganisms , particularly viruses [28–31] . Foll et al . [32] recently proposed the use of approximate Bayesian computation ( ABC ) for the joint estimation of Ne and s in a Wright-Fisher model . Their method can deal with both weak and strong selection regimes , but still requires multilocus genome-wide data with mostly neutral loci to estimate Ne accurately . In this study , we investigated the evolutionary dynamics of five variants of PVY in 15 closely related pepper genotypes . All plants were inoculated with the same mixture of virus variants and variant frequencies were determined with HTS in eight plants of each genotype at each of six sampling dates after inoculation . A diverse range of evolutionary patterns was observed . We developed a method for estimating the parameters of a multi-allelic Wright-Fisher model with selection and genetic drift , to investigate the underlying evolutionary processes . This method has two main advantages: it applies to a large range of selection and genetic drift intensities and it works efficiently in the absence of neutral markers . The parameters of the Wright-Fisher model ( i . e . selection coefficients for each virus variant and effective population sizes at given time points ) can be estimated by coupling maximum likelihood and ABC methods and applying them to a set of variant frequencies determined at several time points in independent hosts . We tested the method with numerical simulations mimicking the datasets obtained with HTS in evolve-and-resequence experiments [33] . The simulations covered an extensive range of Ne and s values . We were then able to estimate the selection coefficient of each PVY variant in each pepper genotype and the changes in effective population size over time during the colonization of the plant by the virus . Finally , by varying pepper genotypes and fixing the initial PVY population , we provided evidence that the effective population size of PVY is a heritable plant trait . This finding paves the way for the breeding of plant cultivars exposing viruses to greater genetic drift and/or smaller selection effects .
We developed a method for estimating the parameters of a multi-allelic Wright-Fisher model with selection and genetic drift for a haploid population . The parameters and state variables of the model and the observed variables are summarized in Table 1 . Before using the estimation method on the datasets corresponding to the biological experiment , we performed several batches of simulations to assess its ability to infer effective population sizes and selection coefficients accurately ( see S2 Text for details ) . Briefly , in experiment 1 , we first simulated the changes in frequencies of five virus variants under 750 selection and genetic drift regimes with a Wright-Fisher model for haploid individuals . The simulations were designed to fit the experimental setup of our datasets ( 48 independent host plants regularly analyzed at 6 sampling dates ) . For each of the 750 datasets obtained , the true parameters θtrue were known and could be compared with the estimated parameters θ ^ . In experiment 2 , we assessed the sensitivity of the estimation method to the presence of a sixth undetected virus variant . This sixth variant was selectively neutral ( its selection coefficient is zero ) , present in the inoculum at a frequency of 3% and still present at the last sampling date ( 34 dpi ) in all plants analyzed , at frequencies ranging from 1% to 6% . It affected the dynamics of the five variants of interest in all plants but was not detected , so the variant frequencies measured by HTS ( and used to estimate θ ^ ) are noisy with respect to their true values . In all , 350 simulated datasets were analyzed in this second test .
The frequencies of the five virus variants were assessed in completely isolated populations during the course of infection , in 15 different plant genotypes . For each of these 15 pepper genotypes , 48 plants were inoculated with the same equimolar mixture of the five variants , and the frequencies of the virus variants were determined in eight plants at each of six sampling dates , from 6 to 34 days post-inoculation ( Fig 2 ) . In a few cases , no viruses were detected in plant samples ( lacking bars in Fig 2 ) . These negative samples may reflect the presence of an extreme bottleneck at inoculation , leading to virus population extinction , or a long time lag to systemic infection of the plant ( for measurements from 10 to 34 dpi ) , resulting in the sampling of leaves not yet infected ( e . g . DH line 2321 ) . Negative samples were most frequent for the first two dates on which systemically infected leaves were analyzed , i . e . at 10 and 14 dpi , probably indicating a time lag to systemic infection in some DH lines . Negative samples were observed in only four DH lines ( e . g . DH lines 219 and 2321 ) . No infection was observed in a mean of 3 . 5 ( resp . 2 . 0 ) plant samples 10 ( resp . 14 ) dpi for the four DH lines concerned . The virus populations present in all infected plants and in the common inoculum were analyzed by HTS , to determine the frequencies of the five PVY variants . Inoculum analysis confirmed that all variants were present in roughly equimolar proportions , with 22 . 6% of variant G , 17 . 5% of N , 20 . 6% of K , 17 . 1% of GK and 22 . 2% of KN . The raw data for variant frequency dynamics provided considerably different patterns between the 15 pepper genotypes ( Fig 2 , S2 and S3 Figs ) . Variant frequencies were similar between virus populations sampled on the same date in some plant genotypes , consistent with weak genetic drift ( e . g . DH lines 240 and 2430 , Fig 2A and 2B ) , whereas they differed in other plant genotypes ( e . g . DH lines 2321 and 219 , Fig 2D and 2E ) . Furthermore , the heterogeneity of variant frequencies between the eight plants analyzed fluctuated between dates , probably due to changes in effective population size during the course of infection ( e . g . DH line 2344 , Fig 2C ) . The four pepper genotypes for which some samples were virus-negative were also characterized by the highest heterogeneity in variant frequencies , consistent with an extreme bottleneck at inoculation and/or during systemic movement of the virus ( see DH lines 2321 , 219 , 2256 and 2400 in Fig 2D and 2E , S2D and S3I Figs ) . Selection regimes also differed between lines . In some DH lines , all variants remained present at all dates ( e . g . DH line 240 , Fig 2A ) , whereas one variant ( e . g . DH line 219 , Fig 2E ) , or up to two variants ( e . g . DH lines 2430 , 2344 , 2321 , Fig 2B–2D ) became extinct in others . Before its application to the experimental dataset , we validated the estimation method proposed by numerical simulations of a Wright-Fisher model with selection and genetic drift for haploid individuals . We estimated the Ne ( t ) and ri of the PVY populations in each DH line with a Wright-Fisher model including selection and genetic drift . By contrast to the numerical experiments , the evolutionary parameters underlying the true dynamics of virus populations in their hosts were unknown . The Wright-Fisher model fitted the data very satisfactorily ( Fig 5 ) . The best-fit line between observed and fitted mean variant frequencies ( averaged over all virus populations and sampling times ) was very close to the first bisector ( Fig 5A; slope = 0 . 92 , intercept = 0 . 01 , R2 = 0 . 92 ) . This was also the case for the variability of variant frequencies between virus populations at each sampling date td ( Fig 5B; slope = 0 . 92 , intercept = -0 . 09 , R2 = 0 . 84 ) . A Wright-Fisher model including selection and genetic drift accurately described the mean evolutionary dynamics of a virus population and the variability of these dynamics between hosts . Due to an identifiability issue ( we observed the relative frequencies of variants rather than variant densities ) , we had to fix the number of generations per day γ . We set this number to 1 , a value close to that reported by Khelifa et al . [40] . Different γ values would change ri and Ne ( t ) estimates to r i 1 / γ and γNe ( t ) , but would have no effect on their ranking . Relative fitness values ( ri ) ranged from 0 . 43 to 1 . 25 ( corresponding to |s|: 5% quantile = 0 . 004 , mean = 0 . 12 , 95% quantile = 0 . 27 ) and were associated with narrow 90% confidence intervals ( S3 Table ) . The fitness ranks of the PVY variants were very similar in most DH lines ( Fig 6A and 6C ) . Variant G was the weakest in all DH lines , followed by variant N in 13 DH lines . Variant GK was the fittest variant in 13 DH lines , with variant K the fittest variant in the remaining two lines ( DH lines 2256 and 2430 ) . Overall , variants K and GK were the two fittest variants in 12 DH lines; variants GK and KN were the two fittest in DH lines 2349 and 2321 , and variants N and GK the two fittest in DH line 219 . The fitness difference between the weakest and the fittest variants ranged from 0 . 14 for DH line 219 to 0 . 81 for DH line 2349 . We further estimated the dynamics of effective population size over the time course of the experiment , as modeled by a piecewise function Ne ( t ) , using a model selection procedure . Four models with one to four parameters were considered . The most general model M 4 distinguished four successive effective population sizes ( one in the inoculated organ and three during systemic infection ) . M 4 was the model best supported by the data for five DH lines ( 2173 , 2321 , 2328 , 2344 and 2367 ) . Model M 3 distinguished three successive effective population sizes ( one in the inoculated organ and two during systemic infection ) . It was best supported by the data for five DH lines ( 219 , 221 , 2256 , 240 and 2430 ) . Model M 2 , which distinguished two successive effective population sizes ( one in the inoculated organ and one during systemic infection ) , was selected for a single DH line ( 2426 ) . Finally , with M 1 , the effective population size of the virus population remained constant . This model was selected in the four remaining DH lines ( 2123 , 2264 , 2349 and 2400 ) . The corresponding posterior probabilities of each model are shown in S4 Table , together with effective population size estimates and 90% credibility intervals . At the first sampling date , considerable variability was observed ( Fig 6B and 6D ) , with effective population sizes ranging from 13 for DH lines 219 and 2256 to 1515 for DH line 240 . This was not surprising , given that we chose the DH lines on the basis of the density of primary infection foci in inoculated organs [34] ( S1 Fig ) . A much narrower range of effective population sizes , from 18 to 462 , was observed across all plant genotypes at 10 dpi , the first date on which systemic infection was observed . From 6 to 10 dpi , effective population sizes decreased in eight DH lines ( Fig 6B ) , remained approximately constant in six DH lines ( Fig 6D ) and increased slightly in a single plant genotype ( DH line 2173 , Fig 6D ) . Later on , from 10 to 34 dpi , effective population size increased in eight DH lines ( mostly DH lines displaying a bottleneck from 6 to 10 dpi , Fig 6B ) and remained approximately constant in the others ( mostly in DH lines with lower , i . e . < 500 , effective population sizes in the inoculated organ , Fig 6D ) . By creating two dataset replicates of 24 randomly chosen plants for each DH line , we estimated the heritability of two plant traits corresponding to the evolutionary forces exerted by the plant on virus populations: selection and genetic drift . These forces were estimated by ( i ) intrinsic rates of increase in viral variants and ( ii ) effective population sizes for PVY . With 24 plants in each dataset , we used the function Ne ( t ) of model M 2 with two parameters . In this approach , we used the contrasting behavior of PVY populations , which were fixed and identical at the time of inoculation in all plants , on different pepper genotypes to characterize the phenotype of each host . Very high heritability estimates were obtained for the intrinsic rates of increase ( mean heritability over the five variant estimates: h2 = 0 . 94 ) . Somewhat lower , but nevertheless substantial heritability estimates were obtained for effective population size in the inoculated organ ( mean heritability , h2 = 0 . 64 ) and for effective population size during systemic infection ( mean heritability , h2 = 0 . 63 ) . The details of the calculation are provided in S3 Text .
We present here a method for the estimation of selection and genetic drift in a haploid and asexual organism , as modeled by a Wright-Fisher process . As for any model-based approach , the population of interest must not be too far from an ideal Wright-Fisher population with suitable parameters [10] . The estimation method did not require neutral markers . It was validated for small effective population sizes ( Ne ≪ 100 ) and a wide range of both positive and negative selection coefficients ( weak ( |s| ≃ 0 . 01 ) or strong ( |s| ≃ 0 . 15 ) selection ) , using simulated datasets . Recent reviews [23 , 32] have highlighted the small number of methods available for the inference of selection and genetic drift over the whole range of variation , particularly in the case of small effective population sizes ( Ne ≪ 1000 ) and strong selection coefficients ( |s| ≃ 0 . 1 ) . Indeed , these conditions do not fulfill the hypotheses underlying most approximations of the Wright-Fisher model . The classical approximation , with a standard diffusion process , requires both selection and genetic drift to be weak [23] . Approximations based on Gaussian diffusion require the stochastic effects of genetic drift to decrease more rapidly than the effects of selection [23] . The work of Foll et al . [11 , 32] constituted a major step forward , but their method requires a large proportion of the genetic markers studied to be neutral . This assumption is not valid for many pathogens with small genomes , such as viruses . For example , only 22 . 7% of 66 randomly chosen mutations in the genome of Tobacco etch virus ( TEV , genus Potyvirus ) , a plant RNA virus , were found to be consistent with neutrality [45] . As the statistical power to detect departure from neutrality is limited , the true proportion of neutral mutations is probably much lower . Similar results have been obtained for bacteria ( e . g . [46] ) . The estimation method proposed does not require neutral markers , an appealing feature for studying pathogens with small genomes . Lacerda and Seoighe [47] recently developed another method that does not require neutral markers . Their method provided satisfactory estimates of both Ne and s ( estimated at a single locus ) for a relatively small effective population size of 1000 individuals and values of s up to 0 . 5 . They did not test the performance of their method for Ne ≪ 1000 . By comparison , the method developed here was effective for much lower Ne values , in the range of a few tens of individuals , and for inferring the time course of Ne over a few tens of generations . However , although the range of selection coefficients s included cases of strong selection ( |s| ≃ 0 . 1 , as defined by Malaspinas [23] ) , none of the simulation experiments included values as high as 0 . 5 . It may be possible to infer such high selection coefficients with the estimation method proposed , provided that the first generations are sampled more densely , typically every day after inoculation in our set-up . Lacerda and Seoighe [47] , for example , used samples taken at each generation , for 20 generations . This makes it possible to record the trajectories of variant frequencies before variant loss or fixation . The use of the proposed estimation method requires observation of the evolution of isolated populations derived from the same parental population , each population being sampled only once . This design is particularly suitable for studying within-host microbial evolution when several genetically-identical hosts ( 48 plants for each pepper genotype in our case study ) can easily be included in the experiment . With this experimental design , we observed a set of variant frequencies at several time points , in independent hosts . This set contained footprints of selection and genetic drift . In the method developed , selection is evaluated from the mean trajectories of variant frequencies . Genetic drift is evaluated at several time points , by assessing differences in variant frequencies between the replicated populations during the time-course of the experiment . Even for populations with small effective sizes , for which genetic drift and selection have confounding effects on the fate of variants ( Fig 2 ) , a moderate number of replicates contains sufficient information to disentangle the two mechanisms . Here , we estimated four selection coefficients and four effective population sizes ( i . e . 8 parameters ) with 48 samples ( 6 sampling dates × 8 replicates ) . The proposed estimation method could be improved further . It explicitly accounts for the technical sampling noise resulting from the assessment of variant frequencies from finite counts of virus sequences . However , HTS also introduces sequencing errors , albeit at a low rate of about 1 substitution per 400 bases for MiSeq technology [48] , which were not explicitly accounted for in our framework . Several models have been proposed for separating true genetic variation from technical artifacts [48] , and these models could be integrated into the method through a hierarchical Bayesian modeling framework [49] , for example . Finally , the method could be extended to take mutation and recombination into account , particularly for experiments over longer periods , in which new variants might appear and displace those currently most abundant . In our short-term experiment , we have already observed de novo substitutions in a few plants ( removed plant samples , see S1 Text ) . The inclusion of recombination is not relevant for our case study , as the nucleotide positions differentiating the variants are located only a few codons apart . Recombination can thus be ignored in this study [50] , particularly given the small number of generations considered [32] . On the host side , our experiment involved 15 DH lines of pepper , all carrying the major resistance gene pvr23 , but differing in terms of their genetic backgrounds [12] . These DH lines were derived from the F1 hybrid between two pepper lines , Perennial and Yolo Wonder . Consequently , on average , any pair of DH lines have 50 percent of alleles in common for markers differentiating between Perennial and Yolo Wonder . This is the first study , to our knowledge , to show such a high level of diversity in selection and genetic drift regimes experienced by virus populations from the same viral inoculum in closely related host genotypes ( Fig 2 , S2 and S3 Figs ) . On the pathogen side , we used five virus variants: the G and N variants displayed weaker adaptation to pvr23 than the K , GK and KN variants . The ranking of the selection coefficients of the five variants was mostly identical in the 15 plant genotypes . We were therefore unable to identify any host genotype , among those tested , able to counterselect against the virus variants best adapted to pvr23 . This may be due to ( i ) the strong selective effect exerted by the major-effect resistance gene pvr23 , which is present in all the DH lines studied here and probably exceeds the additional selective effect of the plant genetic background and/or ( ii ) the close genetic relatedness of the DH lines analyzed . Other genetic resources for pepper should be explored , to identify genotypes capable of counterselecting against the K , GK and KN variants , which were the fittest in our study . The best candidates for this would be pepper genotypes carrying pvr2 resistance alleles other than pvr23 , with a different specificity in the face of PVY diversity [51] , or pepper genotypes devoid of resistance alleles at the pvr2 locus , as shown by Quenouille et al . [12] . Combinations of plant genotypes exerting opposite selective pressures on pathogen populations are particularly interesting for the sustainable management of plant resistance at landscape level , and can be implemented in cultivar rotations , mixtures or mosaics [52] . However , in our study , the difference in fitness between the weakest and fittest variants differed between host genotypes . The dynamics of selection for the fittest variants were under plant genetic control and could therefore be modulated by the choice of plant genotypes grown . For example , growing the pepper DH lines with the smallest differential selection between the five PVY variants would be particularly useful for delaying PVY adaptation in pvr23-carrying plants , in which a two-step mutational trajectory may be required [12] . Indeed , the G and N variants are most likely to appear initially , because they require transitions , whereas the K variant requires a transversion , and transitions are more frequent than transversions [53] . However , an additional substitution , in a second step , is required to confer a sufficient level of fitness for the emergence of GK and KN variants . These mutational trajectories were observed in PVY adaptation to the Perennial pepper genotype , the resistant parent of all the DH lines studied here [12] . We also inferred the time course of the genetic drift experienced by the viruses in the 15 host environments during the experiment . Genetic drift intensities were highly variable with time and between plant genotypes , revealing an unprecedented level of variability between closely related host genotypes . Our estimates of Ne ( t ) ranged from 18 to 462 just after the colonization of apical leaves at 10 dpi , and from 13 to 1515 in the inoculated leaves four days previously ( at 6 dpi ) . Eight of the 15 DH lines displayed a high Ne in the inoculated leaves at 6 dpi ( from 421 to 1515 ) , a decrease at 10 dpi ( Ne ( 10 dpi ) values of 1 . 5 to 83 . 5% of the value at 6 dpi ) and a subsequent increase ( Fig 6B ) . This pattern suggests a founder effect , in which a new PVY population in apical leaves is set up by a few members of the original population in the inoculated leaf . In the remaining seven DH lines , the Ne of the inoculated leaves at 6 dpi was much lower ( from 13 to 462 ) , and Ne values often remained low in the apical leaves ( Fig 6D ) . However , an increase in Ne was observed in DH lines 219 and 2173 , after 14 dpi . This result sheds new light on the importance of the within-host bottlenecks experienced by virus populations , as discussed in a recent article by Zwart et al . [54] , who reported that the Ne of TEV in the first systemically infected leaf of tobacco plants was determined largely by inoculum viral load . They then hypothesized that genetic drift occurred mostly during the inoculation process . Previous estimations of Ne for viruses did not focus on Ne dynamics at the whole-plant level as in this study . Instead , they considered the multiplicity of infection ( MOI ) during cell-to-cell movement or Ne during the colonization of apical leaves ( for a comprehensive review , see Gutiérrez et al . [4] ) . Direct comparisons with these studies are , therefore , not appropriate . Gutiérrez et al . [55] recently showed that Turnip mosaic virus ( genus Potyvirus ) infections are characterized by a very low MOI ( ≃ 1 ) when cells are infected with virus particles moving in the plant vasculature , and a much higher MOI ( ≃ 30 ) during subsequent cell-to-cell movement in the mesophyll . The general picture that emerges when we consider both these MOI patterns and plant growth dynamics is consistent with our observations . Indeed , the lowest Ne values were observed at 10 dpi , corresponding to the onset of systemic infection , when plants were small and consisted essentially of a few infected leaves . Ne tends often to increase with time , because ( i ) increasing numbers of leaves are infected and behave as virus sources as the plant grows and ( ii ) leaf areas increase , probably increasing the relative proportion of cell-to-cell , as opposed to long-distance , virus movement . One of the key results of this study is the finding that the effective population size of PVY is a heritable plant trait . The high heritability estimated for Ne ( partially due to the use of a DH progeny of pepper genotypes ) indicates that plant resistance could potentially be improved through breeding programs . Indeed , our findings pave the way for the breeding of plant cultivars exposing viruses to greater genetic drift . This would provide a twofold benefit against viruses . First , in asexual populations , genetic drift favors the accumulation of deleterious mutations , decreasing viral fitness ( Muller’s ratchet ) [56] . Second , genetic drift decreases the fixation probability of beneficial mutations , such as those responsible for overcoming plant resistance genes [57] . Breeding for greater genetic drift in virus populations would thus constitute a novel approach to increasing the durability of resistance to plant viruses in agricultural landscapes [52 , 58 , 59] . Another key result is the finding that the Wright-Fisher model accurately captures the major processes driving the within-host dynamics of a set of virus variants ( Fig 5 ) , despite being much simpler than the underlying mechanisms involved in the infection of highly structured hosts . Over longer periods , mutation and recombination increase in importance and this can easily be encompassed in the Wright-Fisher model [60] . This model can thus serve as a valuable cornerstone for linking the within- and between-host scales of disease dynamics and studying , for example , how breeding for greater genetic drift can delay the emergence of a new pathogen variant .
|
A growing number of experimental evolution studies are using an “evolve-and-resequence” approach to observe the within-host dynamics of pathogen variants of biomedical or ecological interest . The resulting data are particularly appropriate for studying the effects of evolutionary forces , such as selection and genetic drift , on the emergence of new pathogen variants . However , it remains challenging to unravel the effects of selection and genetic drift in the absence of neutral markers , a situation frequently encountered for microbes , such as viruses , due to their small constrained genomes . Using such an approach on a plant virus , we observed that the same set of virus variants displayed highly diverse dynamics in closely related plant genotypes . We developed and validated a method that does not require neutral markers , for estimating selection coefficients and effective population sizes from these experimental evolution data . We found that the viruses experienced considerable diversity in genetic drift regimes , depending on host genotype . Importantly , genetic drift experienced by virus populations was shown to be a heritable plant trait . These findings pave the way for the breeding of plant varieties exposing viruses to strong genetic drift , thereby slowing virus adaptation .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"organismal",
"evolution",
"plant",
"anatomy",
"population",
"genetics",
"variant",
"genotypes",
"microbiology",
"genetic",
"mapping",
"plant",
"science",
"effective",
"population",
"size",
"microbial",
"evolution",
"population",
"biology",
"leaves",
"evolutionary",
"genetics",
"viral",
"evolution",
"genetic",
"drift",
"population",
"metrics",
"population",
"size",
"virology",
"heredity",
"genetics",
"biology",
"and",
"life",
"sciences",
"evolutionary",
"biology",
"evolutionary",
"processes"
] |
2017
|
Estimating virus effective population size and selection without neutral markers
|
An accurate diagnosis of helminth infection is important to improve patient management . However , there is considerable intra- and inter-specimen variation of helminth egg counts in human feces . Homogenization of stool samples has been suggested to improve diagnostic accuracy , but there are no detailed investigations . Rapid disintegration of hookworm eggs constitutes another problem in epidemiological surveys . We studied the spatial distribution of Schistosoma mansoni and hookworm eggs in stool samples , the effect of homogenization , and determined egg counts over time in stool samples stored under different conditions . Whole-stool samples were collected from 222 individuals in a rural part of south Côte d'Ivoire . Samples were cut into four pieces and helminth egg locations from the front to the back and from the center to the surface were analyzed . Some samples were homogenized and fecal egg counts ( FECs ) compared before and after homogenization . The effect of stool storing methods on FECs was investigated over time , comparing stool storage on ice , covering stool samples with a water-soaked tissue , or keeping stool samples in the shade . We found no clear spatial pattern of S . mansoni and hookworm eggs in fecal samples . Homogenization decreased S . mansoni FECs ( p = 0 . 026 ) , while no effect was observed for hookworm and other soil-transmitted helminths . Hookworm FECs decreased over time . Storing stool samples on ice or covered with a moist tissue slowed down hookworm egg decay ( p<0 . 005 ) . Our findings have important implications for helminth diagnosis at the individual patient level and for epidemiological surveys , anthelmintic drug efficacy studies and monitoring of control programs . Specifically , homogenization of fecal samples is recommended for an accurate detection of S . mansoni eggs , while keeping collected stool samples cool and moist delayed the disintegration of hookworm eggs .
Although schistosomiasis and soil-transmitted helminthiasis affect hundreds of millions of people and account for more than 40% of the global burden due to neglected tropical diseases , parasitic worm infections are often still neglected [1]–[3] . An accurate diagnosis is necessary for adequate patient treatment , a deeper understanding of the epidemiology of helminthiases , assessment of anthelmintic drug efficacy , and for monitoring the community-effectiveness of control programs [4] , [5] . The Kato-Katz technique is the current method of choice for the diagnosis of Schistosoma mansoni , Schistosoma japonicum , and soil-transmitted helminths in epidemiological studies [6]–[8] . However , the Kato-Katz technique has several shortcomings . First , there is a lack of sensitivity , with light infection intensities particularly prone to be missed [9]–[12] . Second , there is considerable intra- and inter-specimen variation of helminth egg distribution and aggregation in feces [10] , [11] , [13]–[16] . Interestingly though , contradicting findings have been reported on the spatial distribution of helminth eggs in human stool samples [16] , [17] . For example , two studies reported significantly higher S . japonicum fecal egg counts ( FECs ) on the surface compared to the center [16] , [17] . For S . mansoni , however , no significant differences in FECs have been found [18] , [19] . Similarly , no differences have been observed in the distribution of eggs of the two soil-transmitted helminths , Ascaris lumbricoides and Trichuris trichiura in human stool samples [20] . To date only two studies examined helminth egg distribution along the length axis of the stool and both focused on schistosome species [16] , [21] . Of note , in these studies , sample sizes were very small ( ≤11 individuals ) , and hence the reported results have to be interpreted with caution . Third , a time delay from stool production to processing the specimens in the laboratory is influencing the sensitivity of helminth diagnosis , particulary for hookworm [22] , [23] . Homogenization of fecal material has been suggested as one way to overcome intra-specimen variation of helminth egg counts [22] , [23] . However , the effect of homogenization on helminth FECs has yet to be determined . In fact , we could identify only two studies that examined the effect of homogenization on the variability of the distribution of S . japonicum , T . trichiura , and A . lumbricoides eggs within entire stool samples [17] , [20] . Another study merely states a suggestion about the effect of homogenizing based on findings about the similarity of FECs from the center and surface of stool [21] . Studies on soil-transmitted helminths concluded that homogenizing by stirring would not overcome the influence of intra-specimen variation of helminth egg location , while the study on S . japonicum showed that variation decreased after stirring [17] , [20] . Yet , the aforementioned features are likely to affect the performance of all diagnostic methods for which sampling of fecal material is involved . We therefore aimed to investigate the nature of intra-specimen variation of helminth egg distribution , to examine whether there is any effect of homogenization for the detection and quantification of helminth eggs in stool samples , and to monitor FECs over time in stool samples stored on ice , covered with a water-soaked tissue , or kept in the shade . Emphasis was placed on S . mansoni and hookworm infections . Results from our study might be of direct relevance for stool sampling and laboratory work-up in diagnostic centers , helminth epidemiological surveys , anthelmintic drug efficacy evaluation , and control programs .
The study protocol was approved by the institutional research commission of the Swiss Tropical and Public Health Institute ( Swiss TPH , Basel , Switzerland ) . Ethical approval was granted by the ethics committees of Basel ( EKBB , reference no . 377/09 ) and Côte d'Ivoire ( reference no . 1993 MSHP/CNER ) . District health and village authorities , study participants and parents/guardians of individuals aged <18 years , were informed about the purpose , procedures , and potential risks and benefits of the study . Written informed consent was obtained from participants or the parents/guardians of minors before the collection of the first stool sample . Participation was voluntary and there were no further obligation for those who withdrew from the study . All results were coded and treated confidentially . At the end of the study , all participants who provided a stool sample for the parasitological investigation were treated with albendazole ( single 400 mg oral dose ) and praziquantel ( single 40 mg/kg oral dose ) free of charge , irrespective of their helminth infection status . The study was carried out in Azaguié , a small town in the district of Agboville in south Côte d'Ivoire . Azaguié is situated approximately 40 km north of Abidjan , the economic capital of Côte d'Ivoire . Soil-transmitted helminthiasis and schistosomiasis are highly endemic [24]–[26] . There are four main seasons in the area , a long dry season from December to March , the main rainy season between April and mid-July , a short dry season from mid-July to mid-September , and a short rainy season from mid-September to November . The average temperature is 27°C and the annual precipitation is 1 , 200–1 , 500 mm . The study was conducted in September and October 2010 . Once local authorities and nearby schools had been informed , the research team invited all interested people of the area to come to an information session . After participants gave their written informed consent , they were supplied with an aluminum ‘take away box’ , together with a cover-lid , a sheet of aluminum foil , a sticker , and an instruction form explaining how to collect the stool sample ( Figure 1 ) . Participants were invited to place their fresh morning feces directly on the aluminum foil , while trying to keep it in a long , straight shape . Subsequently , participants were asked to wrap the stool into the foil without breaking it and place it into the ‘take-away box’ . The box was closed and a sticker put on the box to mark the front of the stool ( defined as that part of the stool that had left the bowel first ) . Mushy samples , where no front could be indicated , were not marked . Finally , participants were asked to note the exact time of defecation ( hh∶mm ) onto the lid and return the sample to the laboratory at the Azaguié health center , where the diagnostic work-up took place . In a first step , stool specimens were categorized into one of five consistency categories: ( i ) sausage-shaped ( equivalent to type 3 on the Bristol Stool Chart ( BSC ) [27] ) ; ( ii ) sausage-shaped-but-lumpy ( type 2 BSC ) ; ( iii ) sausage-shaped-but-soft ( type 4 BSC ) ; ( iv ) lumpy ( type 1 BSC ) ; and ( v ) mushy ( types 5–7 BSC ) . Next , samples of each category were randomly allocated either to the assessment of whole-stool homogenization or to the assessment of helminth egg distribution in stool by drawing lots . Figure 2 shows how samples designated for assessment of helminth egg distribution in stool were further stratified according to their consistency . In brief , sausage-shaped samples , including sausage-shaped-but-lumpy samples , were cut into four equally sized pieces along the length axis ( named front , second , third , and back piece ) . Care was taken that no fecal material was transferred from one piece to another . For each piece of stool , one Kato-Katz thick smear ( using standard 41 . 7 mg templates [28] ) was prepared from the center and a second one from the surface . Center samples were obtained by breaking open the stool piece without transferring fecal material from the surface region into the center , and by subsequently taking a small piece of stool from the center using a fresh spatula . Surface material was taken by scraping or cutting-off feces from the outer layer of the stool with a spatula , not invading deeper than 2–3 mm into the inside of the stool . Subsequently , the remaining part of the stool piece was put into a plastic cup and thoroughly homogenized by stirring with a plastic tongue spatula by two different laboratory assistants for at least 1 min each . A third Kato-Katz thick smear was then prepared from the thoroughly homogenized fecal material . Sausage-shaped-but-soft stool samples were cut into four equally long pieces as described above . However , these samples were too soft to properly take stool from the center and the surface . Hence , a first Kato-Katz thick smear was prepared from any unspecified region of the piece and a second one after the homogenization had been completed . Lumpy samples were not cut . Sufficiently big lumps were chosen and Kato-Katz thick smears were prepared from the center , surface , and the homogenized lump , as described above . Mushy samples of types 5 and 6 BSC were always allocated to the assessment of whole-stool homogenization , as they were not suitable for any of the other processing schemes . Very liquid samples ( type 7 BSC ) were excluded from the different diagnostic approaches as they were not suitable for any processing . However a single Kato-Katz thick smear was prepared from these samples to identify the participant's helminth infection status . From all samples allocated to the assessment of whole-stool homogenization , prior to homogenization , a first Kato-Katz thick smear was prepared by taking material from any unspecified region of sample , as mostly done in routine analysis . The rest of the whole-stool sample was then transferred into a plastic cup and thoroughly homogenized by stirring with a plastic tongue spatula by two different laboratory assistants for at least 1 min each . A second Kato-Katz thick smear was prepared from the homogenized whole-stool sample . To avoid confounding due to the time delay from production to examination of the different stool pieces , we established four distinctive examination time points , each lasting 2 h . At each time point , one stool piece per sample was randomly chosen to be examined using the aforementioned methodology by drawing lots . Using this approach , we assured that each piece of each stool sample was examined at a randomly chosen , but predefined time point of the day and we avoided introducing any systematic error into the analysis of egg distribution . Our rationale was as follows . If stool sections would have been analyzed in a systematic way ( i . e . , analyzing the front first and the back last ) and assuming that FEC might decline over time , we might have observed a spatial egg distribution pattern with eggs declining from the front to the back . However , in reality , this observation would be due to the effect of helminth egg decay over time rather than real spatial egg distribution . By randomly choosing the time point of analysis for each piece , the potential confounder ( i . e . , time ) is removed . Additionally , this procedure allowed us to monitor for potential change in FECs over time . Independent of their processing schemes , approximately one third of all samples were stored in a box kept on ice , a third was stored being covered with a tissue soaked with tap water , and the remaining third was stored without any additional preservation efforts but placed in the shade outside the laboratory . We adhered to World Health Organization ( WHO ) guidelines for Kato-Katz thick smear preparation and examination [29] , [30] . In brief , Kato-Katz thick smears were read by an experienced laboratory technician in a systematic way within a maximum of 60 min after preparation . The number of helminth eggs was recorded for each species separately . Ten percent of all slides were subjected to quality control and checked for internal consistency . In case of conflicting results , all Kato-Katz thick smears of that individual where re-read and the results of the second reading were used for analysis . Additionally , all data recording sheets were checked for internal consistency . Data were double entered by a single person into EpiInfo™ version 3 . 4 . 1 ( EpiInfo 2007 ) , checked for internal consistency and then analyzed with STATA version 10 . 1 ( Stata 2009 ) . A stool sample was considered positive for a specific helminth species if at least one egg was found in any of the slides examined . Egg counts derived from individual Kato-Katz thick smears were multiplied by a factor of 24 to obtain a standardized value of eggs per gram of stool ( EPG ) . Helminth species specific EPG values of each individual were categorized into infection intensities according to cut-off values provided by WHO [31] . A random effects negative binomial regression ( NBR ) model was performed for all assessments to check for the interaction of FECs between the different pieces or locations . Additionally , the Wilcoxon ( WXN ) signed rank test was used for categorical data whenever two categories were compared , and the Kendall's coefficient of concordance ( KCC ) was used to show the degree of agreement between FECs obtained in each stool part . A KCC value of 1 defines total agreement and a KCC value of 0 indicates no agreement . For the assessment of differences in FECs from formed stool and mushy stool , a non-overlapping 95% confidence interval ( CI ) indicates significance . For the assessment of the effect of homogenization , mushy stool samples were excluded because we assumed that they already were homogeneous .
Stool samples were collected from a total of 222 individuals aged 5–52 years with a median age of 12 years . Among them , 125 ( 56 . 3% ) were infected with at least one helminth species . However , nine helminth-positive participants were excluded from the statistical analysis because their samples were of insufficient amount to be examined with more than a single Kato-Katz thick smear . Of the remaining 116 stool samples , 34 were stored on ice , 45 in a box kept in the shade , and 37 covered with a water-soaked tissue . The whole-stool homogenization assay was performed with 53 stool samples and 63 samples were allocated to the assessment of helminth egg distribution in different locations of the stool . Details of the exact number of samples allocated to each examination procedure are shown in Figure 3 . Among the 222 study participants , 102 ( 45 . 9% ) were infected with S . mansoni , 23 ( 10 . 4% ) were positive for T . trichiura , 21 ( 9 . 5% ) for hookworm , and seven ( 3 . 2% ) for A . lumbricoides . Additionally , two participants ( 0 . 9% ) were infected with the tapeworm Hymenolepis nana ( Table 1 ) , but no further analysis was made for this parasite . Infections with two and three different helminth species were found in 25 ( 11 . 3% ) and seven ( 3 . 2% ) participants , respectively . With the exception of S . mansoni ( 35 . 5% of the positive individuals having ≥400 EPG ) and hookworm ( 4 . 8% of the positive individuals having ≥4 , 000 EPG ) , heavy infections did not occur . Most soil-transmitted helminth infections were light ( 92 . 5% ) and some were moderate ( 5 . 7% ) . Stool was produced between 05:30 and 11:10 hours ( median: 08:35 hours ) and collected between 07:52 and 11:19 hours ( median: 09:05 hours ) . On average , nine samples were collected each day ( range: 2–11 samples ) . One third of all samples ( 33 . 8% ) were sausage-shaped , 28 . 8% were mushy , 25 . 2% were sausage-shaped-but-soft , 7 . 7% were lumpy , and 4 . 5% were sausage-shaped-but-lumpy ( Table 2 ) . An interesting observation worth mentioning is that whole-stool samples were more likely very small when participants were infected with T . trichiura compared to participants infected with other helminth species ( OR = 1 . 88 ) . The delay from stool production to the start of the Kato-Katz preparations in the laboratory was , on average , 120 min ( range 20–300 min ) . In general , FECs of all helminth species in formed stool from type 1–3 BSC were significantly higher than in soft stool from type 4–7 BSC , with a combined mean FEC ratio of 947∶447 EPG ( 95% CI: 698–1 , 196 EPG versus 323–579 EPG ) . S . mansoni-positive stool samples ( n = 42 ) , showed no significant differences in FECs between different locations along the length axis ( zNBR = −1 . 60; p = 0 . 111 ) . There was an agreement of WKCC = 0 . 92 between the ranks of FECs in all four stool pieces ( p<0 . 001 ) . In hookworm-infected individuals ( n = 14 ) , FECs in the front piece of the stool sample were significantly higher than FECs in the back piece ( zNBR = −3 . 11 , p = 0 . 002 ) . In T . trichiura-positive stool samples ( n = 3 ) , FECs in the back piece were significantly higher than in the front ( zNBR = 2 . 63 , p = 0 . 008 ) . There was only one A . lumbricoides-positive sample among the samples dedicated to the assessment of helminth egg location , and hence no comparisons were made for this helminth species . Mean FECs of S . mansoni , hookworms and T . trichiura in the different stool pieces along the length axis of the stool , can be seen in Table 3 . For S . mansoni-positive individuals , no difference in FECs between the surface and the center of the stool samples was found ( zNBR = −1 . 88; p = 0 . 060; n = 95 ) . When eliminating pseudoreplication and analyzing only one randomly selected piece per stool sample , the effect was even stronger , but lacked statistical significance ( zNBR = 0 . 85; p = 0 . 276; n = 30 ) . Similarly , we did not detect any difference in FECs between the surface or center for hookworm-positive ( zNBR = −0 . 12 , p = 0 . 902; n = 4 ) and T . trichiura-positive stool samples ( zNBR = 1 . 85 p = 0 . 064; n = 3 ) . Mean FECs of S . mansoni , hookworms and T . trichiura in the surface and the center of the stool , can be seen in Table 4 . S . mansoni FECs decreased after homogenization of stool samples , irrespectively of whether whole-stool samples ( zWXN = 2 . 14 , p = 0 . 032; n = 16 ) or single pieces of a stool sample were homogenized ( zWXN = 2 . 23 , p = 0 . 026; n = 62 ) . The homogenization had an effect on the S . mansoni infection intensity category of 13 individuals: a change from heavy ( ≥400 EPG ) to moderate ( 100–399 EPG ) , from moderate to light ( 1–99 EPG ) , and from light to moderate intensity was each observed in 4 people . A change from light to heavy infection intensity was found in one individual . With regard to soil-transmitted helminths , no difference in FECs before and after homogenization was found , neither for whole-stool samples ( hookworm , p = 0 . 166 , n = 10; T . trichiura , p = 0 . 655 , n = 8; A . lumbricoides , p = 0 . 456 , n = 4 ) , nor for the homogenization of one randomly chosen piece per sample ( hookworm , p = 0 . 745 , n = 12; T . trichiura , p = 0 . 217 , n = 10; A . lumbricoides , p = 0 . 917 , n = 6 ) . Intra-sample variance of FECs decreased significantly after homogenization for S . mansoni ( zWXN = 4 . 53 , p<0 . 001 , n = 40 ) , but not for soil-transmitted helminths ( hookworm , p = 0 . 655 , n = 9; T . trichiura , p = 0 . 288 , n = 8; A . lumbricoides , p = 0 . 953 , n = 2 ) . Stratified by infection intensity , we found that the reduction of variance in S . mansoni FECs after homogenization only occurred with heavy ( p = 0 . 001 , n = 17 ) and moderate infection intensities ( p = 0 . 008 , n = 12 ) , but not with light infection intensities ( p = 0 . 588 , n = 11 ) . Additionally , the rate of Kato-Katz thick smears initially found positive that “changed” to negative after homogenization ( 14 out of 64 , 21 . 8% ) is nearly equal to the rate of Kato-Katz thick smears that were initially found negative and “changed” to positive after homogenization ( 17 out of 64 , 26 . 7% ) ( both p>0 . 5 ) . The ranks of FECs from S . mansoni did not differ between the different time points of stool examination , irrespective of whether samples were stored on ice ( WKCC = 0 . 87 , p<0 . 001 , n = 30 ) , covered with a water-soaked tissue ( WKCC = 0 . 87 , p<0 . 001 , n = 35 ) , or kept in the shade ( WKCC = 0 . 91 , p<0 . 001 , n = 42 ) . In hookworm-positive stool samples , we observed a significant decline of FECs over time for samples stored in the shade ( zNBR = −2 . 82 , p = 0 . 005 , n = 12 ) , although the agreement of the ranks of FECs determined at different time points was WKCC = 0 . 73 ( p = 0 . 001 ) . Thus , we performed an additional WXN test for the stool pieces that were analyzed first and the pieces that were analyzed last . The test confirmed a significant decline of FECs over time ( zWXN = 2 . 45 , p = 0 . 014 ) . If samples were stored on ice , no significant changes in FECs of hookworm were found over time ( WKCC = 0 . 84 , p = 0 . 005 , n = 12 ) . Samples kept humid showed no significant change of ranks of FECs over time ( WKCC = 0 . 87 , p<0 . 001 , n = 12 ) . For T . trichiura-positive samples , no difference in ranks of FECs between the measured time points were observed , neither for samples stored on ice ( WKCC = 0 . 61 , p = 0 . 080 , n = 3 ) , nor covered with a water-soaked tissue ( WKCC = 0 . 60 , p<0 . 001 , n = 4 ) , nor kept in the shade ( WKCC = 0 . 67 , p = 0 . 003 , n = 11 ) . Due to the small sample size for A . lumbricoides-positive samples in the assessment of FECs over time , no comparison was made .
An accurate diagnosis of helminth infection is of pivotal importance for adequate individual patient management , epidemiological surveys , intervention studies , and the monitoring of helminth control programs [4] , [32] . Despite its relevance for diagnosis , the spatial distribution of helminth eggs in entire stool samples , and the effect of storage , homogenization and time delays of FECs have been assessed only rudimentarily . Here , we present an in-depth analysis of a “piece of shit” , detailing the spatial distribution of S . mansoni and soil-transmitted helminth eggs within whole stool samples , and determined the effect of different stool storage approaches , homogenization and time delays from stool production to laboratory processing on helminth egg detection . The distribution of S . mansoni eggs without any clear pattern in whole stool speciments observed in our study corroborates with findings reported more than 40 years ago [21] . Our results , however , are in conflict with another study that reported a clear trend with S . japonicum eggs being predominantly located in the beginning and the surface of the stool [16] . These contradictions might either be due to a “real” difference between the egg distribution patterns of S . mansoni and S . japonicum , or due to the very low sample size ( n = 5 ) in the study of Yu and colleagues [16] . The authors speculated that differences in the spatial egg distribution of the two schistosome species might be due to the different location of the adult worms harboring in the mesenteric veins [16] . The predominance of observing hookworm eggs in the front of stool specimens revealed in our study cannot be generalized since , by chance , 10 among 14 front pieces of hookworm-positive stool samples were examined at the first time-point , and 11 of the back pieces either at time-points 3 or 4 . The decay of hookworm eggs as a function of time delays between stool production and processing revealed in our as well as previous studies [22] is the likely explanation of this observation . Hence , additional research is warranted to shed new light on the distribution of hookworm eggs along the main axis of entire stool specimens . Moreover , our finding that T . trichiura eggs are mainly located in the end pieces of stool is hampered due to the low size of positive samples . However , if future studies reveal or confirm that hookworm and T . trichiura eggs are mainly located in the front or end piece of the stool , this will have important implications on stool sampling procedures that should be taken into consideration for helminth diagnosis . Our observation of no difference in egg location between the center and the surface of stool samples for any of the helminth species encountered in the current study area is in line with previous studies [18] , [19] . However , although sample sizes for soil-transmitted helminth-positive stool samples in the present study are larger than in previous investigations , they remain small , particularly for A . lumbricoides and T . trichiura , and hence , results have to be interpreted with care . Unless future studies will show distinctive patterns of helminth eggs within stool samples , we feel that the current practice of scoping small pieces of stool anywhere from a stool specimen remains a valid method . Homogenization of stool samples reduced intra-sample variance of S . mansoni FECs . Hence , we recommend that stool sample be homogenized prior to diagnosis to enhance the accuracy of S . mansoni egg detection . This recommendation should be considered for standard operating procedures for S . mansoni diagnosis . Our study also confirms that , while time and storing method has no effect on FECs of S . mansoni and T . trichiura , hookworm FECs significantly decline with increasing time delays between stool production and laboratory processing of fecal material . Additionally we show – to our knowledge for the first time – that storing feces on ice or covered with a wet tissue can delay hookworm egg disintegration over time , which has important ramification for field procedures in any project involving hookworm diagnosis . Notably , hookworm eggs have been reported to be sensitive to dry conditions [33] . During our fieldwork we indeed observed that stool samples dried out quickly , especially on the surface . Hence , we recommend keeping stool samples humid pending laboratory work-up , best using a moist tissue , and regard this as a simple , cheap , and practical procedure to avoid hookworm egg disintegration . In other studies , refrigerating stool has been applied for the same purpose [22] and also in our study storing of fecal samples on ice was an effective strategy to delay the hookworm egg disintegration process . However , if concurrent diagnosis of Strongyloides stercoralis is envisaged , for example using the Baermann or Koga agar plate method [24] , , freezing or storing samples on ice is not recommendable , since S . stercoralis larvae present in stool are temperature-sensitive [38] . Our study is an important contribution to the broad field of schistosomiasis and soil-transmitted helminthiasis diagnosis . In particular , our findings that keeping stool samples on ice or covered with a moist tissue delays hookworm egg disintegration and the observation of a decreased variance through stool homogenization on the FECs of S . mansoni without impacting on soil-transmitted helminth eggs are worth highlighting . Introducing these simple measures will help to achieve more accurate estimations of FECs and infection intensities in helminth diagnosis . Together with the random spatial distribution of S . mansoni , hookworm , and T . trichiura eggs within entire stool samples , these observations should be taken into consideration for stool transport , storage , and examination in laboratories of travel clinics in the EU and the US as well as for hospitals , and epidemiological studies , clinical trials , and helminth control programs in endemic settings .
|
An accurate diagnosis of parasitic worm ( helminth ) infections is important for adequate patient treatment and disease control programs . Helminth eggs in human stool samples are used as an indicator of infection intensity and morbidity . However , little is known about the exact distribution of helminth eggs in stool samples . Homogenization has been suggested to improve the diagnostic accuracy . Hookworm eggs disintegrate over time , which makes their detection challenging in epidemiological surveys . We determined the location of helminth eggs in entire stool samples from 222 individuals in Côte d'Ivoire . We also investigated whether homogenization has an effect on the detection of eggs , and determined egg counts over time in stool samples stored on ice , covered with a moist tissue , or kept in the shade . No clear pattern of helminth egg distribution was found in human stool samples . Homogenization resulted in more accurate egg counts of the blood fluke Schistosoma mansoni , while it did not affect other helminths . Keeping stool samples on ice or covered with a wet tissue slows down the disintegration of hookworm eggs . Our findings have important implications for individual patient management and the design and implementation of epidemiological surveys and helminth disease control programs .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"public",
"health",
"and",
"epidemiology",
"epidemiological",
"methods",
"epidemiology",
"biology",
"microbiology",
"public",
"health",
"parasitology"
] |
2012
|
An In-Depth Analysis of a Piece of Shit: Distribution of Schistosoma mansoni and Hookworm Eggs in Human Stool
|
The evolution of cooperation among nonrelatives has been explained by direct , indirect , and strong reciprocity . Animals should base the decision to help others on expected future help , which they may judge from past behavior of their partner . Although many examples of cooperative behavior exist in nature where reciprocity may be involved , experimental evidence for strategies predicted by direct reciprocity models remains controversial; and indirect and strong reciprocity have been found only in humans so far . Here we show experimentally that cooperative behavior of female rats is influenced by prior receipt of help , irrespective of the identity of the partner . Rats that were trained in an instrumental cooperative task ( pulling a stick in order to produce food for a partner ) pulled more often for an unknown partner after they were helped than if they had not received help before . This alternative mechanism , called generalized reciprocity , requires no specific knowledge about the partner and may promote the evolution of cooperation among unfamiliar nonrelatives .
Cooperation among unrelated individuals may be achieved by reciprocal altruism in which two or more individuals help each other in turn [1 , 2] . The decision to cooperate is based on expected future help , which may be judged from past interactions . Most theoretical models of reciprocal altruism assume that individuals base their behavior on knowledge about a partner's previous behavior , either towards themselves ( direct reciprocity [3] ) or towards others ( indirect reciprocity [4–6] ) . According to direct reciprocity , A helps B because B has helped A before; individuals remember who did what in past interactions with them and base their decision whether to cooperate or defect on this knowledge [3] . According to indirect reciprocity , A helps B because B has helped C before; indirect reciprocity involves reputation , which increases through helping and is assessed to decide whether to help a partner or not [4–6] . Both direct and indirect reciprocity require that animals possess specific cognitive abilities [7] , which may impede the evolution of cooperation through these mechanisms . Strong reciprocity assumes that individuals punish noncooperators altruistically [8–10] . So far , experimental evidence for strategies predicted by direct reciprocity models remains controversial [11–16] , and indirect and strong reciprocity have been found only in humans so far [8 , 17] ( but see [18] for a possible example at the interspecific level in a cleaner fish mutualism ) . Recent theoretical models have shown that cooperation could evolve even without individual recognition in small groups when individuals base their decision on the outcome of previous interactions with anonymous partners [19 , 20] . This mechanism , called generalized reciprocity ( also “upstream tit-for-tat , ” or “upstream indirect reciprocity” [21 , 22] ) , leads to cooperation because previous interactions provide information about the overall level of cooperation within the group . For instance , if it pays more to cooperate in a cooperative environment than in a noncooperative one , generalized reciprocity may establish stable levels of cooperation when the decision to stay or leave a group evolves simultaneously with the decision to cooperate [23] . The selective force promoting cooperation in generalized reciprocity is thus of the type Lehmann and Keller [24] classified as “repeated interactions with direct or indirect information on the behavior of the partner in previous moves . ” However , it is important to note that under generalized reciprocity , individual recognition and specific social memory are not required , hence possibly this represents a more general mechanism leading to cooperation in animals than direct and indirect reciprocity , which require cognitive abilities potentially impeding their operation in animals [16 , 25] . Simple decision rules such as “walk away when encountering noncooperation” may suffice to stabilize cooperation [26] . Generalized reciprocity has been shown in humans; prior receipt of help increased the propensity to help a stranger [27–29] . A typical situation to show that past positive experience increases the future helpfulness of subjects towards unknown persons is that people who found a coin in the coin return of a public telephone were more likely to help a stranger pick up papers that had been dropped than control subjects [30] . To know whether such behavior is caused by cultural experience or shaped by natural selection , it is important to study whether similar reactions to anonymous experience can be found in nonhuman animals , which would clearly hint that an evolutionary mechanism is involved . For generalized reciprocity , special cognitive abilities are not required , as individuals only need to remember and act upon their own last experience with any partner . This may work with the help of rather simple hormonal or neuronal mechanisms triggering the propensity to cooperate . Yet , so far , to our knowledge , no experimental study has investigated the influence of anonymous prior experience on cooperative behavior in nonhuman animals . Here , we studied whether cooperative behavior in rats is influenced by social experience , irrespective of the identity of partners . First , we trained female wild-type rats ( Rattus norvegicus ) in an instrumental cooperative task; by pulling a stick fixed to a baited tray a rat produced food for its partner but not for herself ( Figure 1A ) . Second , we manipulated the focal rat's experience to receive help from a series of unfamiliar partners . The focal rat either experienced help by three different partner rats that pulled , or it experienced no help by three different partner rats that did not pull ( Figure 1B ) . Subsequently , we tested the focal rat's propensity to help another unfamiliar partner by recording the number of pulls it performed in a given period ( Figure 1C ) . One day after the experiment , we noted the pulling rate of each focal rat when alone in the experimental cage to check for intrinsic differences in pulling frequency ( Figure 1D ) . The situation was equivalent to the experiment , where the rat could move the platform into the cage by pulling but was unable to reach the reward .
Test rats that recently experienced help pulled more often than when they had not experienced help ( Figure 2 ) . The pulling frequency was on average 21% higher in the helper treatment than in the nonhelper treatment ( median = 0 . 86 pulls/min compared to 0 . 71 pulls/min; Z = −2 . 462; n = 19; and p = 0 . 014 ) . The median interval between placing an oat flake on the platform and pulling by the rat was shorter after cooperative experience than after receiving no help . Rats with previous experience of help pulled on average four times earlier ( medians: helper treatment , 6 s; nonhelper treatment , 24 s; Z = −2 . 486; n = 17; and p = 0 . 013; this difference is similar when the two rats that did not pull in one of the two treatments are included in the analysis , assuming an infinite pulling delay; Z = 2 . 133; n = 19; and p = 0 . 033 ) . However , the latency of the very first pull that the rats performed in the test situation did not differ significantly between both treatments ( medians: helper treatment , 13 s; nonhelper treatment , 34 s; Z = −0 . 853; n = 17; and p = 0 . 39 ) . The baseline pulling frequency when alone in the cage was lower ( median = 0 . 29 pulls/min ) than in the test phases of the helper treatment ( p < 0 . 01 ) and nonhelper treatments ( p = 0 . 017 ) , respectively , and it did not differ between treatments ( medians = 0 . 29 and 0 . 29; n = 10 + 9; U = 43 . 5; and p = 0 . 84 ) . Therefore , the intrinsic tendency to pull was not influenced by the experimental treatments .
Our results show that prior social experience changes the propensity of rats to cooperate , irrespective of the identity of the partner . After experiencing cooperation a rat is more helpful towards a new partner than after receiving no help . This indicates that reciprocal cooperation in iterated encounters is not necessarily based on specific knowledge about the partner , but that any prior experience of cooperation can be used . It is worth noting that pulling the stick was a cooperative act to the rats; they pulled very little when alone in the cage , and their intrinsic pulling frequencies did not differ after being subjected to the helper or nonhelper treatments . Which alternative learning mechanisms might explain the behavior of rats in our experiment ? Instrumental conditioning can be excluded as a mechanism to explain the observed behavior , because the test rat was not rewarded for her own behavior during the experience phase . Classical conditioning is unlikely , as in the nonhelper treatment focal rats also received the same amount of food . Also , both forms of conditioning are not supported by the data , because the intrinsic tendency to pull as measured at the end of the experiment was clearly not influenced by the experimental treatments . We can exclude that the focal rats in the nonhelper treatment learned that the platform would not work , because the nonhelper partner rats had not been trained in the pulling task and therefore did not even try to manipulate the stick or to pull . Also , the very first pulling latency of test rats did not differ between treatments . For the latter reason it is also unlikely that the differing performance was caused by “forgetting” how to perform the task in the nonhelper situation , when observations of a pulling rat were not as recent as in the helper treatment . Social learning is also implausible to be responsible for the different behavior of rats in both treatments; experience and test phases were performed on different days , so social facilitation was not involved . True imitation is unlikely , because ( 1 ) the focal rat was able to perform the required behavior already long before the experimental test in both the helper and nonhelper treatments , ( 2 ) the focal rat did not perform the behavior herself right after observing the partner rat in the experience phase , but only about 24 h later , and ( 3 ) imitation could hitherto not be demonstrated in rats despite intensive study [31] . Generalized reciprocity is hence the only hypothesis fully consistent with our results; the rats helped an unknown conspecific more readily because they received help before , even if from another anonymous partner . This is compatible with an “anonymous generous tit-for-tat”-like strategy , which was shown to establish cooperation in small groups [20] . To our knowledge , this is the first evidence for generalized reciprocity in nonhuman animals . The existence of this form of cooperation does not necessarily imply , however , that other selective forces are not at work in rats . In a follow-up study we tested whether the propensity to cooperate would be increased further when Norway rats interacted with a known partner who had helped them before [32] . As expected , this direct reciprocity caused even higher levels of cooperation than generalized reciprocity , i . e . , a rat was 50 . 7% more likely to help a conspecific who had helped her before than an unknown rat after experiencing cooperation with anonymous partners . This is compatible with a “hierarchical information hypothesis” assuming that specific information about the helping propensity of a partner is used if available , but if not , anonymous social experience is used when deciding whether to cooperate or not [32] , i . e . , cooperation may ensue also when specific information is limited or costly to be obtained . A similar mechanism might operate in humans [29] . Theoretical models showed that the existence of direct reciprocity in a population will induce the evolution of generalized reciprocity [22] , entailing much higher levels of cooperation overall . It is worth noting that despite the fact that direct reciprocity also operates in Norway rats , the results of this study cannot be accounted for by direct reciprocity in connection with errors in identifying individuals; the same individuals were tested in both experimental situations , so recognition errors cannot have biased the results in one direction . Generalized reciprocity is functionally related to the winner and loser effects , where anonymous social experience also influences behavior in subsequent interactions ( in this case agonistic behavior [33–35] ) . On the proximate level , physiological and neurological mechanisms causing winner/loser effects and generalized reciprocity might be similar [36] . It has been demonstrated experimentally that primates and rats exposed to socio-positive or socio-negative experience show significant hormonal changes [37 , 38] . These may critically affect the tendency to cooperate . Recently , oxytocin was shown to influence human prosocial behavior [39 , 40] , and it might also mediate positive social interactions in nonhuman animals [41] . A neurological study of human cooperative behavior showed that in women playing the prisoner's dilemma game , mutual cooperation was associated with consistent activation in brain areas linked with reward processing [42] , e . g . , the anteroventral striatum . When electrodes are placed in the striatum of rats , the animals will repeatedly press a bar to stimulate the electrodes [43] . Rilling and coworkers [42] suggested that the activation of these brain areas might positively reinforce reciprocal altruism . Our experiment revealed that cooperative behavior of Norway rats is influenced by anonymous social experience , despite their ability to distinguish individuals and their tendency to help particularly those who have helped them before [32] . We believe that this result may affect future studies of cooperation in two important ways . First , empirical data suggesting the potential operation of direct reciprocity may sometimes be interpreted more parsimoniously in terms of generalized reciprocity . So far , adequate controls to differentiate between direct and generalized reciprocity are missing in empirical studies of reciprocal altruism [44–46] , except for a study on chimpanzees demonstrating partner-specific exchange of altruistic acts [47] and our study on rats [32] . Second , theoretical approaches attempting to explain cooperation in an evolutionary context should account for the potential involvement of generalized reciprocity .
The rats were bred from eight pairs of wild-type rats ( Animal Physiology Department , University of Groningen , Netherlands ) and housed with same-sex littermates in groups of three to seven in cages ( 80 cm × 50 cm × 37 . 5 cm ) . Female groups could not interact with each other between cages because of the arrangement of cages . The housing room had an average temperature of 22 °C and a 12:12 h light:dark cycle with lights on at 20:00 hours . Food ( conventional rat pellets ) and water was provided ad libitum . Rats are predominantly nocturnal , and thus we performed our experiments during the dark phase in the morning hours . Only female rats were used in the experiment . The training of the rats in the operant cooperative task ( which is similar to the task used in [44 , 46] ) consisted of two steps . First , a single rat learned to pull a stick fixed to a baited platform to move it into the cage and reach the reward ( one oat flake ) . All rats learned to pull the stick in this situation within the first two trials of 10 min each . Second , each rat learned to pull alternately with a littermate , providing access to food for each other ( Figure 1A ) . For this , the two rats were placed in a cage that was separated into two compartments by a wire mesh . Only one rat had access to the stick and the opportunity to move the baited platform into the cage . The pulling rat had no access to the reward , only its partner did . In a subsequent session the roles were exchanged . Initially the partners pulled shortly after each other ( i . e . , one partner had to pull four times , then , the roles were exchanged immediately ) . The interval between the exchanges of roles was gradually increased to two days over a period of eight weeks . During this training phase each rat had 35 sessions in which she was in the role of the donor and 35 sessions in which she was in the role of the receiver , and she only interacted with one specific littermate . All rats pulled in this cooperative situation . The pulling rate was significantly higher when the partner was present than when the second compartment was empty ( medians [Wilcoxon-Test]: alone , 0 . 5; partner present , 0 . 8; p < 0 . 001; n = 20 ) , indicating that the propensity to pull was socially influenced ( see [48] ) . Thus the rats learned to cooperate by pulling the stick and to reciprocate with a specific partner . In our experiment we used this learned instrumental cooperative behavior to test the influence of social experience on cooperation in rats . In the experiment , only rats were paired that were unfamiliar with each other ( i . e . , had not interacted before ) and came from different cages ( i . e . , were not closely related ) . The focal rats were first exposed to a situation where they either received help ( test treatment ) or not ( control treatment ) from different partners to get food ( Figure 1B ) . In this experience phase the focal rats themselves could not pull for their respective partners . All 19 focal rats were exposed to both treatments in a random sequence . In the test treatment , on five successive days the rats received help from three different partners that pulled and moved the reward within reach of the focal rat ( i . e . , two partner rats were used twice ) . Each focal rat had only one session per day . The nine different helping partners had been trained in alternated pulling and were randomly assigned to the test rats . As an incentive each helping partner had been rewarded for pulling shortly before the test rat was put into the experimental cage . The session continued until the partner had pulled eight times , which was achieved on average within seven minutes . In the control treatment , the rats were paired with three different partners that did not pull . The nine nonhelping partners had not been trained in pulling , and the platform was mechanically prevented from moving towards the cage . In any other respect they did not differ from the helping partners , including familiarity with the experimental cage . Each partner was randomly assigned to the control rat . Again , the duration of a trial was seven minutes , and each focal rat had one session per day on five consecutive days . During each control session the experimenter also baited the tray eight times with one oat flake on the side of the focal rat . After each session the partner rat was removed first , and the focal rat received the eight oat flakes on the tray . To test for potential differences in behavior of partner rats between the test and control treatments during the experience phase , we compared the behavior of the nine trained and nine nontrained partners when paired with the same focal rat . The analysis revealed that there was neither a difference in the partner rats' social interactions with the focal rat ( p = 0 . 86 and Z = −0 . 178 ) , nor in their general activity ( p = 0 . 26 and Z = −1 . 125 ) , nor in the time spent in the quadrant in which they had access to the stick ( p = 0 . 77 and Z = −0 . 296 ) ( Wilcoxon-Tests ) . Therefore , to the best of our knowledge the only difference for the focal rats between treatments was experiencing help or not . On day six , each focal rat was paired with a new partner and consequently was in the role of the potential helper ( Figure 1C ) . The number of pulls performed by the rat was noted during a period of seven minutes . After four days , we repeated the experimental procedure by switching the experience treatment given to the focal rats . The partner rats providing the opposite experience were again new to the focal rats , whereas in the subsequent test helping behavior of each focal rat was tested with the same individuals as in the preceding treatment . Again , the focal rat herself did not pull in the entire experience phase . Observations were conducted in a blind fashion such that the experimenter did not know which focal rat was in the trial . The experimenter recorded the interactions on a monitor while sitting behind a sliding door . A new oat flake was placed on the platform ten seconds after each pulling event ( i . e . , after the partner rat usually had consumed the food ) . One day after the experiment , we compared the pulling rate of ten focal rats that had received help in the second part of the experiment with the pulling rate of nine focal rats that had not received help recently , when alone in the experimental cage ( Figure 1D ) . The rats could move the platform into the cage by pulling but were unable to reach the reward . Data were analyzed with nonparametric statistics using the software package SPSS 11 . 0 ( SPSS , http://www . spss . com ) . We compared individuals across treatments using two-tailed Wilcoxon matched-pairs signed-ranks tests . Bonferroni correction was applied to account for multiple testing ( pulling frequency and latency ) , thus reducing the significance level to α′ = 0 . 025 . For analyzing differences in pulling frequency between treatment groups after the experiment we used the Mann-Whitney U-Test .
|
The evolution of cooperation is based on four general mechanisms: mutualism , where an action benefits all partners directly; kin selection , where related individuals are supported; “green beard” altruism that is based on a genetic correlation between altruism genes and respective markers; and reciprocal altruism , where helpful acts are contingent upon the likelihood of getting help in return . The latter mechanism is intriguing because it is prone to exploitation . In theory , reciprocal altruism may evolve by direct , indirect , “strong , ” and generalized reciprocity . Apart from direct reciprocity , where individuals base their behavior towards a partner on that partner's previous behavior towards themselves , and which works under only highly restrictive conditions , no other mechanism for reciprocity has been demonstrated among conspecifics in nonhuman animals . Here , we tested the propensity of wild-type Norway rats to help unknown conspecifics in response to help received from other unknown partners in an instrumental cooperative task . Anonymous receipt of help increased their propensity to help by more than 20% , revealing that nonhuman animals may indeed show generalized reciprocity . This mechanism causes altruistic behavior by previous social experience irrespective of partner identity . Generalized reciprocity is hence much simpler and therefore more likely to be important in nature than other reciprocity mechanisms .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"ecology",
"evolutionary",
"biology",
"rattus",
"(rat)"
] |
2007
|
Generalized Reciprocity in Rats
|
There are currently no vaccines or antivirals available for dengue virus infection , which can cause dengue hemorrhagic fever and death . A better understanding of the host pathogen interaction is required to develop effective therapies to treat DENV . In particular , very little is known about how cellular RNA binding proteins interact with viral RNAs . RNAs within cells are not naked; rather they are coated with proteins that affect localization , stability , translation and ( for viruses ) replication . Seventy-nine novel RNA binding proteins for dengue virus ( DENV ) were identified by cross-linking proteins to dengue viral RNA during a live infection in human cells . These cellular proteins were specific and distinct from those previously identified for poliovirus , suggesting a specialized role for these factors in DENV amplification . Knockdown of these proteins demonstrated their function as viral host factors , with evidence for some factors acting early , while others late in infection . Their requirement by DENV for efficient amplification is likely specific , since protein knockdown did not impair the cell fitness for viral amplification of an unrelated virus . The protein abundances of these host factors were not significantly altered during DENV infection , suggesting their interaction with DENV RNA was due to specific recruitment mechanisms . However , at the global proteome level , DENV altered the abundances of proteins in particular classes , including transporter proteins , which were down regulated , and proteins in the ubiquitin proteasome pathway , which were up regulated . The method for identification of host factors described here is robust and broadly applicable to all RNA viruses , providing an avenue to determine the conserved or distinct mechanisms through which diverse viruses manage the viral RNA within cells . This study significantly increases the number of cellular factors known to interact with DENV and reveals how DENV modulates and usurps cellular proteins for efficient amplification .
Dengue is a mosquito-borne viral disease that infects 50–100 million people annually , resulting in dengue fever that is either asymptomatic or flu-like . However , tens-of-thousands of people develop the more severe , and sometimes fatal , dengue hemorrhagic fever/shock syndrome ( DHF/DSS ) [1] . DENV is found in most tropical and many subtropical areas with more than 125 countries being endemic for DENV [2] . There is no approved vaccine or antiviral therapeutic available for this life-threatening disease . Given the seriousness of infection , the expanding geographical range of the DENV , and the limitations in the existing measures of control and prevention , there is a pressing need to better understand the biology and pathogenesis of DENV . DENV is a single-stranded positive-sense RNA virus that belongs to the Flaviviridae family . It has a 5’ cap , no poly ( A ) tail , highly structured 5’- and 3’- untranslated regions ( UTR ) , and a single open reading frame ( ORF ) [reviewed in [3]] . Following virus entry , the viral RNA is released into the cytoplasm . Viral translation and replication occur in membranous assembly “factories” localized in the perinuclear region of endoplasmic reticulum ( ER ) [4] . The positive-stranded RNA molecules are encapsidated; virions are further processed as they are transported through the secretory pathway to the cell surface and released extracellularly [reviewed in [3]] . In addition to the viral proteins , cellular proteins , termed host factors , participate in most , if not all , steps of the DENV life cycle , including entry , translation , replication , virion assembly , and release [5] . Since viruses require host factors for efficient amplification , targeting host factors can provide an effective antiviral target for which the virus has no genetic control over . Therefore , it may be more difficult for viruses to evolve escape mutants that can replicate efficiently in the absence of the host factor [5 , 6] . Several cellular proteins are known to impact DENV infection . For example , the polypyrimidine-tract-binding protein ( PTBP1 ) is relocalized from the nucleus to the cytoplasm following DENV infection where it enhances DENV amplification by binding to the DENV 3’UTR and to NS4A , a viral protein required for the formation of the viral replication complex [7–10] . PTBP1 may also stimulate DENV translation [8] , although this is still controversial [7 , 9] . While most of the known DENV RNA binding proteins enhance viral amplification , several reduce DENV titers [10–12] . One such factor , YBX1 , inhibits viral translation [12] . Although previous studies have laid a foundation for establishing critical interactions between viral RNA and cellular proteins [[13] and reviewed in [14]] , the host factors identified thus far likely represent only a fraction of the total network of DENV host factors . Previously , we have described a high-throughput mass spectrometry method termed TUX-MS ( thiouracil cross-linking mass spectrometry ) to identify host factors that interact with viral RNA during a live infection in cell culture [15] . Importantly , TUX-MS allows for identification of proteins that are bound directly to the viral RNA in living cells . Briefly , during a viral infection in cell culture , thiouridine is biosynthetically incorporated into the viral RNA to serve as a zero-distance cross-linker upon exposure to ultraviolet ( UV ) light . Thus , proteins that are bound directly to the viral RNA during a live infection are cross-linked to the RNA prior to disruption of cellular compartmentalization . This is particularly valuable for the identification of DENV host proteins , since DENV amplification is tightly associated with cellular membrane structures [4] . Following cross-linking , the viral RNA together with cross-linked proteins are isolated under denaturing conditions and identified by mass spectrometry-based proteomics . Using TUX-MS , we reported previously the successful identification and validation of host factors for poliovirus , pointing to a low false discovery rate of < 12% [15] . Here , we expanded the TUX-MS methodology for use with other types of RNA viruses , and investigated RNA-protein interactions during DENV infection . We modified the method to use virus-specific DNA oligos to capture the viral RNA and cross-linked proteins . Furthermore , we used metabolic labelling with stable isotopes to accurately quantify relative protein levels . This quantitative thiouridine cross-linking mass spectrometry ( qTUX-MS ) analysis identified 79 novel host proteins , which were not previously shown to be involved in DENV infection . We placed these findings in the context of whole proteome changes upon DENV infection , and further validated and functionally analysed a subset of the novel DENV host factor candidates . Overall , validation of the qTUX-MS identified factors using secondary assays indicates a low rate of false positives ( 17% ) , suggesting that the majority of the other identified qTUX-MS factors may also play significant roles in DENV viral amplification .
HeLaUPRT cells expressing uracil phosphoribosyltransferase ( UPRT ) were generated previously by transduction of HeLa cells ( ATCC , CCL-2 ) with UPRT-gene containing lentivirus [15] . Huh7 . 5UPRT cells were generated by transduction of Huh7 . 5 cells ( a kind gift from Charles M . Rice , Rockefeller University ) with the same lentiviral construct as in [15] . HeLaUPRT and Huh7 . 5UPRT cells were cultured at 37°C and 5% CO2 in complete Dulbecco’s modified minimum essential medium ( DMEM ) supplemented with 10% FBS ( Fetal bovine serum; Atlanta Biologicals ) and penicillin-streptomycin and grown with 1 mg/ml G418 ( Sigma ) to select for the UPRT gene; Huh7 . 5UPRT cells were additionally supplemented with non-essential amino acids ( Cellgro ) . For SILAC labelling Huh7 . 5UPRT cells were passed 1:10 at least twice in SILAC DMEM ( Thermo Scientific ) with 10% dialyzed heat-inactivated FBS ( Thermo ) , L-proline ( 200 mg/L ) and penicillin-streptomycin , and either 50 mg/L ‘heavy’ ( 13C6 L-lysine and 13C6-15N4 L-arginine; Cambridge Isotope Laboratories , Inc . ) or 40 mg/L ‘light’ L-lysine and L-arginine amino acids [16] . Dengue virus serotype 2 ( DENV2 ) , strain 16681 ( Genebank Accession number U87411 ) was kindly provided by Dr . Robert Striker ( University of Wisconsin-Madison ) . DENV2 was propagated in the mosquito C6/36 cells at 28°C and 5% CO2 in advanced DMEM supplemented with 10% FBS , penicillin-streptomycin ( Cellgro ) , L-glutamate and 10% tryptose phosphate broth ( 20 g/L tryptose; 2 g/L glucose; 5 g/L sodium chloride and 2 . 5 g/L disodium hydrogen phosphate ) . Titers for DENV2 were determined using plaque assays in BHK cells . For infections , cells were incubated with virus containing media for 2 hours , washed twice with the DMEM media after removal of the virus and incubated in the serum-free DMEM for the indicated time . Infections and titer determination of adenovirus 5 ( Ad5 ) were performed exactly as in [15] . The DENV antisense biotin-labelled DNA fragments were generated using PCR and primers listed in ( S1 Table ) from the DENV2 complementary DNA ( cDNA ) and correspond to positions 4350–4914 and 4740–4914 of DENV genome . PCR was followed by removal of the unlabelled DNA strand according to the NanoLink Streptavidin Magnetic beads ( Solulink ) manual . The mixture of two biotinylated single-stranded DNA fragments of 174 base pairs ( bp ) and 564 bp long were bound to NanoLink Streptavidin Magnetic beads magnetic beads according to the manufacturer’s protocol . 1–3 X 107 human hepatoma Huh7 . 5UPRT cells labelled with either ‘light’ or ‘heavy’ SILAC media were infected with DENV2 ( MOI = 10 ) or mock-treated , respectively . Then , virus was replaced with SILAC media with 1 mM 4-thiouracil and 10% FBS . At 28 hours post-infection ( hpi ) the cells were washed with PBS and irradiated at 365 nm UV light for 20 min , collected , cell pellets were frozen on dry ice and stored at -80°C . Cell pellets were lysed in the lysis buffer ( 50 mM Tris-HCl pH 8 , 4 mM magnesium chloride , 150 mM sodium chloride , 0 . 1% Tween-20 , 5 mM dithiothreitol , Recombinant RNasin Ribonuclease Inhibitor [500 units/ml; Promega] , 1× cOmplete protease inhibitor cocktail [Roche] ) , with a half volume of 465–600 μm glass beads ( Sigma ) by shaking at frequency of 30 Hz for 1 min using a Retsch MM200 mixer mill . An aliquot of ‘light’ and ‘heavy’ cell lysates were removed and the remaining lysates were incubated with the Streptavidin Magnetic beads labelled with DENV antisense DNA fragments for 15 to 30 min allowing for viral RNA to bind . The beads were washed twice with wash buffer I ( 50 mM Tris-HCl pH 8 , 500 mM potassium chloride , 0 . 1% Tween-20 ) , once with wash buffer II ( 50 mM Tris-HCl pH 8 , 150 mM sodium chloride , 0 . 5% sodium deoxycholate ) and once with 10 mM Tris pH 7 . 6 . The samples were eluted at 65°C for 2 min in 20 μl of 10 mM Tris pH 8 . 0 . The eluted ‘light’ and ‘heavy’ samples were mixed at a 1:1 ratio , RNA was degraded with 0 . 5 ng/μL bovine RNase A ( Fisher Scientific ) at 25°C for 24 hrs and subjected to quantitative mass spectrometry-based proteomic analysis . Protein eluates and their respective mixed light/heavy input lysates were subjected to in-solution enzymatic digestion using a filter-aided sample preparation approach [17] , then analyzed by nLC-MS/MS , as described in S1 Methods and in [18] . Light ( DENV2 ) and heavy-labelled ( mock ) cell pellets were lysed in 100 mM ABC containing 5% sodium deoxycholate at 95°C to ensure denaturation and virus inactivation . The protein concentrations were determined by the BCA assay and mixed in equal protein amounts ( 100 μg total ) . Proteins were subjected to in-solution digestion with trypsin , then fractionated and analyzed by nLC-MS/MS as described in the S1 Methods . qTUX-MS , its respective mixed input lysate , and the whole cell SILAC instrument raw data were separately processed using the MaxQuant software ( ver . 1 . 5 . 3 . 8 ) , configured with default settings , except for experiment-specific parameters , which are described in the S1 Methods . The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [19] partner repository with the dataset identifier PXD003593 . Using the filtered list of protein identifications , unique gene symbols were used for downstream functional ontology analyses . The gene ontology annotations from UniProt were used to generate and assign the DENV2 RNA interacting candidates into broader functional categories . For the whole cell SILAC protein expression study , genes and their associated ratios were analyzed by PANTHER gene enrichment ( PANTHER database ver 10 . 0 , 2015-05-15 ) [20] using the PANTHER Pathway and Protein Class ontologies . Significant differential protein abundance was determined as a function of ontological classification versus the overall population ( Bonferroni-corrected p-value < 0 . 05 ) . For specific functional protein ontologies that were differentially regulated , a subset were selected for analysis by the Reactome Functional Interaction ( FI ) network Cytoscape plugin [21] . The Reactome FI plugin was used to visualize candidate host factors identified by qTUX-MS . 2 X 106 HeLaUPRT cells were transfected with 350 pmol of Silencer Select Negative Control ( Ambion ) or the specified siRNAs ( S1 Table ) using the XtreamGENE siRNA Transfection Reagent system ( Roche ) . 24 hrs later , 4 X 105 cells/well were plated for infection . 48 hours post transfection cells were infected ( MOI = 0 . 1 ) with DENV2 or Ad5 ( n = 3 ) . At either 30 ( Ad5 ) or 40 ( DENV2 ) hpi , virus titers were determined by plaque assays using 911 or BHK cells , respectively . Knockdown efficiency was measured 48 hrs post transfection by RT-qPCR . Experiments were performed in two biological replicates for each host factor . Statistical analysis was performed using student’s t-test . 24 hrs post siRNA transfection equal numbers of cells ( either 2 X 103 or 8 X 103 ) were seeded in 96-well plates . Cell viability was measured 48 hours after siRNA-mediated knockdown of individual host factors using the Vybrant MTT [3- ( 4 , 5-dimethyl-2-thiazolyl ) -2 , 5-diphenyl-2H-tetrazolium bromide] assay kit ( Invitrogen ) according to the manufacturer's protocol and reported relative to the negative-control siRNA ( set to 100%; n = 3 ) . Statistical analysis was performed using student’s t-test . cDNA was generated from 1μg TRIzol ( Ambion ) purified total RNA using Moloney murine leukemia virus ( MMLV ) reverse transcriptase ( Promega ) as described by the manufacturer using random primers ( Invitrogen ) . qPCR was performed using iQ SYBR green Supermix ( Bio-Rad ) with the primers listed in the S1 Table . The amplification efficiency for each primer set was 100±10% as determined using a standard curve .
TUX-MS can be used to identify host factors by incorporating 4-thiouridine ( 4sU ) , a zero-distance cross-linker , into the viral RNA ( vRNA ) to enable cross-linking of proteins bound to vRNA during a live infection in cell culture [15] . Cross-linking is carried out under physiological conditions prior to cell lysis to ensure specificity and reduce false-positives from non-specific RNA protein interactions that occur upon loss of compartmentalization . vRNA is isolated under denaturing conditions and cross-linked proteins are identified using liquid chromatography-tandem mass spectrometry ( LC-MS/MS ) . To improve quantification of the TUX-MS identified host proteins ( qTUX-MS ) , a SILAC ( stable isotope-labelled amino acids in cell culture ) approach [16] was used to label the uninfected ( mock ) and infected cells with either ‘heavy’ or ‘light’ amino acids , respectively ( Fig 1A ) . When 4-thiouracil ( 4TU ) is present in the medium , Huh7 . 5UPRT human hepatoma cell lines stably expressing UPRT ( uracil phosphoribosyltransferase ) convert 4TU to UMP . Then , the UMP is converted to thiouridine triphosphate ( 4sUTP ) by cellular kinases [22] . Both cellular and viral RNA polymerases use 4sUTP as a substrate during RNA synthesis , which serves as a zero-distance cross-linker , covalently binding proteins to RNAs upon exposure to long wave UV-light . Importantly , protein-protein cross-linking is very inefficient at long UV wavelengths , ensuring that only proteins in direct contact with the reactive thiol group of the 4sU-containing RNA will be cross-linked [23] . We have shown previously that immunoisolation of candidate vRNA-binding proteins identified by TUX-MS ( and confirmed by western ) could be specifically co-isolated with viral RNA [15] . Together , this study established that TUX-MS can identify bona fide interactions between host proteins and viral RNA . The TUX-MS method was originally developed to capture polyadenylated RNA using oligo ( dT ) beads [15] . However , as DENV RNA is not polyadenylated , we modified the method to use sequence specific capture of the vRNA using magnetic beads . Following crosslinking in Huh7 . 5UPRT cells infected with DENV at 28 hpi and affinity capture of the vRNA , the ribonucleoprotein complexes were eluted from the beads , ‘heavy’ and ‘light’ eluates were mixed , and RNase A was used to degrade the RNA . The proteins were digested in-solution with trypsin and subjected to quantitative MS-based proteomics ( Fig 1B ) . The median ‘light’ to ‘heavy’ peptide and protein ratios were calculated , reflecting the specificity of vRNA-protein capture . We identified several classes of proteins , including DENV proteins , known DENV host factors , and putative RNA-interacting host proteins , but most of the qTUX-MS identified factors have not been previously identified through interactions with DENV ( S2 Table ) . Consistent with previous knowledge of flaviviral RNA [24–27] , our qTUX-MS analysis identified several viral proteins—C , E , NS3 , NS4A and NS5—as associated with vRNA . In addition , qTUX-MS identified six known DENV host factors: polypyrimidine tract-binding protein 1 ( PTBP1 ) , interleukin enhancer-binding factor 3 ( ILF3 ) , calreticulin ( CALR ) , calnexin and heterogeneous nuclear ribonucleoproteins hnRNP H1 and hnRNP K , as well as a known DENV anti-viral protein—eukaryotic initiation factor 4A ( eIF4A ) —and 12 other proteins previously shown to associate with DENV RNA or proteins ( S2 Table ) . Altogether , since several known host factors were identified using qTUX-MS , this suggests that the adapted method is effective at identifying host factors for DENV . For identification of novel host factors , cellular proteins with a DENV/Mock SILAC ratio of ≥ 1 . 5-fold ( n ≥ 3 quantified peptides ) were considered putative DENV vRNA interactions . This threshold was selected when considering the median variance in the SILAC ratio ( for proteins with > 3 quantified peptides ) , which was approximately 25% . Therefore , we opted for a conservative cut-off at 50% , representing twice this median value or 1 . 5-fold . Common environmental and non-human cell culture contaminants were excluded , since they existed in only the ‘light’ SILAC state . In addition , our qTUX-MS samples also contained histones: H3 , H4 , H2A , H2B , H1 . 5 and macroH2A . 1 . In a previous study , histones were shown to play roles in dengue infection [28] . However , their functions were mediated through an interaction with a viral capsid protein and were shown to be independent of RNA . In addition , histones are primarily nuclear and highly abundant proteins commonly detected ( > 50% ) in control affinity purifications compiled across diverse protein-protein interaction studies [29] . For these reasons , histones likely represent non-specific associations rather than DENV RNA binding factors , and thus were excluded from further analysis . In total , 93 cellular proteins passed these selection criteria , 79 of which have not been previously shown to associate with DENV ( S2 Table , S1 Dataset ) . Several of the known DENV host factors were enriched but did not meet the stringent inclusion criteria ( S2 Table ) , suggesting that there may be additional host factors below our enrichment threshold ( see S1 Dataset ) . Importantly , the subset of 79 host factors represents a significant potential expansion in the number of known DENV host factors , providing a valuable resource to test for pro-viral or antiviral activities during DENV infection . It is well recognized that viral infections can induce significant changes in cellular proteomes [30–32] and an increase in protein levels during DENV infection may contribute to the increased protein capture measured by qTUX-MS . To address this , we used SILAC-MS to quantify proteome ( i . e . , total protein abundance ) changes following DENV infection . Comparison of qTUX-MS and proteome SILAC ratios showed that the protein abundances for the 93 qTUX-MS-identified vRNA-binding factors remained largely unchanged ( Fig 2A , S1 Fig and S1 Dataset ) . On average , for these proteins , the DENV-induced changes in whole cell abundance were ±1 . 1-fold , suggesting that their identification by qTUX-MS was not due to an increase in their abundance in the cell following DENV infection . Noteworthy , a retrospective qualitative comparison of the qTUX-MS identified factors for DENV with those identified in the TUX-MS analysis on poliovirus revealed less than 10% were identified for both viruses [15] ( Fig 2B ) . Since the identified proteins are largely DENV specific , qTUX-MS is not biased towards identifying a sub-set of cellular RNA binding proteins . Taken together , our results indicate that the enrichment ratios measured by qTUX-MS is predominantly due to their specific association with the DENV RNA . While proteins that bound DENV RNA did not show significant changes in abundance upon infection , we performed bioinformatics analysis on the complete proteome dataset of whole cell abundance to determine the global proteome effects of DENV infection under these conditions . In total , 4 , 907 host proteins were quantified by SILAC MS in biological duplicates ( S1 Dataset ) . The abundance ratios between biological duplicates were reproducible , with only ~ 2% of the ratios varying by > 50% ( Fig 3A ) . From these duplicates , an average abundance ratio was calculated and the respective proteins were analyzed by PANTHER gene enrichment analysis ( S2 Fig ) [20] . This analysis found systematic up regulation of proteins in the ubiquitin proteasome pathway ( UPP ) , comprising 18 members of the 26S proteasome as well as various ubiquitin-conjugating enzymes ( S3 Fig ) . Many of these enzymes are linked to ubiquitin-dependent proteasome degradation , consistent with the current knowledge that the UPP is important for production of infectious virions [31 , 33 , 34] . Yet , other enzymes , such UBE2N and UBE2V2 , catalyze polyubiquitination at Lys-63 , which does not lead to proteasome degradation but rather participates in transcriptional activation of target genes and may promote innate immune signaling [35 , 36] . In contrast , proteins in the transporter protein class were on average down regulated ( Fig 3B and S2 Fig ) . Assembly of the annotated proteins into Reactome protein networks identified several subnetworks with various transporter activities ( S4 Fig ) . While the abundances of mitochondrial transporters and nucleoporins were the most consistently decreased , not all transporters were down regulated; for example , the lipoprotein ( APO ) transporters were increased in expression ( Fig 3C ) . Interestingly , the RNA binding protein class was significantly down regulated ( Fig 3B and S2 Fig ) , though the effect was not as pronounced as the transporter class ( Fig 3B ) . The overall down-regulation of RNA binding proteins appears to be driven by changes in cytoplasmic and mitochondrial ribosomal subunits , and proteins involved in RNA degradation and processing ( S5 Fig ) . Nevertheless , the relative protein abundance for the set of 93 ( known and putative ) DENV binding factors identified by qTUX-MS was largely unchanged , despite being enriched in RNA processing and translation factors ( Fig 2A ) . Overall , the quantitative proteome analysis suggests that DENV selectively alters the abundance of proteins , and reveals several pathways that could be directly or indirectly modulated in the host response to DENV infection . To gain insight into potential molecular mechanisms and biological processes of the 93 qTUX-MS identified factors , we performed a functional network-based analysis using the curated human pathway relationships from the Reactome database . This analysis revealed a high degree of connectivity , with 62 proteins forming a large interconnected network ( Fig 4 ) . The densest network connectivity included proteins involved in RNA Processing/Translation ( orange nodes ) and DNA binding/Transcription ( blue nodes ) . Several additional proteins with RNA and/or translational activities were also identified , but lacked annotation in Reactome ( orange single nodes ) . Overall , our bioinformatic evaluation further supports the ability of qTUX-MS to capture vRNA-bound host factors and points to their possible function in DENV amplification . Since most of the factors were associated with RNA processing in the Reactome analysis ( Fig 4 ) , we focused on these factors for functional analysis of their roles in dengue infection . We have randomly selected six qTUX-MS identified host proteins with functions in RNA processing/translation , which were enhanced in the DENV sample ranging from 1 . 32-to 2 . 26-fold ( DENV/mock ) . Thus , by validating factors that are only modestly enhanced in the qTUX-MS analysis this will indicate if the qTUX-MS identified factors that are near the cut-off of 1 . 5-fold are bona fide host factors or not . We assessed the effect of siRNA knockdown of these factors ( Fig 5A ) on viral production . HeLaUPRT cells were used for siRNA silencing experiments due to higher siRNA transfection efficiency compared with Huh7 . 5UPRT cells . Knockdown of five out of six qTUX-MS identified candidates: Non-POU domain-containing octamer-binding protein ( NONO ) , Embryonic stem cell-specific 5-hydroxymethylcytosine-binding protein ( HMCES ) , RBMX ( RNA-binding motif protein , X chromosome ) , hnRNP M and hnRNP F significantly decreased DENV production , while knockdown of hnRNP L had no effect on DENV titer ( Fig 5B; S5 Fig ) . Knockdown of PTBP1 , a positive control [7 , 8] , also resulted in decreased viral titers ( Fig 5 ) . For negative controls , we selected two RNA binding proteins ( DDX39 and hnRNP A0 ) that were not identified by qTUX-MS . DENV titers were not altered following silencing of these two proteins , suggesting that only specific RNA binding proteins are used by DENV . Altogether , our data suggests that RBMX , NONO , HMCES , hnRNP M , hnRNP F are required for viral production . These results demonstrate that qTUX-MS is a robust method with a low false discovery rate for high-throughput identification of viral host factors . Reduced viral amplification could be due to compromised cell fitness rather than a specific requirement of the virus for a particular host factor . Using an MTT assay , we confirmed that knockdown of these factors did not impact cell viability ( Fig 5C ) . As a positive control , knockdown of G3BP2 did reduce cell fitness , as previously shown ( S6 Fig ) [37] . To more rigorously rule out any potential effects of host factor knockdown on cell fitness that would affect viral amplification , an unrelated virus ( adenovirus 5 ) , was amplified following knockdowns of the candidate factors . Adenovirus 5 replication was not significantly decreased by RBMX , NONO , hnRNP M , hnRNP F or HMCES siRNA knockdown ( Fig 5B and S6C Fig ) demonstrating that knockdown of these factors does not affect cell fitness for viral amplification . Given that these proteins bind directly to viral RNA and are required for viral amplification , RBMX , NONO , hnRNP M , hnRNP F and HMCES are novel DENV host factors . To determine if the host factor is required for a step prior or subsequent to viral replication , vRNA was quantified by qRT-PCR in the DENV infected cells knocked down for RBMX , NONO , hnRNP M , hnRNP F or HMCES ( Fig 6 ) . As a positive control , knockdown of PTBP1 , which is required for DENV replication [7] , reduced DENV RNA levels . Similarly , the intracellular vRNA levels were reduced in cells knocked down for either hnRNP F , RBMX or HMCES . The decrease in dengue RNA levels ( Fig 6 ) is consistent with the decrease in viral titers ( Fig 5B ) . Thus , hnRNP F , RBMX or HMCES are required for the early steps in the viral replication cycle , such as translation , replication or RNA stability . In contrast , knockdown of hnRNP M and NONO did not change intracellular viral RNA levels despite the dramatic decrease in viral titers , suggesting they may play a role downstream of replication . Altogether , we have identified and validated five novel host factors for DENV , demonstrating that qTUX-MS can identify factors that function at different stages of the virus life cycle .
An estimated 40% of the world’s population is at risk from dengue for which vaccines or antivirals are not yet available . Since diagnostic tests can detect DENV infection at early stages , administration of antivirals could significantly improve survival rates as viral load is correlated with symptom severity [38] . Using antivirals that target host factors may limit the appearance of drug-resistant viruses and may be effective for all DENV serotypes and possibly for multiple flaviviruses [5 , 6 , 39 , 40] . The qTUX-MS analysis identified 79 novel cellular proteins , for which the majority are distinct from those previously identified for poliovirus using a similar approach [15] . This suggests that unrelated RNA viruses have evolved to utilize distinct host RNA binding proteins . Interestingly , PTBP1 and NONO , which were identified in both the poliovirus and DENV TUX-MS analyses , were shown to be required for production of both viruses ( this study , Figs 5 and 6 ) [15 , 41 , 42] . Further analysis of virus-specific and shared host factors will reveal whether unrelated viruses utilize similar or diverse mechanisms to control viral RNA replication , processing and packaging within cells . The host factors that enhance amplification of both poliovirus and dengue , ( Fig 2B ) could serve as attractive targets for the development of broad-spectrum antivirals . The novel DENV RNA interactions identified in our study reveal a large network of cellular proteins which belong to different functional classes primarily associated with the nucleic acid metabolism , including numerous components of splicing , RNA processing and translation machineries . These factors likely play direct roles in DENV translation , replication or packaging . In addition , we have detected multiple components of cell signaling and stress response , such as several members of 14-3-3 adapter proteins , heat shock proteins and β-catenin . These factors are known to regulate diverse pathways , including host innate immune and cellular homeostasis [43–45] suggesting their possible role in host antiviral response or viral strategies to subvert the innate immune response . We demonstrated that the majority of the qTUX-MS factors that we selected for validation were required for efficient DENV amplification ( Fig 5 ) . Specifically , we found that hnRNP F , HMCES and RBMX are required for the early steps in the viral life cycle . In contrast , hnRNP M and NONO appear to act downstream of viral RNA replication ( Fig 6 ) , which may be significant given that both have been shown to be in a complex together [46] . NONO and its binding partners are predominantly nuclear , bind RNA , and are involved in pre-mRNA processing , splicing , and RNA transport , as well as in transcriptional activation and repression [47–49] . Interestingly , other NONO binding partners: PSF/SFPQ ( polypyrimidine tract-binding protein ( PTB ) -associated splicing factor ) and Matrin3 were identified by qTUX-MS as well . Many of the qTUX-MS identified cellular proteins are hnRNPs , which encompass a large class of RNA binding proteins that either localize to the nucleus or shuttle between the nucleus and the cytoplasm in order to perform multiple functions in RNA metabolism , from transcription to RNA turnover [50–52] . Importantly , the vast majority of these factors have established roles in viral infections or in modulating the antiviral host response to various viruses [53–56] , including DENV ( S2 Table and references within ) . Our study establishes that RBMX ( hnRNP G ) , hnRNP F and hnRNP M are required for efficient DENV amplification ( Fig 5B ) . Since several hnRNPs , such as PTBP1 ( hnRNP I ) , hnRNP A1 and hnRNP K , were previously shown to re-localize from the nucleus to the viral replication sites during DENV infection [8 , 57 , 58] , RBMX , hnRNP F , hnRNP M and possibly other nuclear qTUX-MS identified factors are also likely to be either actively recruited to the viral replication sites or retained in the cytoplasm upon DENV infection . Interestingly , the qTUX-MS identified hnRNPs affect different steps in the DENV life cycle ( Fig 6 ) , suggesting that they have distinct functions during infection . This is consistent with studies that have suggested that DENV RNA structures are dynamic during the viral life cycle [59] and may suggest that host factors play an important role in these structural changes . Furthermore , we showed that knockdown of some hnRNPs ( hnRNP A0 and hnRNP L ) did not affect dengue viral titers significantly demonstrating that only certain hnRNPs are required for DENV amplification . Since some of hnRNPs are known to modulate cellular gene expression in response to dengue infection [60 , 61] , we can not rule out that some of the observed effects on virus titers derive from their roles in regulating host mRNAs . Among the numerous qTUX-MS identified factors of interest , our study is the first to demonstrate the involvement of HMCES ( or C3orf37 ) in viral infection . While the cellular role of human HMCES is currently unknown , the mouse homologue was suggested to be an RNA-binding protein and predicted to contain a putative peptidase domain [62 , 63] . Interestingly , it is possible that the nucleic acid binding domain enhances the protease activity or visa versa as has been shown for other such proteins [64–66] . For example , Adenovirus uses a nucleic acid binding protease to localize the protease activity to the viral substrates [64] . It has been suggested that the protease is recruited to the empty capsid as an inactive protease , then it becomes fully activated once bound to the viral DNA inside the virion . Using the DNA as a guide wire , it moves along the nucleic acid , searching for capsid and core proteins to cleave , which is required to render the viral particle infectious [64 , 67 , 68] . However , since we observed that knockdown of HMCES resulted in a decrease in viral RNA , it seems more likely that it might participate in translation , replication or the switch from translation to replication as has been shown for other nucleic acid binding proteases [65 , 69] . Only one of the qTUX-MS identified factors was increased at the protein level in whole cells following DENV infection , suggesting that qTUX-MS identifications derived from the specific associations to vRNA rather than changes in protein abundances . Our analysis of the host cell proteome upon infection also revealed interesting changes , including up regulation of proteins in the ubiquitin pathway and down regulation of transporter proteins . The ubiquitin-proteasome pathway is one of two major cellular pathways used to degrade 80 to 90% of proteins . Previous studies on DENV infected cell lines and patient samples showed that the ubiquitin pathway was upregulated [31 , 39 , 70] . Many groups have consistently shown that the ubiquitin proteasome pathway is critical for amplification of a number of flaviruses , including DENV and West Nile virus [31 , 34 , 71 , 72] . However , it remains controversial as to which step in viral amplification is affected by ubiquitination , but it appears to be early during internalization or viral genome release [33 , 39 , 73] . Further studies will be required to understand how DENV up-regulates the pathway and the mechanism that ubiquitination has in DENV amplification . Altogether , our study has significantly increased the number of cellular proteins known to interact with the DENV RNA during a live infection in cells . We have also placed these interactions in the context of proteome abundance changes in the infected cells . A recent study by Phillips and colleagues [13] exploited a cross-linking label-free MS approach to identify DENV RNA associating proteins in cell culture by cross-linking the RNA to the proteins using short wavelength UV light and isolating DENV RNA bound proteins by anti-sense DNA affinity capture [74] . While their method identified several DENV host factors [12 , 75–77] , the qTUX-MS method reported here resulted in improved identification of known dengue host factors and putative DENV RNA interacting proteins . There could be several reasons for these results , such as , the qTUX-MS approach achieves greater cross-linking efficiency by using long wave UV light to form crosslinks to 4-thio-uridines compared to short-wavelength UV light , which is inherently inefficient [78] . Moreover , since thio-uridine is a zero distance cross-linker for RNA-bound proteins at long UV wavelengths and protein-protein cross-links are not formed at long UV wavelengths , qTUX-MS may also have achieved improved specificity , as only proteins in direct contact with the viral RNA would be captured [23] . Additionally , qTUX-MS used an MS-based SILAC approach to determine which host proteins were specifically enriched in the vRNA isolations versus mock . Though isotope-labelling is not applicable in all model systems , it does afford greater quantitative accuracy compared to label-free MS strategies [16] . Overall , the qTUX-MS method identified 93 cellular proteins that bind to DENV RNA , which include 14 previously known or putative interactions . Importantly , five out of the six qTUX-MS identified novel factors that were tested were shown to be bona fide host factors . We used robust assays to show that the identified host factors were specifically required for DENV amplification and did not merely result in a decrease in cell fitness for viral amplification . Future studies will reveal whether the identified factors may also be required for other flavivirus infections that cause life-threatening illnesses , such as yellow fever , West Nile , Zika , Japanese and tick-borne encephalitis . Therefore , our data demonstrates that qTUX-MS is an effective technique for identifying novel virus host factors that can be used for a broad spectrum of RNA viruses by simply designing antisense DNA oligonucleotides to allow for efficient sequence-specific isolation of the vRNA .
|
DENV is the most important mosquito transmitted viral disease in humans causing almost 400 million infections each year . Early detection is possible; however , there are no antivirals or vaccines available for this potentially lethal virus . Host factors that are required for viral amplification provide an attractive target for antiviral therapeutics for rapidly evolving RNA viruses . However , only a handful of DENV host factors are known . This study reports identification of 79 novel dengue RNA binding proteins using a large-scale analysis of cellular proteins that interact with the DENV RNA during a live infection in human cells . Importantly , this analysis proved to have a remarkably low false discovery rate and the confirmed host factors appear to be specific to DENV without compromising the fitness of the cell for viral amplification of other unrelated viruses . Furthermore , these host factors were shown to be required at both early and late stages of the viral life cycle , consistent with the dynamic nature of dengue viral RNA .
|
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2016
|
Identification of RNA Binding Proteins Associated with Dengue Virus RNA in Infected Cells Reveals Temporally Distinct Host Factor Requirements
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A variety of extracellular factors regulate morphogenesis during development . However , coordination between extracellular signaling and dynamic morphogenesis is largely unexplored . We address the fundamental question by studying posterior crossvein ( PCV ) development in Drosophila as a model , in which long-range BMP transport from the longitudinal veins plays a critical role during the pupal stages . Here , we show that RhoGAP Crossveinless-C ( Cv-C ) is induced at the PCV primordial cells by BMP signaling and mediates PCV morphogenesis cell-autonomously by inactivating members of the Rho-type small GTPases . Intriguingly , we find that Cv-C is also required non-cell-autonomously for BMP transport into the PCV region , while a long-range BMP transport is guided toward ectopic wing vein regions by loss of the Rho-type small GTPases . We present evidence that low level of ß-integrin accumulation at the basal side of PCV epithelial cells regulated by Cv-C provides an optimal extracellular environment for guiding BMP transport . These data suggest that BMP transport and PCV morphogenesis are tightly coupled . Our study reveals a feed-forward mechanism that coordinates the spatial distribution of extracellular instructive cues and morphogenesis . The coupling mechanism may be widely utilized to achieve precise morphogenesis during development and homeostasis .
A key question in developmental biology is to address how tissue morphogenesis is regulated by a variety of extracellular signals . This includes identification of such extracellular signaling molecules and intracellular mechanisms that trigger morphogenesis . Since arrival of extracellular factors coincides with dynamic morphogenesis , there must be mechanisms to coordinate signaling and morphogenesis . The coordination can be achieved by an instructive role of morphogenesis in determining the regions where extracellular signals arrive or are activated . However , this is largely unknown , due to the complexity of morphogenesis in vivo . The bone morphogenetic proteins ( BMPs ) are extracellular factors that regulate morphogenesis as well as growth and patterning [1] , [2] . In Drosophila , Decapentaplegic ( Dpp ) , a homologue of BMP2/4 , is secreted either as a homodimer or a heterodimer with another BMP-type ligand ( Glass bottom boat ( Gbb ) or Screw ( Scw ) ) . The ligands bind to the type I receptor Thickveins ( Tkv ) and type II receptor Punt and phosphorylate the transcription factor Mad . Then phosphorylated Mad ( pMad ) , together with Medea , translocates into the nucleus for transcriptional regulation of various genes [3] . The nuclear accumulation of pMad can be visualized by immunostaining and used as a readout of the BMP signal . The Rho-type small GTPases , including Rho , Rac , and Cdc42 , play critical roles in actin cytoskeleton organization , cell-extracellular matrix ( ECM ) adhesion , cell polarity , cell cycle progression , and cell migration [4] , [5] . The activities of the Rho-type small GTPases are tightly regulated by the guanine nucleotide exchange factors ( GEFs ) and GTPase-activating proteins ( GAPs ) . The GEFs activate the GTPases by replacing GDP with GTP , while the GAPs inactivate the GTPases by enhancing their GTP-hydrolyzing activity [6] , [7] . Recent studies have shown that BMP signaling regulates epithelial morphogenesis through the Rho-type small GTPases . However , transcriptional downstream factors that link the BMP signal with the activities of the Rho-type small GTPases are largely unknown [8] , [9] . Posterior crossvein ( PCV ) development mediated by BMP signaling during the pupal stages provides an excellent system for understanding how the long-range BMP signal regulates morphogenesis ( Figure 1A , 1B ) . dpp is initially transcribed at the prospective longitudinal veins ( LVs ) ( Figure 1B ) , then later also in the PCV region about 28 hr after pupariation ( AP ) [10] . In contrast , the BMP signal is detected at all the vein primordia from about 17—18 hr AP ( Figure 1B′ ) . It has been thus proposed that Dpp diffuses from the adjacent LVs ( L4 and L5 ) toward the PCV region during 18—28 hr AP for PCV development [10]–[12] . By visualizing Dpp distribution in the pupal wing , we recently demonstrated that the Dpp-Gbb heterodimer is directionally transported from the LVs into the PCV region through two BMP-binding proteins , Short gastrulation ( Sog ) and Crossveinless ( Cv ) ( Figure 1C ) [13] . Cleavage of Sog by the protease Tolloid-related ( Tlr ) then releases the ligands to activate the receptors ( Figure 1C ) [12] . Interestingly , the direction of BMP transport or PCV position is prefigured independently of BMP signaling by lack of sog transcription at the PCV region about 20 hr AP [10] , [13] , which is thought to help generate the Sog gradient that guides BMP towards the PCV region [13] . To date , the BMP signal mediated by the BMP transport is the earliest instructive signal for PCV formation . A similar BMP transport mechanism also operates in the patterning of the early embryo [14]–[16] . In contrast with the extracellular regulation of BMP transport , little is known about how the BMP signal regulates wing vein morphogenesis recognized by apposition at the basal side of two wing epithelial layers [17] . Furthermore , directional BMP transport toward the PCV region undergoing morphogenesis raises a question of how BMP transport and wing vein morphogenesis are coordinated [13] . A candidate for mediating PCV formation is Crossveinless-C ( Cv-C ) , whose viable mutant allele displays a PCV-less phenotype [18] . Recently , cv-c was identified as RhoGAP88C required for a variety of embryo morphogenesis [19] . However , it remains unclear how Cv-C regulates PCV formation . Here , we show that cv-c is induced at the PCV region by the BMP signal and mediates PCV morphogenesis by inactivating various members of the Rho-type small GTPases . Intriguingly , we found that loss of cv-c inhibited Sog-Cv dependent BMP transport into the PCV region , while an ectopic Sog-Cv-dependent BMP signal was induced toward ectopic wing veins by loss of the Rho-type small GTPases . Taken together , our data suggest that Cv-C mediates a feed-forward loop coupling BMP transport and PCV morphogenesis . We also provide evidence that the initial PCV morphogenesis precedes BMP signaling and sog transcription , highlighting an instructive role of morphogenesis in guiding BMP transport .
To investigate how the PCV region undergoes morphogenesis , we analyzed optical cross-sections in the prospective PCV region , marked by pMad accumulation . The tissue architecture and the cell-extracellular matrix ( ECM ) adhesion were visualized by phalloidin staining of F-actin and immunostaining for ß-integrin [20] . At 18 hr AP , two wing epithelial layers were separated with the similar tissue architecture between the PCV region and intervein regions ( Figure 1E ) . Around 20—21 hr AP , the wing vein lumen was formed through apposition of the basal side of the intervein regions . The apical-basal cell length in the PCV region became shorter than that in the intervein regions ( Figure 1G ) . At 24 hr AP , the apposition continued except the PCV region ( Figure 1I ) and apical-basal polarity is maintained between the PCV region and intervein regions ( Figure S6A–S6A‴ ) . During 18—24 hr AP , F-actin and ß-integrin preferentially accumulated at the basal side of the intervein epithelial cells , but less at the basal side of the PCV region ( Figure 1E′ , 1E″ , 1G′ , 1G″ , 1I′ , 1I″ ) . F-actin also accumulated at the apical side of the wing epithelial cells , which became more evident at the apical side of the PCV region at 24 hr AP ( Figure 1I′ ) . Ubiquitous expression of ß-integrin in the pupal wing suggests that the ß-integrin distribution is regulated posttranscriptionally ( Figure S1 ) . The lack of apposition of the two wing epithelial layers and the distinct tissue architecture in the PCV region recognized by less distribution of the ß-integrin and F-actin at the basal side are hereinafter referred to as PCV morphogenesis . We note that similar ß-integrin and F-actin distributions were observed in the LV formation [20] . Since PCV morphogenesis overlapped with the pMad accumulation ( Figure 1D–1I ) , we investigated whether BMP signal is required for PCV morphogenesis . To test this , PCV morphogenesis was analyzed in cv70 , a null allele of cv , in which pMad accumulation was absent due to lack of BMP transport ( Figure 1J , 1K , 1L , 1M , 1N , 1O ) [11] , [13] . We found that , despite the smaller lumen size , the initial PCV morphogenesis occurred during 18—20 hr AP and was subsequently disrupted around 24 hr AP ( Figure 1K , 1M , 1O ) . PCV morphogenesis was also analyzed in a dppshv mutant ( dpps4/dpps11 ) [21] . In dpps4/dpps11 , BMP signal was severely affected both in the LVs and CVs during pupal stages ( 20–26 hr AP ) , and consequently , distal parts of L4 , L5 and PCV were not formed in the adult wing ( Figure S2A–S2C , data not shown ) [13] . We found that PCV morphogenesis occurred during 22–24 hr AP and was disrupted until 26 hr AP in dpps4/dpps11 ( Figure S2D–S2G ) . These observations suggest that BMP signaling is not required for the initiation but for the maintenance of PCV morphogenesis through regulation of ß-integrin and F-actin localizations . It has been shown that sog transcription also prepatterns the PCV position ( Figure 2A ) [10] , [13] . To test whether the initial PCV morphogenesis is dependent on sog transcription , the initial PCV morphogenesis was analyzed at 20 hr AP in sogP129D , where sog transcriptional prepattern information and pMad signal were severely absent at the PCV region ( Figure 2B–2D ) . We found that the initial PCV morphogenesis still occurred in sogP129D ( Figure 2E–2E″ ) . Thus , the initial PCV morphogenesis is independent of sog transcription . The initial PCV morphogenesis as well as sog transcription may be involved in guiding the BMP transport . We then asked what mediates PCV morphogenesis downstream of BMP signaling . A candidate for mediating PCV morphogenesis is RhoGAP Cv-C ( Figure 3A ) , which regulates a variety of embryo morphogenesis through regulation of the cytoskeleton [19] , [22] . Indeed , optical cross-sections showed defects in PCV morphogenesis at 24 hr AP in cv-c1 , a viable allele of cv-c ( Figure 3B , 3C ) . During 20—24 hr AP , cv-c is strongly expressed in the CVs and weakly in the LVs and intervein regions along the LVs ( Figure 3D , 3E ) . Since cv-c expression is absent from the PCV region during 20—24 hr AP in cv70 ( Figure 3F , 3G ) and ectopically induced by the constitutively active form of type I receptor Tkv ( caTkv ) at 24 hr AP ( Figure 3H ) , cv-c transcription in the PCV region is tightly regulated by BMP signaling . We then asked if Cv-C regulates PCV morphogenesis by inactivating the Rho-type small GTPases . In this case , adult PCV defects in cv-c may be rescued by reducing the activities of Rho-type small GTPases . Indeed , we found that severe adult PCV defects in cv-c1/cv-cc524 were efficiently restored by mutant alleles of Cdc42 , Rho1 , Rac1 , or Rac2 ( Figure 3I ) . Consistently , when Rho1 activity was visualized by a GFP-based sensor that binds to the active form of Rho1 in the dorsal wing layer [23] , Rho1 activity was low in the PCV region and high at the basal side of the intervein region at 24 hr AP ( Figure S3A ) . In contrast , GFP alone was uniformly distributed in the dorsal wing layer at 24 hr AP ( Figure S3B ) . The Rho1 protein also less accumulated at the basal side of the PCV region at 24 hr AP ( Figure S3D ) . The similar distribution of Rho1 activity was also observed in the dorsal wing layer at 20 hr AP in cv70 , even though cv-c was not expressed in the PCV region ( Figure 3F , Figure S3C ) . This suggests that Rho1 activity in the initial PCV morphogenesis is regulated independently of BMP signaling and Cv-C . We then asked if inactivation of the Rho-type small GTPases is critical for PCV morphogenesis downstream of BMP signaling . In this case , defects in PCV morphogenesis due to lack of BMP signaling may be rescued by reducing activities of Rho-type small GTPases . Indeed , by using the viable cdc42 allele cdc422 [24] , we found that defects in PCV morphogenesis in cv70 ( Figure 1N , 1O ) were efficiently rescued at 24 hr AP in cv70 , cdc422 double mutant independently of pMad signal ( Figure 3J–3L ) . Taken together , these data suggest that Cv-C is induced in the PCV region by BMP signaling and regulates ß-integrin and F-actin distribution by inactivating various Rho-type small GTPases ( Figure 3M ) . Unexpectedly , we found that loss of cv-c affects BMP signaling in the PCV region . In cv-c1 , pMad signal in the PCV region was almost absent during 20–24 hr AP ( Figure 4A–4D ) . To investigate how Cv-C is involved in BMP signaling , mutant clones of cv-cc524 , a null allele of cv-c , were generated using the MARCM system [25] . Since BMP ligands are produced in the LVs of both wing layers and diffuse into the PCV region to activate BMP signal in both layers ( Figure 1 ) [13] , we analyzed the effects of cv-c mutant clones on BMP signal in both layers . We found that pMad accumulation appeared normal within small mutant clones ( Figure 4E , 4F ) , suggesting that cv-c mutant cells can activate BMP signal . In such cv-c mutant clones , the apical-basal cell length became longer with F-actin accumulation at the basal side ( Figure S4 ) . In contrast , when mutant clones covered about half of the PCV region in one wing layer , pMad accumulation was normal in a few mutant cells adjacent to wild-type cells but attenuated in the middle of the clones ( Figure 4G ) . When mutant clones straddled almost all the PCV region in one wing layer , pMad signal was severely affected within clones ( Figure 4I ) . Interestingly , in these cases , pMad signal was also attenuated in the PCV region in the other wing layer ( Figure 4H , 4J ) . When mutant clones in both layers were overlapped at the PCV region , pMad signal was more effectively inhibited within overlapping double-sided clones ( Figure 4K–4N ) than single-sided mutant clones ( dashed arrows Figure 4G , 4L ) , and was sometimes lost even in the wild-type cells adjacent to mutant clones ( arrows in Figure 4K , 4K″ , 4M , 4M″ ) . These results indicate that Cv-C is non-cell autonomously required for BMP signaling in the PCV region . The non-autonomous effects of cv-c mutant clones on BMP signal across the wing layer ( Figure 4H , 4J , 4K , 4M ) indicate that BMP ligands transported into one wing layer activate BMP signal in both wing layers . BMP ligands derived from the wild-type wing layer probably cross the lumen to activate BMP signal within cv-c mutant cells or wild-type cells between single-sided clones ( Figure 4G , 4L ) . The non-cell-autonomous function of Cv-C on BMP signaling can be mediated through BMP transporters or BMP-binding protein Crossveinless-2 ( Cv-2 ) , which facilitates ligand-receptor binding in a short-range manner [13] , [26] . We found partial PCV defects in wings transheterozygous for cv-c and sog , or for cv-c and cv , but not for cv-c and cv-2 ( Figure 5A–5D ) . The genetic interaction between Cv-C and BMP transporters suggests that Cv-C is involved in BMP transport toward the PCV region . To test this , we visualized Dpp distribution in the PCV region by expressing functional GFP-dpp in the LVs [13] , [27] . In the wild-type background , GFP-Dpp dots accumulated at the PCV region at 24 hr AP , where pMad signal is positive ( 62 . 5±10 . 1 dots , n = 13 wings ) ( Figure 5E , 5H ) . In contrast , GFP-Dpp dots and pMad accumulation were significantly reduced at the PCV region at 24 hr AP ( 3 . 6±1 . 2 dots , n = 14 wings ) , and consequently the adult PCV defect was not rescued in cv-c1 mutant background ( Figure 5F , 5H ) . When GFP was expressed in the LVs , GFP dots did not accumulate at the PCV region ( 0 . 1±0 . 1 dots , n = 8 wings ) ( Figure 5G , 5H ) . Taken together , these data indicate that Cv-C is required for Sog-Cv-dependent BMP transport into the PCV region . How does Cv-C regulate BMP transport ? Since cv-c is required for PCV morphogenesis , we hypothesized that BMP transport is coupled with wing vein morphogenesis . To test this , we analyzed cdc422 , in which ectopic CVs were frequently observed in the adult wings ( Figure 6A , 6G ) [28] , [29] . We found that ectopic pMad signal was induced in the future ectopic CVs at 24 hr AP in cdc422 without changing dpp transcription ( Figure 6B , 6B′ ) . The ectopic pMad signal and CVs formation in cdc422 were completely cancelled in sogP129D , cdc422 or cv70 , cdc422 double mutant ( Figure 6C–6G ) . Optical cross-sections revealed that ectopic pMad signal was detected at the ectopic wing vein regions ( arrow in Figure 6B ) at 24 hr AP in cdc422 ( Figure 6H , 6I ) . We found that the ectopic wing vein morphogenesis occurred independently of pMad signal in the corresponding region ( arrow in Figure 6C ) in sogP129D , cdc422 double mutant ( Figure 6J , 6K ) . These data indicate that Sog-Cv-dependent BMP transport was guided toward ectopic wing veins by loss of cdc42 . Sog-Cv-dependent ectopic pMad accumulation and ectopic adult wing veins were also induced by loss of Rho1 ( Figure S5 ) . We note that BMP signaling independent wing vein morphogenesis at 24 hr AP by loss of cdc42 ( Figure 3L , Figure 6J and 6K ) never induced adult wing veins ( Figure 6D , 6F , 6G ) , suggesting that additional factors are required to form adult wing veins downstream of BMP signal after 24 hr AP . We then addressed whether PCV morphogenesis plays an instructive role in BMP transport . In this case , despite loss of pMad signal in cv70 , cdc422 , or sogP129D , cdc422 double mutant due to lack of BMP transport ( Figure 6C , 6E ) , defects in pMad signal in weak alleles of BMP transporters may be rescued by reducing the activities of the Rho-type small GTPases . Indeed , we found that defects of pMad and adult PCV in sogp11885 , a weak hypomorphic allele of sog , were efficiently restored in sogp11885 , cdc422 double mutant ( Figure 6L–6N ) . These results suggest that Sog-Cv-mediated BMP transport is tightly coupled with wing vein morphogenesis by loss of the Rho-type small GTPases . What is the molecular mechanism that couples BMP transport and wing vein morphogenesis ? We found that ectopic pMad accumulation by loss of cdc42 or Rho1 was associated with low ß-integrin at the basal side of wing epithelial cells ( Figure 6H–6K , Figure S5 ) . Integrins have been previously proposed to regulate Sog protein distribution from the intervein regions into the LVs during the pupal stages [30] . This raises the possibility that integrins may link Sog-Cv-dependent BMP transport and PCV morphogenesis . Indeed , we found that ectopic adult wing veins including ectopic or thickened CVs were induced in the ß-integrin myospheroid ( mys ) mutants , mys1/mysnj42or mysnj42 ( Figure 7A , 7B , 7H ) [30] , [31] , in a sog- or cv-dependent manner ( Figure 7A–7C , 7G–7K ) . Although anterior crossvein ( ACV ) development requires BMP transport [11] , wing vein fragments were often observed at the ACV region in mysnj42 , sogP129D or cv70 , mysnj42 double mutant ( Figure 7I , 7J ) , which may reflect dpp expression in a part of ACV region during pupal stages [10] . Ectopic pMad accumulation at the PCV region was also observed in mys1/mysnj42 in a sog-dependent manner ( Figure 7D–7F ) . In fact , quantification of GFP-Dpp distributions along apical-basal axis in wings expressing GFP-Dpp in the LVs showed accumulation of GFP-Dpp dots at 21±2% ( n = 125 dots , 3 wings ) from the basal surface in the PCV region ( Figure S6E ) , where ß-integrin is less distributed ( Figure 1 ) . Furthermore , we found that pMad and adult PCV defects in cv-c1/cv-cc524 were efficiently rescued in mysnj42 , cv-c1/cv-cc524 double mutants ( Figure 7L–7N ) . This indicates that low ß-integrin activity promotes BMP transport at the basal side of the PCV region downstream of Cv-C . Taken together , these data suggest that BMP transport is coupled with PCV morphogenesis through ß-integrin .
Despite the critical roles of BMP signaling in various morphogenetic processes , little is known about its transcriptional downstream factors that mediate morphogenesis . Using Drosophila PCV morphogenesis as a model , we found that RhoGAP Cv-C is induced by BMP signaling and mediates PCV morphogenesis through inactivation of various Rho-type small GTPases . Furthermore , we found that Cv-C is required non-cell-autonomously for BMP transport into the PCV region , while BMP signaling is induced at the ectopic wing veins by loss of the Rho-type small GTPases . These results suggest that Cv-C mediates a feed-forward loop coupling BMP transport and PCV morphogenesis . How does the activity of Rho-type small GTPases control morphogenesis in the pupal wing ? Recent studies have revealed that cellular compartmentalization of the Rho-type small GTPases is critical to regulate epithelial morphogenesis [9] , [23] , [32] . We found a similar biased distribution of Rho1 activity in the pupal wing . Rho1 activity is high at the basal side of the intervein regions and low in the PCV region ( Figure S3 ) . Since overexpression of constitutively active form of Rho1 as well as Rho1 RNAi shortens apical-basal cell lengths in the intervein region [33] , localized Rho1 activity rather than total activity is associated with the apical-basal cell length . Localized activities of Rho-type small GTPases then regulate ß-integrin and F-actin accumulation at the basal side ( Figure 6H–6K ) and maintain apical-basal cell length in the intervein region probably by mediating cell-ECM adhesion as in the larval wing epithelium [34] . In the PCV region , we showed that Cv-C is induced by BMP signal and inactivates various Rho-type small GTPases to induce shorter apical-basal lengths ( Figure 3 ) . Interestingly , BMP signaling has been previously linked with the localized Rho1 activity that triggers apical-basal cell elongation in the larval wing imaginal disc [9] . Thus , BMP signaling may positively or negatively regulate the compartmentalization of Rho-type small GTPases in a tissue-dependent manner . Our study revealed that RhoGAP Cv-C also regulates BMP transport through PCV morphogenesis ( Figure 6 , Figure 7 ) . How then is BMP transport coupled with wing vein morphogenesis ? Our data showed that GFP-Dpp is basally accumulated at the PCV region ( Figure S6 ) [13] . Furthermore , a recent study showed that vittelogenin-like protein Crossveinless-d ( Cv-d ) is secreted from hemocytes to regulate BMP signaling in the PCV region [35] . These observations suggest that BMP is transported into the PCV region through the lumen ( Figure 8 ) [13] . The lumen may provide physical space for BMP transport . However , pMad accumulates in the PCV region even before the lumen is formed ( Figure 1 ) . We found that BMP transport is rather associated with ß-integrin distribution ( Figure 1 , Figure 6 , Figure 7 ) . Since Sog-Cv dependent BMP signal is induced in the ß-integrin-free regions adjacent to the LVs ( Figure S5 ) , low level of ß-integrin activity guides BMP transport from the LVs probably by affecting Sog distribution [30] . Since integrins physically interact with Sog [30] , we presume that the Sog protein gradient is formed along the ECM to direct Sog-Cv-BMP complex towards the PCV region ( Figure 8 ) . BMPs are then released from Sog-Cv by Tlr and activate the signal in the PCV region on the both wing layers . In this model , BMP transport is effectively blocked when cv-c mutant clones are overlapped in both layers ( Figure 4K–4N ) . In contrast , when cv-c mutant clones are generated in one wing layer , BMP transport is attenuated in cv-c mutant cells , but BMP ligands can be supplied from the other wing layer to activate BMP signal in cv-c mutant cells ( dashed arrows Figure 4G , 4L ) . However , since total amounts of BMP ligands are reduced in the PCV region , BMP signaling range is affected in both wing layers ( Figure 4H , 4J ) . How is Sog gradient established along the ECM ? ECM components may help Sog distribution . Collagen IV has been recently shown to regulate BMP signal in a variety of developmental processes [36] , [37] . In contrast with Collagen IV accumulation at the basal side of the larval wing imaginal disc ( Figure S6D ) [38] , Collagen IV accumulated as few punctate spots at the basal side and in the hemocytes in the pupal wing ( Figure S6A–S6C ) . Since punctate Collagen IV signal is randomly distributed at the basal side , Collagen IV may not be actively involved in BMP signal at the PCV region but probably degraded by hemocytes for remodeling the pupal wing [39] . Another ECM component Laminin has been shown to genetically interact with Sog [30] . Thus Laminin may be involved in regulating Sog distribution . Recent studies also identified novel extracellular factors that regulate BMP signal via heparan sulfate proteoglycans ( HSPGs ) [40] , [41] . Among them , Pentagon ( Pent ) regulates BMP morphogen gradient via the glypican Dally in the larval wing imaginal discs [40] . Although loss of pent did not induce evident PCV defects , Dally and Dally-like are required for BMP signal at the PCV region non-cell autonomously [35] . Pentagon may be involved in PCV formation together with HSPGs . Our results also provide insights into the positional information for the PCV formation . Since sog mutant could not induce evident ectopic CVs [11] , [13] and PCV formation could be rescued in some cases despite ubiquitous sog expression [26] , it has been argued that sog repression in the PCV region may not be sufficient to provide the positional information for the PCV development [10] , [13] . We showed that the initial PCV morphogenesis provides prepattern information independently of sog transcription ( Figure 2 ) . Thus the initial sog transcription and ß-integrin localization may cooperate to establish Sog gradient to instruct BMP transport toward the PCV region . BMP transport is then maintained by a positive feedback mechanism through Cv-C ( Figure 8 ) . Although the factors that regulate the initial PCV morphogenesis remain to be elucidated , they may regulate Rho1 activity in the initial PCV region ( Figure S3C , Figure 8 ) . Instructive role of morphogenesis for the cell specification was also recently reported in pancreatic tubulogenesis , where Cdc42 mediated tubulogenesis controls cell specification [42] . Our data further suggest the coupling of extracellular cues and dynamic morphogenesis via instructive role of morphogenesis . The coupling mechanism provides two general implications . First , the coupling mechanism ensures spatial distribution of secreted factors at the tissues undergoing dynamic morphogenesis without restricting the competence to respond to signaling . Indeed , the intervein regions can respond to BMP signaling [13] . Second , a positive feedback mechanism allows for continuous signaling to the target tissues . This would be especially important when continuous signaling is required for further differentiation . In fact , adult wing vein morphogenesis requires continuous BMP signaling ( Figure 1O , Figure 6D and 6F ) . In conclusion , we identified a Cv-C-mediated feed-forward mechanism that couples BMP transport and PCV morphogenesis . Given that BMP signaling and a human homolog of Cv-C , Deleted in liver cancer ( DLC1 ) , act as tumour suppressors in a variety of contexts [43] , [44] , a similar coupling mechanism may be operated in tissue homeostasis as well as tissue morphogenesis . As illustrated in our study , investigating simple in vivo models would provide further insights into the coordination between extracellular cues and dynamic morphogenesis .
The cv70 , sogP129D , cv2KO1 , shv3Kpn-Gal4 , and UAS-GFP-Dpp flies were described previously [13] . The cv-c1and cv-cc524 flies were obtained from H . Skaer [19] . The UAS-PNKG58AeGFP flies were kindly provided by J . C . Hombria [23] . The mysnj42 flies were obtained from F . Schoeck . The dppshv-lacZ , dpps11 , dpps4 , cdc422 , Rho172O , Rac2Δ , Rac1J11 , UAS-GFP , sogP11885 , UAS-Rho1RNAi , BS1348-Gal4 , and mys1 flies were obtained from Bloomington Drosophila Stock Center . Vkg-GFP flies were obtained from Fly Trap stock collection . cv-c MARCM clones were generated using y w hs-FLP; tubP-GAL4 UAS-mCD8::GFP; FRT82B cv-cc524/FRT82B tubP-GAL80 . Drosophila pupal wings were fixed at 4°C overnight and then dissected from the pupae . All immunohistochemistry and in situ hybridizations were performed , as previously described [11] . The primary antibodies were as follows: rabbit anti-pMad at 1∶1000 ( a gift from P . ten Dijke ) , mouse anti-LacZ at 1∶1000 ( Promega ) , mouse anti-ß-integrin ( CF . 6G11 ) at 1∶100 ( Developmental Studies Hybridoma Bank ( DSHB ) ) , rabbit anti-aPKC ( C-20 ) at 1∶200 ( Santa Cruz Biotechnology , Inc . ) , and mouse anti-Dlg ( 4F3 ) at 1∶100 ( DSHB ) . The secondary antibodies were as follows: anti-rabbit IgG-Alexa 568 or 647 and anti-mouse IgG-Alexa 488 were used at 1∶1000 , respectively ( Invitrogen ) . Can Get Signal Solution B ( TOYOBO ) was used for staining with anti-pMad and anti-ß-integrin . The fluorescent images were obtained with a Leica TCS SP5 confocal microscope . To analyze the number of GFP-Dpp dots , approximately 10 confocal sections were taken at app . 1-µm intervals to cover a single cell layer and the images were processed by maximum intensity profile and quantified using analyze particle command in ImageJ software ( National Institutes of Health , Bethesda , MD , USA ) . To analyze GFP-Dpp distribution along apical-basal axis , relative position of GFP-Dpp dots from basal surface of the PCV region ( the basal surface is set to 0% and the apical surface is set to 100% ) was measured individually in a single confocal image using Image J . The heatmap of the intensity of pMad signal was produced using the “HeatMap Histogram” plugin of ImageJ .
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It has been extensively studied how tissue morphogenesis is regulated by a variety of extracellular cues . Given that dynamic morphogenesis coincides with arrival of extracellular factors , there must be also mechanisms that coordinate extracellular signaling and intracellular morphogenesis . However , the coordination is largely unknown , due to the complexity of morphogenesis in vivo . We addressed the fundamental question by studying posterior crossvein ( PCV ) development in Drosophila as a model , in which a long-range transport of bone morphogenetic protein ( BMP ) type ligands from adjacent longitudinal veins plays a critical role during the pupal stages . Here , we first showed that RhoGAP Crossveinless-C ( Cv-C ) is induced at the PCV region by BMP signal and mediates PCV morphogenesis . By modulating wing vein morphogenesis , we then found that PCV morphogenesis is required for BMP transport , while ectopic wing vein morphogenesis sufficiently guides a long-range BMP transport . These data suggest a feed-forward mechanism that coordinates the spatial distribution of extracellular instructive cues and morphogenesis . The coupling mechanism may be widely utilized to achieve precise tissue morphogenesis and tissue homeostasis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"cell",
"differentiation",
"animal",
"models",
"developmental",
"biology",
"drosophila",
"melanogaster",
"model",
"organisms",
"organism",
"development",
"molecular",
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"morphogenesis",
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"signaling",
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] |
2013
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A Feed-Forward Loop Coupling Extracellular BMP Transport and Morphogenesis in Drosophila Wing
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Antibodies constitute a critical component of the naturally acquired immunity that develops following frequent exposure to malaria . However , specific antibody titres have been reported to decline rapidly in the absence of reinfection , supporting the widely perceived notion that malaria infections fail to induce durable immunological memory responses . Currently , direct evidence for the presence or absence of immune memory to malaria is limited . In this study , we analysed the longevity of both antibody and B cell memory responses to malaria antigens among individuals who were living in an area of extremely low malaria transmission in northern Thailand , and who were known either to be malaria naïve or to have had a documented clinical attack of P . falciparum and/or P . vivax in the past 6 years . We found that exposure to malaria results in the generation of relatively avid antigen-specific antibodies and the establishment of populations of antigen-specific memory B cells in a significant proportion of malaria-exposed individuals . Both antibody and memory B cell responses to malaria antigens were stably maintained over time in the absence of reinfection . In a number of cases where antigen-specific antibodies were not detected in plasma , stable frequencies of antigen-specific memory B cells were nonetheless observed , suggesting that circulating memory B cells may be maintained independently of long-lived plasma cells . We conclude that infrequent malaria infections are capable of inducing long-lived antibody and memory B cell responses .
Malaria , a parasitic disease of humans caused predominantly by two species of Plasmodium , P . falciparum and P . vivax , remains an important cause of mortality and morbidity in many parts of the world . Development of a vaccine against malaria has proven challenging due to the complex nature of the parasite and to the difficulty in correlating naturally-acquired immune responses with clinical immunity . While immunity against some of the severe clinical symptoms may be achieved quite rapidly , following perhaps as few as one or two infections [1] , immune effector mechanisms capable of controlling parasite growth develop only after repeated infections over a number of years . Even with repeated infections , protective immunity to malaria is not complete , and asymptomatic infections may exist throughout life . Understanding the causes of this continuing susceptibility to infection and , in particular , understanding the development and maintenance of immunological memory , is essential for rational development of malaria vaccines . Antibodies are a crucial component of naturally acquired protective immunity against blood stage malaria with roles that may include inhibition of merozoite invasion into new red blood cells ( RBCs ) , blocking cytoadherence of infected RBCs ( iRBCs ) to endothelial cells , and enhancing phagocytic activity of monocytes and macrophages ( reviewed in [2] , [3] ) . It is widely believed that periodic reinfection is required to maintain acquired immunity to malaria and that antimalarial antibodies are short-lived in the absence of reinfection ( reviewed in [4] ) ; implying that B cell memory to malaria may be defective or suboptimal . However , the development and persistence of B cell memory following malaria infection has long been a matter of debate ( reviewed in [5] ) . Some studies in animal models have shown that memory B cells do develop and are maintained normally after malaria infection [6] , [7]; whereas others have found that malaria infection interferes with the development of memory B cells and long-lived plasma cells [8] , [9] . In humans , several studies have demonstrated stable antibody responses to malaria antigens [10] , [11] , [12] , however , short-lived antibody responses have also been observed [13] , [14] , especially in young children [10] , [15] . To date , very few studies have examined the induction and maintenance of malaria-specific memory B cells in humans . Dorfman et al [14] were frequently unable to detect circulating malaria-specific B cells in antibody seropositive children , but it is unclear whether this reflects an absence of such cells or a lack of sensitivity in the assays used to detect them . Conversely , Asito et al [16] observed an increase in both the total CD38+IgD− memory B cell population and the transitional CD10+CD19+ B cell population , following an episode of acute malaria in African children but this study lacked any analysis of the specificity of B cell responses as well as any long term follow up to ascertain the duration of the response . The aim of this study was to investigate the longevity of the human B cell memory response to malaria in individuals with one or more known malaria infections . To do this , we identified individuals living in an area of very low malaria endemicity in Northern Thailand who were either malaria naïve or who had had recorded ( and parasitologically confirmed ) clinical episodes of P . falciparum or P vivax infection some years previously and characterised the antibody and memory B cell response to a variety of discrete P . falciparum and P . vivax antigens under conditions of infrequent re-exposure/boosting of the immune response .
Malaria-specific humoral immune responses of 93 , HIV negative Thai adults were studied ( Table 1 ) . Individuals were assigned to one of three groups according to their place of residence and their prior malaria history . Subjects from Chiang Mai were designated “City Naïve” ( n = 17 ) . Subjects from Muang Na ( Chiang Dao ) were designated “Rural with no clinical malaria episode ( Rural 1; n = 30 ) ” if they reported no prior episodes of malaria infection and/or if no record of malaria infection was found in the past 6 years . Muang Na residents who had had one or more fully documented episodes of infection with P . falciparum , P . vivax or both parasite species , as well as those who recalled a previous infection and were seropositive to P . falciparum schizont extract ( PfSE ) but for whom hospital records could not be found , were designated as “previously malaria infected” ( Rural 2; n = 46 ) . In this group , 21 subjects ( 45 . 7% ) reported at least one episode of infection with P . falciparum , 14 ( 30 . 4% ) reported at least one episode of infection with P . vivax and 6 ( 13 . 0% ) reported infection with both species in the past 6 years . The frequency of malaria infections within the six years prior to recruitment varied from 1–3 episodes ( mean 1 . 25±0 . 56 episodes for P . falciparum and 1 . 10±0 . 26 for P . vivax ) . Five Rural 2 subjects ( 10 . 9% ) were strongly seropositive to PfSE and recalled prior malaria episodes , but no documentary evidence of these malaria episodes was found . The time since last documented malaria infections prior to recruitment varied from 4–58 ( 21 . 2±12 . 9 ) months for those known to have been infected with P . falciparum and 7–39 ( 20 . 6±10 . 1 ) months for those known to have been infected with P . vivax . Of the 76 rural subjects included at enrolment , 49 ( 64 . 5% ) were seen again at 3 months , 44 ( 57 . 9% ) at 6 months and 51 ( 67 . 1% ) at 12 months . All city individuals were re-sampled 3 months later . None of the subjects were infected with P . falciparum or P . vivax - as determined by blood film examination and PCR - at any visit . However , one of 76 rural subjects demonstrated a significant increase in antibody titre during the study ( but only to one antigen , PfSE ) suggesting that this individual may have experienced a recent malaria infection , even though they did not report being ill . The three groups did not differ significantly by age or sex . Antibody levels against tetanus toxoid ( TT ) were measured by indirect ELISA . There was no significant difference among the groups in the overall levels of antibodies to TT ( Fig . 1A ) but only 23 . 7% of the rural subjects ( Rural 1 + Rural 2 , n = 76 ) were seropositive for TT at the time of recruitment . Among the rural individuals ( Rural 1 + Rural 2 ) who had blood collected at recruitment and 12 months later ( n = 51 ) , the seropositivity rate for TT ( 19 . 6% ) did not differ between the two time points ( Fig . 1G ) . The individual data for the rural subjects who were seropositive for TT at the time of recruitment and had blood collected more than one time point ( n = 17 ) are shown in Figure 1M . Relative antibody titres to PfSE were measured , at the time of enrolment and at subsequent follow-up . Among the Rural 1 population , 4 ( 13 . 3% ) individuals had antibody responses above the cut-off , indicating that they had , in fact , been exposed to malaria ( Fig . 1B ) . Among Rural 2 subjects , 25 ( 54 . 4% ) individuals were seropositive for PfSE . The proportion of seropositives in the Rural 2 group was significantly higher than in the Rural 1 group ( p = 0 . 0003; Fisher's exact test ) . There was no difference in the levels of anti-PfSE antibodies between subjects who had been infected with P . falciparum only or infected with P . vivax only ( Fig . S1 ) . Overall , the Rural 2 group had levels of anti-PfSE antibodies that were significantly higher than the Rural 1 group ( p = 0 . 0005; Mann Whitney U test ) . There was no correlation between the levels of anti-PfSE antibodies and age of the subjects or the number of previous malaria episodes they had experienced ( data not shown ) . Among the rural subjects ( Rural 1 + Rural 2 ) who had blood collected at the beginning and at the end of the study ( n = 51 ) , 19 ( 37 . 3% ) were seropositive for PfSE at the time of recruitment and all of these remained positive 12 months later ( Fig . 1H ) . The individual data for the rural subjects who were seropositive at the time of recruitment and had blood collected at more than one time point ( n = 25 ) are shown in Figure 1N . Antibody responses to recombinant malaria antigens PfAMA-1 , PfMSP-119 , PfMSP-2 and PfCSP were examined by indirect ELISA . PfAMA-1 , PfMSP-119 and PfMSP-2 are antigens of blood stage merozoites . PfCSP is the major surface protein on the surface of sporozoites , the infective stage of the malaria parasite . All of these antigens are key P . falciparum vaccine candidates . City naive subjects were seronegative to all P . falciparum antigens tested ( Fig . 1C–1F ) . Among the thirty rural individuals with no known episodes of malaria infection in the past 6 years ( Rural 1 ) , 7 ( 23% ) , 4 ( 13% ) , 1 ( 3% ) and 3 ( 10% ) subjects had positive antibody titres against PfAMA-1 , PfMSP-119 , PfMSP-2 and PfCSP , respectively ( Fig . 1C–1F ) . Seropositivity to individual malaria antigens , and to PfSE , was not significantly correlated ( data not shown ) and , overall , 10 ( 33% ) Rural 1 subjects were seropositive to one or more P . falciparum antigens . The frequencies of antibody responses to PfAMA-1 , PfMSP-119 , PfMSP-2 and PfCSP in the previously infected ( Rural 2 ) group were 17 ( 37% ) , 22 ( 48% ) , 7 ( 15% ) and 4 ( 9% ) , respectively . Again , seropositivity to individual malaria antigens was not significantly correlated ( data not shown ) and , overall , 30 ( 65% ) Rural 2 subjects were seropositive to one or more P . falciparum antigens ( schizont extract and/or recombinant proteins ) . The proportion of individuals in the Rural 2 and Rural 1 groups who were seropositive for recombinant malaria antigens was not significantly different , except that a higher proportion of Rural 2 were seropositive for PfMSP-119 ( p = 0 . 003; Fisher's exact test ) . The titres of antibodies to PfMSP-119 and PfMSP-2 were significantly higher among Rural 2 subjects than among Rural 1 subjects but among the Rural 2 group the levels of antibodies to individual P . falciparum antigens were not different between previously P . falciparum- and P . vivax- infected subjects ( data not shown ) . Moreover , the titres of antibodies against P . falciparum antigens in some Rural 2 subjects were at least as high as those of the positive control of pooled adult African sera . There was no detectable antibody response to the carrier proteins used in the production of recombinant antigens ( data not shown ) . Several subjects reporting prior infection only with P . vivax had antibodies to P . falciparum antigens . Of the 14 individuals with recorded P . vivax infections but no recorded P . falciparum infections , 8 ( 57% ) had antibodies to at least one P . falciparum antigen . This is consistent with results of previous studies [17] , [18] , [19] and may reflect an undiagnosed prior infection with P . falciparum or cross-reactivity of antibodies to the two parasite species [17] , [20] , [21] , [22] . As shown in Fig . 1I–1L , most of the subjects who were seropositive at recruitment and who were tested again 12 months later remained seropositive . The individual data for the rural subjects who were seropositive for the different malaria antigens at the time of recruitment and had blood collected at more than one time point are shown in Fig . 1O–1R . At an individual level , titres of antibodies against PfAMA-1 , PfMSP-119 and PfMSP-2 were significantly correlated with titres of anti-PfSE Abs ( data not shown ) . No correlations between age and the antibody titres against individual malaria antigens were found ( data not shown ) . We also investigated the antibody responses to P . vivax antigens , PvAMA-1 , PvMSP119 and PvDBP by ELISA , all of which are P . vivax blood stage antigens and are key vaccine candidates . City naïve subjects were seronegative to all P . vivax antigens ( Fig . 2A–2C ) . Among Rural 1 subjects , none were seropositive to PvAMA-1 ( Fig . 2A ) , one ( 3% ) had a borderline positive titre to PvMSP-119 ( Fig . 2B ) and two ( 6 . 7% ) were seropositive to PvDBP ( Fig . 2C ) . Of the Rural 2 subjects , 5 ( 11% ) , 5 ( 11% ) and 3 ( 6 . 5% ) were seropositive to PvAMA-1 , PvMSP-119 and PvDBP , respectively . Overall , 8 ( 17 . 4% ) Rural 2 subjects were seropositive to one or more P . vivax recombinant antigens . Of the 20 subjects known to have been previously infected with P . vivax ( P . vivax only or both P . vivax and P . falciparum ) , 5 ( 25% ) were seropositive to one or more P . vivax antigens and 15 ( 75% ) were seronegative . The proportion of subjects who were seropositive to P . vivax antigens did not differ significantly between the Rural 1 and Rural 2 groups . Similarly , no significant differences in anti-P . vivax antibody titres were observed between the Rural 1 and Rural 2 groups , although the power of this analysis was poor due to the very low numbers of seropositive subjects . Antibody responses to P . vivax antigens were not different between subjects known to have been infected with P . falciparum- and those known to have been infected with P . vivax ( data not shown ) . Most of the subjects who were seropositive to P . vivax antigens at the time of recruitment and who had samples collected at more than one time point remained seropositive over the course of the study and there was no evidence of declining titres ( Fig . 2D–2F ) . Antibody avidity tends to increase over time as a result of somatic mutation in the immunoglobulin-encoding genes of germinal centre B cells and in response to increasing competition between B cell clones for diminishing amounts of antigen [23] , [24] . To determine whether the avidity of the anti-malarial antibody response changed over time , or whether antibody avidity was associated with durability of antibody responses , the avidity indices of anti-PfAMA-1 and anti-PfMSP-119 antibodies were determined for all those individuals ( as defined in Figure 1 ) who were seropositive to one or other antigen at the time of recruitment . Overall , avidity indices for antibodies to both antigens were higher in Rural 2 group than in Rural 1 group ( Fig . 3A and 3B ) , and this difference was statistically significant for antibodies to PfMSP-119 . However , there was no detectable change in the avidity of antibodies to either antigen in either group over the 12 months of the study ( Fig . 3C–3F ) . To determine the longevity of the antimalarial antibody responses , we analysed the change in concentrations of antibodies to PfSE , PfAMA-1 and PfMSP-119 in relation to time ( in months ) since the last documented malaria episode ( Figure 4 ) . The half-life of the antibody response was analysed separately for each antigen using data from Rural 2 subjects who were seropositive at the time of enrolment and for whom follow-up samples were obtained ( PfSE n = 14; PfAMA1 n = 8; and PfMSP-119 n = 12 ) in a repeated measurements analysis including multiple data points from the same subjects . Subjects known to be infected with P . vivax but not known to have been infected with P . falciparum were not included in this analysis in order to ensure specificity to P . falciparum . Mixed-effects regression models revealed very low rates of decline ( converted to years ) in anti- PfSE , PfAMA-1 and PfMSP-119 antibody concentrations over time and statistically , these rates could not be distinguished from zero ( Table 2 ) . The best estimates of half-lives were: 5 . 5 years for PfSE , 10 . 4 years for PfAMA-1 and 7 . 6 years for PfMSP-119 , respectively but , in each case , the 95% CI included infinity . Pooled regression analysis of data for antibodies to PfAMA-1 and PfMSP-119 also yielded a rate of decline that was not statistically significant from zero . Inclusion of anti-PfSE antibody data in the pooled regression analysis resulted in a marginally significant rate of decline equivalent to a half-life of 6 . 4 years ( 95% CI = 3 . 22 , 650 . 48; p = 0 . 048 ) . These analyses suggest that antibody responses to malaria are stably maintained in this population . We next enumerated memory B cells to malaria antigens and to TT using a highly sensitive ELISPOT protocol [25] . The number of subjects available for analysis was limited by availability of cryopreserved PBMCs . Antigen-specific memory B cell frequencies are presented as a percentage of the total number of IgG-secreting cells . Frequencies of TT-specific memory B cells were similar among the three study groups ( Fig . 5I ) . No spots were detected for any individual when cells were tested against the irrelevant control protein ( keyhole limpet hemocyanin ) and no malaria-specific spots were observed in samples from the City naïve group ( data not shown ) . At the time of recruitment , of the 21 Rural 1 subjects whose PBMCs were available , 3 ( 14 . 2% ) , 3 ( 14 . 2% ) , and 1 ( 4 . 8% ) subjects had memory B cells specific to PfAMA-1 ( Fig . 5A ) , PfMSP-119 ( Fig . 5B ) , and PfMSP-2 ( Fig . 5C ) , respectively . No memory B cells specific to PfCSP were found in the Rural 1 group ( Fig . 5D ) . A much higher proportion of Rural 2 individuals had detectable memory B cells: of the 33 tested , 16 ( 48% ) , 11 ( 33% ) , 6 ( 18% ) and 1 ( 3% ) gave spots to PfAMA-1 , PfMSP-119 , PfMSP-2 and PfCSP , respectively . Overall , 19 ( 58% ) Rural 2 subjects had memory B cells to one or more P . falciparum recombinant antigens . None of the 14 Rural 1 subjects tested had detectable memory B cells against PvAMA-1 , and only one individual ( 7% ) had detectable memory B cells to PvMSP-119 ( Fig . 5E and 5F ) . However , among the 26 Rural 2 individuals tested , 6 ( 23% ) and 7 ( 27% ) had memory B cells specific to PvAMA-1 and PvMSP-119 , respectively . Nine Rural 2 subjects ( 35% ) had memory B cells specific to one or more P . vivax antigens . For the Rural 2 individuals , we then characterised the frequency of PfAMA-1- and PfMSP-119-specific memory B cells in relation to time since their last documented malaria infection , using mixed-effects regression analysis ( allowing for repeated measurements from individual subjects ) as described above . We found that PfAMA-1- and PfMSP-119 specific memory B cells were stably maintained over time ( Fig . 5G and 5H ) . The best estimate of the rate of change in AMA-1-specific memory B cell numbers indicated no decline during follow-up , whereas the best estimate for the half-life of MSP-119-specific memory B cells was 10 years ( Table 2 ) . Single and pooled regression analysis of data resulted in rates of decline that , statistically , could not be distinguished from zero . Similar observations were made for memory B cells to TT ( data not shown ) . These results indicate that memory B cell responses to malaria antigens are stably maintained in this very low transmission area . It was immediately evident from the TT data that circulating memory B cells could be detected in many ( ∼47% ) seronegative individuals ( Figure 6G ) . We therefore carried out a systematic analysis of the association between circulating memory B cells and plasma antibody titres at the individual level . No correlation was observed between specific antibody titres and frequencies of memory B cells ( data not shown ) . Among the 33 Rural 2 subjects for whom we had both antibody data and memory B cell responses to P . falciparum antigens at the time of recruitment , 7 ( 21% ) , 8 ( 24% ) 2 ( 6% ) and 0 ( 0% ) had both circulating antibody and memory B cells to PfAMA-1 , PfMSP-119 , PfMSP-2 and PfCSP respectively ( Fig . 6A–6D ) . Four ( 12% ) , 7 ( 21% ) , 2 ( 6% ) and 3 ( 9% ) individuals were seropositive to the respective antigens but no B cell spots were observed whereas 9 ( 27% ) , 3 ( 9% ) , 4 ( 12% ) , and 1 ( 3% ) were seronegative but had memory B cells to PfAMA-1 , PfMSP-119 , PfMSP-2 and PfCSP respectively . Of the 26 Rural 2 subjects for whom we had data on both antibody and memory B cell responses against P . vivax antigens at the time of recruitment , 1 ( 4% ) and 2 ( 8% ) individuals had both antibody and memory B cells against PvAMA-1 and PvMSP-119 respectively ( Fig . 6E and 6F ) , 3 ( 12% ) and 2 ( 8% ) gave positive results in ELISA but not in ELISPOT , and 5 ( 19% ) and 5 ( 19% ) had memory B cells but not antibodies to PvAMA-1 and PvMSP-119 , respectively . These results suggest that serum antibody levels alone or memory B cell frequencies alone may not fully represent the humoral immune response to malaria parasites . Different individuals had different patterns of antibody and memory B cell responses to the various malaria antigens . Table 3 shows the heterogeneity of such responses in all Rural 2 subjects at recruitment . In a number of cases where antigen-specific antibodies were detected , the frequencies of memory B cells were below the limit of detection ( Subjects 16 , 17 and 29 ) . Likewise , in several subjects where antigen-specific antibodies were not detected , stable frequencies of antigen-specific memory B cells were observed ( e . g . Subjects 27 , 31 and 33 ) .
Antibodies are critical in protection against blood stage malaria infection through numerous , diverse mechanisms [2] , [3] . In murine malaria infections , B cells are required not only for the production of protective Abs , but also for the development of T cell helper function [26] . However , the development and persistence of B cell memory responses following malaria infection has repeatedly been called into question [27] . It is widely perceived that antibody titres rapidly decline in the absence of re-infection or when individuals leave an endemic area . It is notable that most of the studies reporting short-lived antibody responses have been conducted at or following the time of acute infection , and these infections were terminated by effective antimalarial drug therapy and that these were often observations in children [13]–[16] , [28] . It is not clear , from these studies , whether the rapid decline of antibody concentrations observed in children is related to removal of antigen by chemotherapy , by consumption of antibodies and formation of antigen-antibody complexes during parasite clearance or due to limitations in the ability of the bone marrow compartment to support differentiation and/or survival of plasma cells [29] , [30] . However , the results of a recently published study in healthy , Gambian children in which antibody titres were found to decline more slowly both in older children and in children with persistent asymptomatic malaria infection suggests that both antigen persistence and immunologic maturity may be important in determining the longevity of the serum antibody responses [15] . One explanation for these observations might be that short-lived antibody responses are the result of induction of short-lived , but not long-lived , plasma cells following acute malaria infection . In murine models of malaria infection , primary P . chabaudi infection leads to expansion of short-lived , immature B220+ splenic plasma cells however secondary infection is accompanied by apparently normal emergence of a larger population of fully mature ( Ighi , CD138hi , CD9+ , B220− ) , terminally-differentiated B220- plasma cells in the bone marrow [31] , indicating that memory B cells are efficiently induced by primary infection and are fully able to differentiate into long-lived plasma cells on secondary exposure to antigen . Similar studies have not been reported , to date , in humans but we were able to take advantage of a very particular epidemiological situation in rural Northern Thailand to examine the natural history of the anti-malarial B cell memory response . In our study area , both P . falciparum and P . vivax are endemic but transmission is kept at extremely low levels by an assiduous malaria surveillance and control programme in which all detected infections are recorded and effectively treated [32] . We have thus been able to recruit a cohort of individuals whose malaria infection history over the previous 6 years are known in considerable detail and have been able to follow these individuals for a period of 12 months to observe both long- and short-term changes in their adaptive immune response to malaria . Furthermore , we were able to recruit a cohort of individuals from the same community with no evidence of malaria infection in the past 6 years , and a cohort of known malaria naives from the city of Chiang Mai , where malaria transmission was eliminated more than 30 years ago ( Suwonkerd W; The Ministry of Public Health; personal communication ) . The very low levels of malaria transmission reported in the Muang Na area [33] are confirmed by our finding that none of the study subjects were found to be infected with malaria parasites ( detectable by blood film or PCR ) at any point during the study , none of them showed any clinical signs of malaria infection and only one individual showed boosting of antibody responses ( and against only 1 malaria antigen ) during the study . In addition , anti-malarial antibody responses were not correlated with age , indicating that there is likely to be little or no effective acquired immunity to malaria in this population . Nevertheless , some of the rural village residents with no record or recollection of malaria infection in the past 6 years ( Rural 1 ) appeared to have experienced malaria infections at some time in their lives as shown by seropositivity to malaria antigens in ELISA and positive B cell ELISPOTs . Given the lack of evidence for acquired protective immunity in this population , and since we found no evidence of asymptomatic malaria infections , it is unlikely that these individuals had experienced undiagnosed malaria infections and thus the presence of antibodies and B cell memory responses in this group suggests that anti-malarial seropositivity can be maintained for many years in the absence of reinfection . Overall , the prevalence and magnitude of antimalarial antibody and memory B cell responses compared favourably with the anti-tetanus responses . Although the frequencies of tetanus-specific memory B cells tended to be somewhat higher than the frequencies of malaria-specific memory B cells , the prevalence of antibodies to the P . falciparum schizont extract , PfMSP-119 and PfAMA-1 was in fact higher than for tetanus . Thus , despite the fact that the anti-tetanus response is likely induced by a very potent vaccine and boosted by environmental exposure or revaccination ( which is routinely given during pregnancy ) , humoral immune responses to tetanus do not appear to be particularly more robust than those induced by infrequent natural exposure to malaria . Moreover , frequencies of malaria-specific memory B cells in Thai adults were similar to frequencies of diphtheria-specific memory B cells in UK adults ( J . Palomero-Gorrindo and J . Hafalla; unpublished data ) . Therefore , frequencies of malaria-specific memory B cells seem to be of the same order of magnitude as responses to commonly used vaccine antigens [34] , [35] . Of note , Buisman et al [35] also found rather higher frequencies of memory B cells to tetanus toxoid than to other antigens . As the time since last detected malaria infection was known for the Rural 2 group we were able to obtain estimates of the rate of decline of both serum antibodies and circulating memory B cells . Importantly , and in marked contrast to previously published data from African children [14] , there was no evidence of any significant decline in either antibody titres or memory B cell responses to PfSE , PfAMA-1 or PfMSP-119 over periods of more than 5 years since the last known malaria infection . One reason for this discrepancy may be that previous studies have characterised the decay of the antibody response in the first few days or weeks after resolution of an acute malaria infection [14] , [15] which is likely to capture the initial very rapid decay in antibody titre associated with contraction of the pool of short-lived plasma cells whereas in this study , where the most recent malaria infection occurred many months or years ago , we are capturing the long term “maintenance” phase of the antibody response [36] . Our best estimates of the half-life of this maintenance phase of antibody responses to malaria antigens ranged from ∼5 to ∼16 years , putting them in the same range as the half-lives recently estimated for nonreplicating antigens such as tetanus or diptheria toxoids [37] . However , the 95% confidence intervals for the half-lives of these responses all included infinity , suggesting that antibody responses to malaria may in fact be much more stable than those to nonreplicating antigens and may be maintained in a manner that is more similar to that of antiviral responses [37] . Similar estimates were obtained for the half lives of malaria-specific memory B cell responses – indicating that the circulating memory B cell pool is extremely stable - which is consistent with data from the P . chabaudi mouse model that malaria infection induces long-lived antibody responses as well as memory B cells [31] . However , whilst these analyses are consistent with a long half life for antimalarial antibody and memory cell responses , given the very wide confidence intervals around the our estimates , data from a larger cohort of study subjects is required to obtain definitive half lives for these responses . However , it is important to note that 11 subjects ( 24% ) who were known to have been infected with malaria had no detectable circulating memory B cells and/or antibodies and less than 50% of subjects tested had either antibodies or circulating memory B cells to PfMSP-2 , PfCSP , PvAMA-1 or PvMSP-119 . Given that everyone in the study had experienced their most recent malaria infection at least 4 months before recruitment and that the genotypes of their infecting parasites are unknown , we cannot tell whether these seronegative individuals had completely failed to make a humoral response to malaria , whether they had made antibodies to polymorphic epitopes that did not cross-react with the antigens used in our assays or whether they had developed only very short-lived responses . In a previous study , in a higher malaria transmission area , very short-lived antibody responses to malaria were particularly associated with younger individuals who ( presumably ) had had the fewest number of malaria infections [15] suggesting that the long-lived responses seen in many of our study subjects may develop only after they have experienced a number of malaria infections . Nevertheless , given the very low levels of malaria transmission in our study area , the number of infections required to develop long-live antibody responses is likely to be quite small . Since the pharmacological half-life of a human IgG molecule is around 21 days [38] , long term maintenance of IgG titres indicates either ongoing secretion of antibodies from plasma cells or memory B cell differentiation in response to inflammatory stimuli; there is still no clear consensus on whether persisting specific antigen is required for this process [39] or not [40] , [41] . During inflammation , IFN-γ induces plasmablasts to express the chemokine receptor CXCR3 , promoting their migration into inflamed tissues [42] and thereby maximising antibody production at sites of infection . Resolution of inflammation leads to loss of survival signals , and these short-lived plasma cells die in situ . However , in the absence of prolonged antigenic stimulation , plasmablasts express another chemokine receptor CXCR4 allowing them to migrate to the bone marrow [43] . It is possible , therefore , that short term fluctuations in serum antibody concentrations may occur in response to infection with memory B cells being stimulated to differentiate into short-lived plasma cells , secrete immunoglobulins and then die . However , in the circumstances of lack of frequent re-exposure to malaria infection ( such as in this study ) , a larger proportion of plasmablasts may differentiate into long-lived plasma cells which maintain the level of antibodies over time . Such a scenario does , of course , beg the question as what would happen to long-lived plasma cells and memory B cells under conditions of repeated or persistent malaria infection . Immediately after malaria immunisation in humans the frequency of antigen-specific memory B cells is positively correlated with antibody titres [44] , suggesting ( not surprisingly ) that induction of antibody secreting cells and memory B cells is linked . However , the lack of correlation that we observed between antibody titres and memory B cell responses months or years after exposure to malaria antigens confirms recent findings for anti-viral responses [37] and is consistent with accumulating experimental data from animals [45] , [46] and data from therapeutic B cell depletion in humans [47] , [48] showing that depletion of circulating memory B cells does not affect antibody titres , at least in the short-term . Collectively , these data indicate that although both long-lived plasma cells and memory B cells can be stably maintained the two populations are independently regulated and that activation of circulating memory B cells may not be required for maintenance of serum antibody titres . High affinity antibodies are expected to play an important role in the humoral immune response . The avidity indices of antibodies against PfAMA-1 and PfMSP-119 did not change during the 12 months of study; this is not surprising since there was no evidence of reinfection of any of the subjects during the follow-up period which might have driven further avidity maturation . However the avidity of anti-PfMSP-119 antibodies was significantly higher among Rural 2 subjects than among Rural 1 individuals , supporting the notion that the Rural 2 population had had more frequent exposure to malaria parasites than the Rural 1 group . In summary , we conclude that B cell memory responses to malaria are effectively induced and maintained – in a significant proportion of individuals - in areas of low malaria transmission . ( This is , of course , an entirely separate issue from whether these particular antibodies confer protective immunity to malaria; whilst there is strong evidence to suggest that malaria-immune individuals have very effective antimalarial antibody responses [49] the antigenic targets of protective antibodies are still very poorly defined . Whilst it is possible that the subjects in this study with long-lived humoral responses to malaria antigens might be protected from reinfection , this issue was not directly addressed in this study ) . Although it remains possible that persistent and repeated malaria infections in areas of very high endemicity may eventually lead to B cell anergy or clonal exhaustion [50] , the fact that individuals in these areas develop high titres of antimalarial antibodies and become resistant to high density malaria infections and clinical symptoms argues against this as a major impediment to the development of effective immune responses . Finally , our results are highly encouraging for vaccine developers since they imply that – once induced – anti-malarial immune responses are likely to be long-lived even in the absence of frequent boosting .
Study subjects were either long-term adult residents of Muang Na , a village in a low malaria transmission area in the Chiang Dao region of northern Thailand , near the border with Myanmar , or were permanent adult residents of the city of Chiang Mai where malaria transmission does not occur . Ethical approval for the study was obtained from the Research Institute for Health Sciences , Chiang Mai University , from the Ministry of Public Health , Thailand and from the London School of Hygiene and Tropical Medicine , UK . Written informed consent was obtained prior to enrolment in the study . Subjects were interviewed to ascertain their previous malaria exposure . Residents of Chiang Mai were selected on the basis that they had not travelled to , or lived in , malaria endemic areas . In Muang Na , dates and species ( P . falciparum , P . vivax or both ) of malaria infections were confirmed from the records of the Office of Vector Borne Disease Control in the Department of Communicable Diseases Control at the Ministry of Public Health , which maintains detailed records of all malaria cases detected by active or passive case detection and during periodic population surveys as described in detail elsewhere [51] . Venous blood was collected in acid citrate dextrose on the day of recruitment , and again 3 months later for City naïve subjects and 3 , 6 and 12 months after recruitment for rural subjects . Giemsa-stained blood films were examined for the presence of malaria parasites . Blood samples from each subject were checked for subpatent malaria parasitaemia by PCR . DNA was isolated using FlexiGene DNA extraction kits ( Qiagen® ) according to the manufacturer's protocol and subjected to nested PCR for P . falciparum and P . vivax as described previously [52] . As HIV infection may have an effect on immunological parameters , all subjects were tested for HIV infection ( presence of anti-HIV antibodies by gel particle agglutination assay ) at the time of recruitment and at the end of the study ( 3 months after recruitment for city subjects and 12 months after recruitment for other groups ) ; subjects received pre- and post-test counselling from trained HIV counsellors and HIV-infected individuals were given access to the National Antiretroviral Programme . Data from HIV-infected subjects were excluded from the analysis . P . falciparum circumsporozoite protein ( PfCSP ) [ ( NANP ) 4] and P . falciparum merozoite surface protein-2 ( PfMSP-2 ) were a gift from J . E . Tongren ( Centre for Disease Control and Prevention , Atlanta , GA , USA ) . The 19kDa fragments of P . falciparum and P . vivax MSP-1 ( PfMSP-119 and PvMSP-119 ) were gifts from A . Holder ( National Institute of Medical Research , London , UK ) and the proteins were expressed as described [53] . P . falciparum apical membrane antigen-1 ( PfAMA-1 ) was a gift from R . F . Anders ( LaTrobe University , Victoria , Australia ) ; the equivalent P . vivax antigen ( PvAMA-1 ) was a gift from B . Farber and A . Thomas ( Biomedical Primate Research Centre , Rijswik , Netherlands ) . P . vivax duffy binding protein ( PvDBP ) was a gift from L . H . Carvalho Centro de Pesquisas René Rachou , Fundação Oswaldo Cruz , Belo Horizonte , MG , Brazil ) . Since Thai populations are routinely vaccinated with tetanus toxoid ( TT ) , antibody responses to TT were included as a positive control . TT was obtained from the National Institute of Biological Standards and Control ( Health Protection Agency , Hertfordshire , UK ) . Keyhole limpet haemocyanin ( KLH ) was from Thermos Fisher Scientific ( Northumberland , UK ) . Continuous cultures of P . falciparum ( 3D7 strain were maintained in the laboratory [54] and were periodically shown to be free from Mycoplasma contamination by polymerase chain reaction ( PCR ) ( Venor® GeM , Minerva Biolabs ) . Mature schizonts were obtained by gradient centrifugation over 60% Percoll ( Amersham Biosciences ) , adjusted to a concentration 1×108 schizont-infected red blood cells ( iRBC ) /ml and exposed to three freeze/thaw cycles to obtain P . falciparum schizont extract ( PfSE ) . Plasma antibody levels were detected by indirect ELISA , as described [55] . Briefly , Immulon 4HB ( Dynatech ) or Maxisorb ( Nunc ) plates were coated with antigen ( at a concentration equivalent to 105 iRBC/ml for PfSE , 0 . 5 µg/ml for Plasmodium-derived antigens and TT ) in bicarbonate buffer ( pH 9 . 6 ) overnight at 4°C . Plates were blocked with PBS containing 1% non-fat milk powder . Diluted plasma samples ( 1∶200 for PfCSP , 1∶1000 for PfSE , PfMSP-119 , PfMSP-2 , PvMSP-119 and PvDBP; 1∶2000 for PfAMA-1 , PvAMA-1 and TT ) were incubated in dubplicate . Plates were subsequently developed with anti-human IgG horseradish peroxidase conjugate ( Caltag Laboratories , Invitrogen , Paisley , UK ) followed by o-phenylenediamine substrate ( Sigma ) . The enzyme reaction was terminated with sulphuric acid ( 2N ) and absorbance was then read at 492 nm on a Spectra MR plate reader ( Dynex Technology ) . Antibody levels were determined by comparison to a standard curve ( derived by serial dilution of a pool of hyperimmune plasma collected in The Gambia , which was given an arbitrary value of 1 , 000 units/ml of anti-PfSE Abs ) on each plate , as described previously [12] . PBMCs were separated from citrated blood by gradient centrifugation over Ficoll-Hypaque ( Amersham Biosciences ) . Contaminating erythrocytes were removed by incubating with lysis buffer ( 0 . 15 M NH4Cl , 10 mM KHCO3 , 0 . 1 mM Na2EDTA ) at RT for 5 minutes . The cells were washed twice with RPMI , resuspended in 10% human AB serum/RPMI ( R10 culture medium ) , counted , adjusted to the required concentration and cryopreserved in 10% dimethylsulfoxide ( DMSO ) /foetal calf serum . Cryopreserved PBMCs were quick thawed in a 37°C water bath . The cells were washed twice with warm RPMI , resuspended in R10 culture medium and added at a concentration of 1×106 cells/ml to a 24 well culture plate . The cells were stimulated with medium alone or with a mixture of Phytolacca americana pokeweed mitogen ( 1/100 , 000 dilution; a gift from M . Causland and S . Crotty , La Jolla Institute of Allergy and Immunology , CA , USA ) , 6 µg/ml CpG 2006 ( Qiagen/Operon ) , and 1/10 , 000 dilution of Staphylococcus Aureus Cowan ( SAC ) ( Sigma ) , as previously described [25] . The culture plates were incubated in 5% CO2 at 37°C for 5 days . B cell ELISPOT assays were performed as described previously [25] . Briefly , ELISPOT plates ( Millipore ) were coated with donkey anti-human IgG ( H+L ) ( Jackson ImmunoResearch ) , or with 1 µg/ml recombinant malaria proteins overnight at 4°C . After washing once with PBS-T and three times with PBS , 200 µl of 1% bovine serum albumin in RPMI were added to each well and incubated for 2 hours at 37°C , 5% CO2 . Cultured PBMCs were recovered from the 24 well culture plates , washed , transferred directly to antigen-coated ELISPOT plates and incubated for 6 hours at 37°C , 5% CO2 . After 4 washes with PBS and 4 washes with PBS-T , 100 µl of Biotin-SP-conjugated donkey anti-human IgG ( Jackson Immunoresearch ) were added to each well and the plates were incubated overnight at 4°C . The plates were washed , 100 µl of alkaline phosphatase-streptavidin ( Vector Laboratories ) was added and incubated for one hour at room temperature . After three washes with PBS-T and three washes with PBS , 100 µl of 5-bromo-4-chloro-3-indolyl phosphate/ nitro blue tetrazolium - alkaline phosphatase substrate solution ( Vector Laboratories ) were added to each well and the reaction was allowed to proceed for 8 minutes before being stopped with distilled water . In vitro restimulated PBMCs incubated overnight with an irrelevant protein , KLH , as well as PBMCs cultured without stimulation and then incubated overnight with malaria antigens were used as negative controls . Since no malaria-specific spots were detected in city naïve individuals , this group was not be used to set a cut-off for positivity . Rather , a positive ELISPOT response was defined when spots were observed in 2 or more replicate wells and where the total number of spots in the antigen-coated wells was at least twice the number observed in the negative control wells . An enzyme immunoassay for determination of antibodies against malaria antigens was carried out as described above . Following the incubation step of sera with antigens , one duplicate set of sera was treated with 4 . 0 M guanidine dissociating solution ( Guanidine Hydrochloride , Sigma ) for 10 minutes prior to washing with PBS-T . Avidity indices were calculated as the ratio of the OD of guanidine -treated wells to the OD of the untreated wells . To determine whether an individual was seropositive for a particular antigen ( PfSE , Pf- or Pv-derived antigens , or TT ) , cut-offs for positive antibody titres were calculated using a mixture model , which assumes that untransformed titres for seropositive and seronegative samples each follow a normal Gaussian distribution [56] , [57] . Mann Whitney U test was used to analyse differences in the levels of antibodies or memory B cells among groups ( GraphPad Prism software ) . Fischer's exact test was used to analyse differences in the proportion of positive individuals between Rural 1 and Rural 2 groups , as well as differences in the proportion of seropositives at recruitment compared to 12 months later . Decay rates for antibody titres and memory B cell frequencies were calculated using logarithmically transformed data from subjects who were seropositive or memory B cell positive , respectively , at recruitment . The effect of time since malaria infection was analysed using a log-linear mixed-effects regression model incorporating Gaussian random intercepts . This resulted in an estimate of the decay rate of antibody titres or memory B cell frequencies , assuming a single-exponential decay model . Half-lives were calculated from the estimated decay rate and the boundaries at 95% confidence interval obtained from the mixed-effects model . Where the decay rate is a positive value , the calculated half-life is reported as infinity . All analyses were undertaken using Stata ( version 10 , Statacorp LP ) .
|
It is widely perceived that immunity to malaria is short-lived , rendering people susceptible to repeated malaria infections . However , there have been very few studies on “memory” responses , how the human immune system recognizes previously encountered malaria parasites . In particular , very little is known about the durability of malaria-specific B cells and antibodies . The aim of this study was to investigate the induction and maintenance of B cell memory responses to malaria parasites in a region of Thailand where people become infected with malaria , but where the levels of malaria transmission are so low that repeated infection is uncommon . From hospital records we were able to identify people who either had been infected with malaria over the past 6 years and/or had never been infected . Blood samples were collected on four separate occasions over a period of one year and analysed by microscopy and PCR for presence of malaria parasites and by ELISA and ELISPOT for anti malarial antibodies and malaria-specific memory B cells . We found that , in a significant proportion of individuals , malaria infection results in the generation of antibodies and the establishment of populations of memory B cells against malaria parasites , which were very stably maintained over time despite the lack of any evidence of malaria reinfection . Contrary to the widely held idea that memory to malaria is suboptimally induced , our data demonstrate that B cell responses to malaria can be maintained for many years after a malaria infection and indicate that there is no inherent reason why malaria vaccines should not also induce long-lasting protection against malaria .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunology/immune",
"response",
"public",
"health",
"and",
"epidemiology/infectious",
"diseases",
"infectious",
"diseases/protozoal",
"infections",
"infectious",
"diseases/tropical",
"and",
"travel-associated",
"diseases",
"immunology/immunity",
"to",
"infections"
] |
2010
|
Long-Lived Antibody and B Cell Memory Responses to the Human Malaria Parasites, Plasmodium falciparum and Plasmodium vivax
|
Neurons develop distinctive dendritic morphologies to receive and process information . Previous experiments showed that competitive dendro-dendritic interactions play critical roles in shaping dendrites of the space-filling type , which uniformly cover their receptive field . We incorporated this finding in constructing a new mathematical model , in which reaction dynamics of two chemicals ( activator and suppressor ) are coupled to neuronal dendrite growth . Our numerical analysis determined the conditions for dendritic branching and suggested that the self-organizing property of the proposed system can underlie dendritogenesis . Furthermore , we found a clear correlation between dendrite shape and the distribution of the activator , thus providing a morphological criterion to predict the in vivo distribution of the hypothetical molecular complexes responsible for dendrite elongation and branching .
One of the primary interests in developmental biology is the emergence of function through morphogenesis . Morphological diversity of dendrites and its impact on neuronal computation perfectly represents the importance of this problem: shapes of dendrites are highly variable from one neuronal type to another , and it has been suggested that this diversity supports differential processing of information in each type of neuron [1–3] . Therefore , patterning of neuronal class-specific dendrites is a process to produce shapes that realizes the physiological functions of neurons . Recent advances in genetic manipulation at the single-cell level enabled us to identify genes whose loss of function affects neuronal morphology ( reviewed in [4–6] ) ; however , we are far from formulating an overall picture of the underlying mechanism of pattern formation . Among various classes of dendrites is the “space-filling” type , which uniformly covers its receptive field . The concept of space-filling was introduced by Fiala and Harris [7] , and we use this term with a slightly different meaning here . Neurons elaborating space-filling dendrites are found in various parts of nervous system , including retinal ganglion cells [8] , trigeminal ganglion cells [9] , Purkinje cells ( Figure 8B ) [10] , and Drosophila class IV dendritic arborization ( da ) neurons ( Figure 1 ) [11–14] . The space-filling type looks very complex morphologically , but can be regarded as being simple in their isotropic features and in their two-dimensionality . Most importantly , it shows distinctive spatial regulation of pattern formation: for instance , dendritic branches of Drosophila class IV da neurons avoid dendrites of the same cell and those of neighboring class IV cells , which allows complete , but minimal overlapping , innervation of the body wall ( designated as isoneuronal avoidance and tiling ) ( Figure 1A and 1B ) [11 , 13–15] . Our previous experiment together with studies by others demonstrated that competitive dendro-dendritic interaction underlies tiling , as shown by the fact that the da neurons reaccomplish tiling in response to ablation of adjacent neurons of the same class or to severing of their branches ( Figure 1C ) [11 , 14] . It should be noted that the qualitatively same inhibitory dendro-dendritic interaction is working between the adjacent neurons of the same type as well as between dendrites of the same neurons . There are two types of the proposed mechanisms that support this repulsive behavior of dendrites: one is contact-dependent retraction of dendrites and the other is repulsion of dendrites via diffusive suppressors . The contact-dependent mechanism seems insufficient to a clear field splitting , because as far as dendrites do not make contacts ( by passing under other dendrites , for example ) they can invade neighboring territories . Moreover , time-lapse analysis showed that dendrites make a turn before they are about to cross nearby branches [16] . So we prefer diffusive signaling to a contact-dependent one . Similar mechanisms have been suggested to work in other model systems as well [9 , 17 , 18] . With all available information taken together , we considered the space-filling dendrite to be an ideally suited one for us to start modeling , due to the simplicity of its patterning and the experimentally verified mechanism of the pattern formation . A number of mathematical models for neurite formation were previously proposed; and most of them assumed that dendrite development is a consequence of stochastic sprouting and subsequent growth arrest [19–22] . Different forms of branching functions were postulated and modified so that calculated dendrograms would fit dendritic arbors of real neurons in a quantitative manner . Those studies were descriptive and did not provide a comprehensive mechanism of pattern formation . In this study , we developed a new class of mathematical model for neurite formation to approach a principle of development of the space-filling dendrites . In our neurite growth model that is based on the aforementioned inhibitory dendro-dendritic interaction , various aspects of pattern formation , e . g . , extension , orientation of growth , and branching of dendrites , are represented in a single framework . Computer simulation showed that our model develops dendritic extension and branching autonomously; furthermore , numerical analysis determined the conditions for dendritic growth .
As mentioned above , two-dimensionality is a characteristic of space-filling dendrites; thus we built our model in the 2D space , dividing the 2D space into two distinct compartments ( Figure 2A ) , i . e . , the compartment occupied by neurons ( designated as the cell compartment or the cell region hereafter ) and the extracellular compartment . This model is referred to as the “cell compartment model . ” We assumed that growth of the cell region , which shapes the dendritic trees , is regulated by a hypothetical intracellular chemical , i . e . , the activator ( Figure 2A ) . We set a restriction in terms of the movement of the activator so that it diffuses only the inside of cells . The activator promotes the growth of the cell compartment when its concentration is higher than threshold ( Tr in Figure 2D ) . To account for the inhibitory dendro-dendritic interaction , we hypothesized another chemical , the suppressor . The suppressor is produced when the concentration of activator is high , i . e . , it is produced at the actively growing region of dendrites . The suppressor acts to decrease the concentration of activator , but the concentration of activator can increase by its autocatalytic production where the activator is locally concentrated . The reaction between activator and suppressor is the so-called “activator-inhibitor type” [23 , 24] ( “1” in Figure 2A ) . The activator-induced production of the suppressor can be realized by either local translation of suppressor-encoding mRNA in dendrites [25] or secretion of suppressor proteins from intracellular organelles . The suppressor is secreted from the cell , diffuses throughout the extracellular space , and then binding of the suppressor to its receptor drives intracellular signaling to repress the production of the activator ( “2” in Figure 2A ) . So , the suppressor mediates long-range inhibitory interactions between dendrites ( Figure 2B ) . These settings endow the system with feedback-loop regulation at two different levels: one is between the two chemicals and the other is between the dynamics of these chemicals and the expansion of the cell compartment . The latter consists of the following reciprocal interactions: the activator controls growth of the cell region and growth of the cell region determines where the activator can diffuse further . Our model can be written as the following equations: where u and v are concentrations of the activator and the suppressor , respectively . Note that these equations are already non-dimensionalized , so d is the ratio of the diffusion coefficient between the two substances ( see the section “Original equations” ) . As we hypothesize that diffusion of the suppressor is faster than that of the activator , d is larger than 1 [26] . c ( x , t ) is a symbolic variable to indicate the “core” of the cell ( Figure 2C and 2D ) . The biological correlates of c could be microtubules that support structural integrity of the cell . The right-hand side of Equation 1c indicates that the dynamics of the cell state is bi-stable and that the two steady states are 1 and 0 , indicating “core” and “not core , ” respectively , and a ( u ) is the switching point at which the growth behavior of c is flipped . c quickly reaches 1 when u is higher than threshold ( Tr ) . The symbol Ω is the 2D real space , and xc denotes a point in Ω , where c is larger than 0 . 5 . Ωc , which is the region of the cell in Ω , and is defined by using xc as follows: ( γ is a rate constant to rescale time and space ) [26] . R is the distance between core and the plasma membrane , and the cell compartment is represented by collective circular domains around the core with radius R ( Figure 2C ) . We found that R = 0 . 004 realized the finest resolution of patterns , so we used this value of R throughout this study ( see the section “R value” for details ) . Describing the cell growth as a rapid transition between bistable states is reminiscent of a way to solve moving boundary problems in phase-field models [27] . A difference between these models and ours is whether diffusion of the phase field is incorporated or not; a diffusion term does not appear in Equation 1c , because diffusion of the cell state is biologically unrealistic in this case . f ( u , v ) and g ( u , v ) represent chemical reaction terms , where the partial derivatives satisfy the following conditions: > 0 ( autocatalytic production of the activator ) , < 0 ( inhibition of synthesis of the activator by the suppressor ) , > 0 ( production of the suppressor by the activator ) and < 0 ( concentration-dependent degradation of the suppressor ) . We used the following formulas for f and g: We assumed that the receptor is uniformly distributed over the dendritic surface and that the strength of the signaling follows the local concentration of the suppressor . We adopted the 0-fixed boundary condition for the activator at the cell boundary: We used the periodic boundary for the other variables v and c at the boundary of the 2D square space to model the real 2D space Ω in numerical simulation . We numerically calculated the model given by Equations 1a–1c with reaction terms of Equations 2a and 2b ( see Materials and Methods ) . Computer simulation showed that the cell compartment model could autonomously generate quite distinct dendritic patterns depending on the set of parameters employed ( Figure 3 ) . In each case where the model produced dendritic patterns , they were generated through repeated cycles of elongation and branching of dendrites ( two examples are shown in Videos S1 and S3 ) . With one set of parameters , smooth branches were formed , where neighboring branches aligned themselves nearly parallel to each other ( Figure 3A ) . In such a cell , the distribution of the activator is continuous and mostly uniform , except for every branch terminal , where the density of the activator is relatively high ( arrows in Figure 3B; Video S2 ) . With a different set of parameters , the dendritic branches showed a more rugged morphology ( Figure 3D ) . Stubby and non-aligned branches were formed , and the activator was distributed in a punctate manner in that cell ( Figure 3E; Video S4 ) . We call each punctum , where the activator was highly concentrated , a “spot . ” Dendrites elongated by generating new spots ( arrows in Figure 3E ) and bifurcated when spots fissioned ( arrowheads in Figure 3E ) . The suppressor was concentrated where the density of the activator was high , and it was distributed more broadly than the activator ( Figure 3C and 3F ) . This distribution underlies long-range inhibitory interactions between neighboring dendrites . The interactions appeared to control whether or not dendrites would branch and in which direction dendrites would elongate . As a result , the branching frequency considerably varied among branchlets ( compare yellow and blue arbors in Figure 3A and 3D ) , whereas the branch density was kept almost constant throughout the dendritic trees . In a separately prepared manuscript , we addressed more biological issues such as tiling ( Figure 1A and 1B ) and regeneration in response to branch severing ( Figure 1C ) . Branches of multiple neurons in our computer simulation , when they appeared in the same 2D space , avoided each other and accomplished tiling and isoneuronal avoidance . The neurons in our computer simulation were even able to reaccomplish tiling after local destruction of dendritic arbors exactly as Drosophila class IV da neurons do . Furthermore , modifications of our model enabled reproduction of a wide range of space-filling dendritic trees and even a non–space-filling type . Taken together , our model succeeded in qualitatively recapturing development of space-filling dendrites . In the all cells examined , u and v exhibited a linear relationship at the growing tip of dendrite ( Figure 4A for smooth branches and Figure 4B for rugged ones ) . Starting from u = 0 at the distal margin of dendrite , u should increase with time and it is observed as spatial change in u from distal to more-proximal parts of dendritic terminals . In contrast , the spatial change in v cannot be explained by reaction dynamics: for instance , in a case of Figure 4A , u and v should increase and decrease , respectively , according to vector field . Nevertheless , the supply of the suppressor from proximal dendrites via its diffusion seems to counteract actions of reaction functions , resulting in the increase of v in the proximal direction . Thus , most likely diffusion plays an essential role in determining the dynamics of the suppressor at dendritic tips . As described below , we conducted numerical analysis to examine the generality of our cell compartment model and to determine the conditions for growth of dendrites that could be common to various types of neurons . We calculated the cell compartment model by using different parameter sets of reactions between the activator and the suppressor , and searched for those by which dendritic patterns were successfully generated ( Figure 5A ) . We defined a dendritic pattern by the following two conditions: first , cellular extensions bifurcated . Second , the density of dendrites was less than a criteria value . Typical examples of patterns violating either of these conditions are shown in Figure 5B–5D . This analysis clearly shows that dendritic patterns could be generated in a large parameter region ( closed circles in Figure 5A ) , and so formation of dendritic patterns in our model does not appear to depend on particular parameter sets . As explained before , our model produced two different types of patterns: the well-aligned smooth pattern , in which the activator is continuously distributed ( Figure 3A ) and the poorly aligned rugged pattern , in which punctate distribution of the activator is seen ( Figure 3D ) . Those patterns shown in Figure 3 are two extreme examples; and intermediate patterns could be generated , depending on parameters employed . Interestingly , our numerical analysis revealed a correlation between Turing instability [23] and the distinctive shape of dendritic patterns . Turing instability , a widely applied theory of pattern formation , indicates an ability of chemical ( in this case , activator–suppressor ) interactions to develop spatially periodic patterns . The condition of chemical reaction dynamics for Turing instability was addressed by considering the two-variable ( u and v ) dynamics in the uncompartmentalized 2D space ( designated as no compartment model , that is , a conventional RD model ) , and then by numerically calculating a parameter region for potential Turing instability in the no-compartment model ( see Equations A3a–A3d in the section “Conditions for Turing diffusion-induced instability” and region I in Figure 5A ) [26] . We used typical values for other parameters such as pb because changing the pb value did not significantly alter the shape or the size of region I ( unpublished data ) . The results of this analysis clearly showed that relatively rugged patterns were obtained by using the condition that satisfied Turing instability ( region I in Figure 5A ) ; on the other hand , better-aligned patterns were obtained by using the condition that did not satisfy it ( region II in Figure 5A ) . Therefore , it is suggested that the difference in two typical dendritic patterns obtained in our computer simulation stems from whether chemical dynamics in themselves are able to develop spatially periodic patterns or not . Furthermore , we noticed that the shape of dendrites reflected the intracellular distribution of the activator . From bottom-left to top-right of the ( pe − pa ) space ( Figure 5A ) , the dendrite morphology became smoother; and distribution of the activator changed from punctate in nature to more continuous ( Figure 5E1-5E4 ) . Continuity in the activator distribution seems to strongly depend on the shape of local branches ( Figure 5E2 ) . Even within the same cell , the local distribution of the activator was punctate in branch-rich regions ( e . g . , right-enclosed branches in Figure 5E2 ) , whereas it was more continuous in branchless regions ( e . g . , left-enclosed branch in Figure 5E2 ) . Co-existence of two distinctive types of distributions , punctuate and continuous , in a single cell suggests that these two types of distributions are locally stable structures . The above-mentioned analysis also indicated that the condition for developing dendritic patterns did not entirely cover region I . In addition , it is of particular interest that spatially non-homogeneous dendritic patterns were generated in region II , in which homogeneous distribution at the steady state should be stable in the two-variable ( u and v ) dynamics ( see Discussion for details ) . Most likely this discrepancy of conditions for pattern formation in the cell compartment model and the no compartment one originates from the structure of cell and the feedback between the chemical reaction and cell growth in the model . We further examined the relationship between our model and the Turing system . In general , the Turing system develops dot , stripe , or reverse-dot patterns in the 2D space , depending on parameters ( e . g . , the distance from the equilibrium point to the upper limitation of activator [Amax] ) [28] . So we explored whether or not the conditions for dendritic pattern formation were related to the property of the Turing system to generate either a dot , stripe , or reverse-dot pattern . By changing the upper limitation of activator ( Amax ) in the no-compartment model , we drew a phase diagram , in which each dot , stripe , and reverse-dot pattern was mapped to a different parameter region ( Figure 6A ) . Subsequently we searched for parameter sets that developed dendritic patterns in the cell compartment model ( circles in Figure 6A ) ; and the results of this analysis indicated that dendritic patterns were obtained mostly in the dot domain ( D in Figure 6A ) . Therefore the punctate distribution of the activator in rugged dendrites ( Figure 3E ) can be interpreted as the typical dot pattern of the conventional RD system being generated inside of the cell compartment . Dendritic patterns were not obtained in most of the stripe or reverse-dot domains ( S or R in Figure 6A ) . Computer simulation with parameter settings in the stripe or reverse-dot domains generated patterns , which did not resemble the shape of dendritic arbors of real neurons ( Figure 6B–6E ) . If conditions for Turing instability were not satisfied , dendritic pattern was produced in a parameter region adjacent to the dot domain . These results are consistent with an intuitive understanding of the process of dendritic pattern formation; that is , dendrites grow in pursuit of a track of locally activated molecular complexes for branching . In this sense , a punctate or terminally dense distribution of activator is favored , whereas the stripe or reverse-dot one is not . It is worth evaluating whether the results of this study are specific to a particular dynamics or if they represent more general properties of the RD system . For that purpose , we tested several different forms of reaction terms and one of them was as given below: Parameter settings for potential Turing instability in the linear dynamics described by Equations 3a and 3b were determined and plotted ( region I in Figure 7A ) as in Figure 5A . Parameter dependency of dendritic pattern formation was examined , and we found that dendritic patterns were generated in both outside and inside of region I ( Figure 7B and 7D , respectively ) . Therefore , classical Turing conditions were not necessary or sufficient for dendritic pattern formation in this linear dynamics , either . Furthermore , whether the function was linear or non-linear , the activator distribution well-correlated with the shape of branches ( Figure 7C and 7E; compare them to Figure 5E ) ; and dendritic patterns were generated preferentially in the dot domain , but not in the stripe or reverse-dot domain ( unpublished data ) . Collectively , all of the results suggest that a wide range of parameter settings and different dynamics of chemical reactants allow development of dendritic patterns in the cell compartment model . Finally we found that our cell compartment model provides a prediction for future experiments . As described before , the numerical simulation of the model unraveled a strong correlation between shapes of dendrite and distributions of the activator ( Figure 5E and Figure 7E ) . We noticed that dendritic trees of some real neurons were reminiscent of those of the smooth type in our computer simulation ( Figure 8A and 8B ) and that terminal branches of some other real neurons were less aligned ( Figure 8C and 8D ) . Accordingly , if the developmental machinery proposed by this study is actually functioning in vivo , the intracellular distribution of the hypothetical activator could be predicted on the basis of the morphological features of dendrites . More specifically , the distribution of the activator may be terminally dense in neurons of the smooth type and punctate in the rugged type ( for instance , Figure 8A and 8B and Figure 8C and 8D , respectively ) . To support the validity of our prediction , we set a quantitative measure called a “dispersion of orientation of branches” ( DOB ) to characterize dendrite morphology . DOB is the coefficient of variation of directions of branch segments in each local region of dendritic trees ( Figure 9 and Materials and Methods ) ; hence the smaller is the DOB , the better-aligned are the local branches . Quantification of the DOB for the smooth and rugged types of the obtained patterns in our computer simulation confirmed that it was significantly smaller in the former type ( double asterisks in Figure 8E ) . We next quantified the DOB for real neurons and found that values for the smooth type ( Figure 8A and 8B ) were significantly smaller than those for the less-aligned type ( Figure 8C and 8D; asterisks in Figure 8E ) . These results suggest that geometry of real neurons may also be characterized by DOB and that we can use DOB as a morphological measure for predicting the intracellular distribution of the activator in vivo .
In this study , we developed the first mathematical model that sheds light on autonomous pattern formation of neuronal dendrites . The cell compartment model , which is based on the experimentally verified dendro-dendritic interaction , autonomously develops dendritic elongation and branching . It should be noted that dendritic patterns are defined not only by the numerical parameters such as the terminal number , but also by other properties such as mutual avoidance . Our model places emphasis on the latter aspects of the space-filling dendrites , which are difficult to characterize by quantitative measures , and indeed qualitatively recaptures developmental regulation of the space-filling dendritic patterns . Collectively , we believe that this study offers a new concept in developmental biology , a self-organizing mechanism in neuronal dendrite pattern formation . Many of the previous models assumed that elongation and branching of dendrites are controlled by probability functions , in which each parameter separately codes individual growth rules such as degree- or segment length- dependent rate of elongation and/or branching [19 , 20] . In contrast , dendritic patterns are autonomously generated without embedding different parameters to control each branching frequency , branch angle , and self-avoidance of dendrites in our model . Considering that we are presently far from understanding the entirety of the molecular mechanisms of chemical reactions occurring in vivo , the high performance of the proposed system obtained with diverse forms of reaction function takes on significance , because it may support a future application of the model to the dendritogenesis of a whole variety of real neurons . Our numerical analysis showed that generation of dot patterns of the activator in rugged dendrites could be attributed to a property of chemical dynamics , which is supported by Turing instability . On the other hand , classical Turing diffusion-induced instability alone cannot give us a comprehensive explanation of the pattern formation in our model , because dendritic patterns were successfully developed even when the spatially homogeneous pattern at the steady state of chemical reaction dynamics was stable . We think that the compartmentalized structure in our model may increase instability of the dynamics of the cell growth . Actually , it was shown both in experiments and in computer simulation that a straight interface could become unstable to make complex spatial patterns in certain bistable dynamics [27 , 29] . Hence , analyzing the model based on the idea of front instability may be one way to understand the behavior of our model . From a viewpoint of experimental biology , these results suggest that simultaneous , high-resolution imaging analyses on molecular interactions and plasma membrane dynamics would be informative . We introduced new criteria to categorize patterns of dendrites in real neurons and to predict the intracellular distribution of potential molecular complexes for dendrite growth . Two distinctive dendritic patterns were found in both computer-simulated and real neurons , and it is suggested that the distribution of the activator is characteristic of the shape of branches . Further advances in our understanding of the molecular mechanisms involved in dendrite development are required to address whether the prediction from our cell compartment model is valid or not . Yet , there are a couple of interesting observations that may indicate periodicity in dendrites of real neurons . For instance , Golgi apparatus is distributed in a punctate manner in da neurons and pyramidal neurons [30–32]; and its localizations at branch points are important for branch formation . In addition , staining for microtubule-associated protein 2 in the absence of detergents reveals that regions of high signal intensity are found in a spatially periodic manner along dendrites and that dendritic branch points are preferentially associated with these regions [33] . It would be interesting to review these observations in the perspective of our model . Our cell compartment model is a simplified version of dendrite growth in vivo , and new elements can be installed depending on needs or researchers' interests . For instance , although generated patterns in the present model are highly homogeneous , less homogeneous patterns could be obtained if stochastic aspects or noise are strengthened ( for example , by fluctuating Tr along dendritic branches ) . It is also interesting to extend our model to include activity-dependent processes , such as synaptotropic dendrite growth [34 , 35] and refinement of pre-existing branches during late stages of development [36 , 37] . Furthermore , we are now trying to reproduce development of non–space-filling type dendrites , which are anisotropic in terms of the direction of elongation and inhomogeneous in terms of coverage of a field , by incorporating a guidance mechanism and/or an RD system of intracellular activator and suppressor . Although we should bear in mind that overlaying these additional features could modify the properties of the system , we hope that combination of biochemical experiments with enlarged editions of this mathematical model may clarify the comprehensive logic underlying neuronal dendrite development . Colony formation by Bacillus subtilis is a well-known example of dendritic patterning in biology . Bacillus subtilis generates distinctive colony patterns depending on the substrate softness and nutrient concentration [38] , and formation of most of the colony patterns was well-reproduced by RD models [39 , 40] and a cell automaton model [41] . Similarity between neuronal dendrites and bacteria colonies is found not only in terms of their morphology , but also with respect to repulsive behaviors; i . e . , when two colonies are in close proximity , they avoid each other just as do space-filling neurons [42] . In addition , interesting parallels can be also found between dendrite development and other branching morphogenesis such as coral [43] , vertebrate lung [44] , and trachea of Drosophila [45] . These systems accomplish physiological functions that can be regarded as similar to space-filling dendrites . For instance , trachea must elaborate its branches to deliver oxygen to the whole body . Mathematical models for these pattern formations have been proposed [43 , 44 , 46 , 47] , and it is suggested that branching morphogenesis in general can be understood as the following: a part of the structure that happens to sprout due to some fluctuation locally speeds up its growth and eventually develops a visible branch . We observed a similar behavior of dendrites in our computer simulation . Furthermore , recent works revealed the molecular basis of lateral inhibition between the neighboring lung epithelium and between growing tips of trachea that may correspond to long-range inhibitory dendro-dendritic interactions in the development of space-filling dendrites [44–46] . Therefore , our model on neurite formation would be potentially informative in understanding the above-mentioned branching morphogenesis . Despite the afore-mentioned similarities , there is one big difference between bacteria colony models and ours . The former relies on non-linearity in diffusion and reaction function for pattern formation [39] . On the other hands , dendritc growth in our model does not require such non-linearity ( Figure 7 ) . It might be that unambiguous boundary of the cell in our model plays an equivalent role to non-linear diffusion terms in bacteria colony models . Taking advantage of the fewer constraints in chemical dynamics in our model , we addressed the relationship between Turing instability and biological branching morphogenesis . Other branching morphogenesis might obey the conditions that were clarified in this study . Again , generality of the proposed mechanism would be significant for testing this possibility in other systems of interest .
To calculate the model , we used the finite difference method , a simple explicit scheme . The simulation starts from a small cell body . The initial value of the activator is 0 . 5± small random deviations in each position inside of the cell body and 0 in other places , whereas the value of the suppressor is 0 . 1± small random deviations in the cell body and 0 otherwise . Changes in initial conditions of the activator or the suppressor affected the results only slightly . Small noise was added to the diffusion coefficient of the activator in every calculation step to cancel the anisotropy of the grid in numerical simulation . Image processing and measurement were done with ImageJ . First , we superimposed a square on individual dendritic trees ( those in Figure 3A and 3D and Figure 8A–8D; see also Figure 9 ) . The size of each square was normalized to that of the entire dendritic tree ( the size of the tree was defined as that of a polygon connecting dendritic tips ) . As for the obtained patterns in computer simulation ( those in Figure 3A and 3D ) , we skeletonized them and sampled four pairs of squares that were located at the same coordinates ( “1” and “2” in Figure 9 ) . Each branch segment was approximated by a line segment connecting two edges of the branch segment ( “3” in Figure 9 ) . We measured the angle of the line segment with respect to the horizontal direction , repeated measurement for all segments in each small square , and calculated the coefficient of variation , which we called the DOB . Average values of DOB for each dendritic tree are shown with means ± SD in Figure 8E . Imaging and single cell labeling of Drosophila sensory neurons were done as described [11 , 13 , 48] . Strains used were NP7028 UAS-mCD8::GFP [11] , ppk-GAL4 UAS-mCD8::GFP [49] , elav-GAL4 UAS-mCD8::GFP hsFLP , tub-Gal80 FRT40A , and FRT40A [13] . Original equations of the activator-suppressor model were as follows: where u and v are the concentration of the activator and that of the suppressor , respectively . du and dv are diffusion coefficients . Original chemical reaction terms were: We non-dimensionalized Equations 4a–4c and Equations 5a–5b to obtain Equations 1a–1c and Equations 2a–2b . The value of R determines the thickness of the branches as expected . Smaller R resulted in thinner branches , thus finer patterns . However , there seems to be a minimum value of R to support dendrite growth . The minimum value may be necessary to produce a new spot of the activator , which is separated from the pre-existing spot , in the vicinity of the cell boundary . We confirmed that the minimum value of R was independent of the spatial grid size in numerical simulation , and thus the above results are not an artifact of numerical simulation . So we used R = 0 . 004 , which gave the finest dendritic patterns ( R = 0 . 0041 yielded nearly equal results to those obtained with R = 0 . 004 ) . Conditions for Turing diffusion-induced instability [23] are the following: where the partial derivatives of f and g are evaluated at the steady state ( u0 , v0 ) which satisfies f ( u0 , v0 ) = 0 and g ( u0 , v0 ) = 0 [26] . Equations 6a and 6b describe conditions for a stable equilibrium point in the absence of diffusion . Equations 6c and 6d describe conditions for an unstable periodic solution in the presence of diffusion .
|
Neurons elaborate two types of neuronal extensions . One is axon , which sends outputs to other neurons . Another is dendrite , which is specialized for receiving and processing synaptic or sensory inputs . Like elaborated branches of trees , the shape of dendrites is quite variable from one type to another , and different dendritic geometry contributes to differential informational processing and computation . For instance , neurons of the space-filling type ( e . g . , retinal ganglion cells ) fill in an open space to pick up spatial information from every corner of their receptive field . Therefore , dendrite development is one of the representative examples of the emergence of function through morphogenesis . Previous experiments including ours showed that competitive dendro-dendritic interactions play critical roles in shaping dendrites of the space-filling type . In the present study , we incorporated this finding in constructing a new mathematical model , in which reaction dynamics of chemicals are coupled to neuronal dendrite growth . Our numerical analysis suggested that self-organizing property of the proposed system underlies formation of space-filling dendrites . Furthermore , we provided a morphological criterion to predict the in vivo distribution of the hypothetical molecular complexes responsible for dendrite elongation and branching . We have now found a substantial number of molecules involved in dendrite development , thus it is timely to discuss the prediction from this work .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"mathematics",
"drosophila",
"developmental",
"biology"
] |
2007
|
Self-organizing Mechanism for Development of Space-filling Neuronal Dendrites
|
Mitochondrial function affects many aspects of cellular physiology , and , most recently , its role in epigenetics has been reported . Mechanistically , how mitochondrial function alters DNA methylation patterns in the nucleus remains ill defined . Using a cell culture model of induced mitochondrial DNA ( mtDNA ) depletion , in this study we show that progressive mitochondrial dysfunction leads to an early transcriptional and metabolic program centered on the metabolism of various amino acids , including those involved in the methionine cycle . We find that this program also increases DNA methylation , which occurs primarily in the genes that are differentially expressed . Maintenance of mitochondrial nicotinamide adenine dinucleotide reduced ( NADH ) oxidation in the context of mtDNA loss rescues methionine salvage and polyamine synthesis and prevents changes in DNA methylation and gene expression but does not affect serine/folate metabolism or transsulfuration . This work provides a novel mechanistic link between mitochondrial function and epigenetic regulation of gene expression that involves polyamine and methionine metabolism responding to changes in the tricarboxylic acid ( TCA ) cycle . Given the implications of these findings , future studies across different physiological contexts and in vivo are warranted .
Mitochondrial function is key to normal cellular physiology , given the many different biochemical process that occur in the organelle [1] . A tremendous amount of effort over the past several decades has been dedicated to understanding how mitochondrial dysfunction impacts the cellular environment and organismal health . This has been largely based on studies of rare mitochondrial diseases that share many molecular mechanisms with more common disorders that also present with mitochondrial dysfunction , e . g . , Parkinson’s disease , cancer , and diabetes . Despite these efforts , fundamental aspects of how mitochondria function impacts cellular physiology remain ill defined . For instance , how the mitochondria communicate with and impact reactions within the nucleus is poorly understood . The gene expression program ( s ) and metabolic rewiring that change in response to mitochondrial dysfunction are not clear . It is also not known whether mitochondrial-driven epigenetic changes impact gene transcription . Finally , despite the fact that mitochondrial dysfunction can increase DNA methylation [2 , 3] , a mechanistic link between these effects is still missing . We recently described a novel cell culture model of progressive mitochondrial DNA ( mtDNA ) depletion in the human embryonic kidney 293 ( HEK293 ) background [4] . This model relies on the inducible expression of a mutant mtDNA polymerase gamma that works as a dominant negative , herein called DN-POLG ( dominant-negative DNA polymerase gamma transgene ) . Upon addition of doxycycline , DN-POLG is expressed , and over a period of 9 days , the mtDNA is completely depleted . Because the mtDNA encodes critical components of the electron transport chain ( ETC ) —which generates ATP using tricarboxylic acid ( TCA ) cycle–derived nicotinamide adenine dinucleotide reduced ( NADH ) or flavin adenine dinucleotide hydroquinone ( FADH2 ) —by depleting the mitochondrial genome , we can regulate electron transport , ATP production , and the flux through the TCA cycle . Additionally , because a membrane potential ( ΔΨm ) is generated as a byproduct of the ETC , producing reactive oxygen species ( ROS ) , we can also modulate redox signaling . Using this model , we showed that complete loss of mtDNA and of ETC function ( achieved at day 9 ) led to severe mitochondrial dysfunction and loss of cell proliferation . We also showed that , concomitant to loss of mtDNA , histone acetylation was decreased in the nucleus . Using isogenic cells that ectopically express 2 nonmammalian proteins—NADH dehydrogenase-like 1 ( NDI1 ) and alternative oxidase ( AOX ) —we found that maintenance of NADH oxidation with a pseudo-ETC was sufficient to preserve levels of histone acetylation but had no impact on cellular proliferation in the absence of mtDNA . Conversely , by deleting ATPase inhibitory factor subunit 1 ( ATPIF1 ) , a regulatory subunit of the mitochondrial ATPase , we showed that maintenance of the ΔΨm without rescue of histone acetylation or ATP production sustained cell proliferation under conditions of complete mtDNA loss , seemingly by restoring redox signaling [4] . The unique progressive nature of mtDNA depletion and mitochondrial dysfunction of this cell culture system provides an exceptional opportunity to fill some of the gaps of knowledge in the field . In this study , we took advantage of this model to gain insights into how cells respond to stepwise mitochondrial dysfunction from transcriptomic , metabolic , and epigenetic perspectives . Our approach revealed that metabolic , epigenetic , and gene expression changes initiate prior to detectable signs of mitochondrial dysfunction , primarily centering on an amino acid response that also aims to sustain the TCA . Unexpectedly , we found that polyamine metabolism is significantly changed upon mitochondrial dysfunction; this , in turn , impacts the methionine cycle and DNA methylation in ways that are independent of serine-driven one-carbon ( 1C ) remodeling or transsulfuration .
The progressive nature of mtDNA depletion in the DN-POLG system provided us with a unique opportunity to address fundamental questions about the nuclear response to progressive mitochondrial dysfunction . We took an integrative approach that involved transcriptomic , metabolomics , and epigenetic analyses at each time point ( days 0 , 3 , 6 , and 9 ) during the course of complete mtDNA depletion . Furthermore , we utilized the cells expressing NDI1/AOX to define the responses to complete mtDNA loss that were specifically linked to NADH oxidation in the mitochondria . A schematic representation of this integrative approach is shown in S1A Fig . The reproducibility of the results is shown in S1B–S1G Fig . We started by performing RNA sequencing ( RNA-seq ) at days 0 , 3 , 6 , and 9 in the DN-POLG cells , and found 2 , 854 genes ( S1 Data ) , including all mtDNA-encoded transcripts , whose expression was changed ( adjusted p ≤ 0 . 05 ) at any given day compared to day 0 ( Fig 1A ) . When stratifying by day , we found 236 differentially expressed genes ( DEGs ) at day 3 , which were mostly ( 78% ) upregulated , while we found 2 , 135 DEGs at day 6 ( 1 , 064 upregulated and 1 , 071 downregulated ) . At day 9 we found 1 , 272 DEGs , most of which ( 64% ) were upregulated ( Fig 1B ) . Common to all time points were 121 DEGs , including POLG that was upregulated at least 7-fold relative to day 0 ( S1 Data ) . The identification of over 200 DEGs at day 3 was surprising given the lack of significant changes in mitochondrial function at this time [4] . Our model also revealed progressive upregulation of fibroblast growth factor 21 ( FGF21 ) and growth differentiation factor 15 ( GDF15 ) relative to day 0 ( S1 Data ) . FGF21 and GDF15 are metabolic cytokines induced in patients and mouse models of mtDNA or protein translation defects , which have been proposed as biomarkers of mitochondrial dysfunction [1] . Validation of randomly selected genes by quantitative real-time PCR can be found in S2A Fig . The use of Ingenuity Pathway Analysis ( IPA ) revealed that , globally , the genes modulated during the course of mtDNA depletion enriched for tRNA charging , cholesterol biosynthesis , glutamate ( via 4-aminobutyrate ) and putrescine degradation , and D-myo-inositol-5-phosphate metabolism ( top 10 , S2 Data ) . These results are consistent with the loss of mtDNA having a negative impact on oxidative TCA flux , since glutamate degradation can contribute to the cycle as precursor for succinate . Likewise , putrescine can contribute to the TCA as succinate via γ-aminobutyric acid ( GABA ) catabolism [5] , known to occur in cells beyond the central nervous system [6] . To our knowledge , this is the first report to identify polyamine metabolism as responsive to loss of mitochondrial function . Inositols are sensitive to glucose and NADH levels [7] , the metabolism of which is also impacted by loss of mtDNA . To understand how DN-POLG cells respond to progressive loss of mtDNA , we next stratified the analysis based on time point and the directionality of gene changes . We reasoned that the genes modulated at day 3 would reflect early responses to mtDNA depletion that take place prior to signs of mitochondrial dysfunction [4] . Those DEGs at day 6 would reveal responses to significant loss of ETC function and the pathways directly linked to this process—e . g . , ATP production and the oxidative TCA—while the ones detected at day 9 would reveal adaptive changes within the cell . A summary of the main transcriptional responses identified at each time point is shown in Fig 1C . Most genes detected at day 3 ( 184 ) were upregulated and enriched for methionine and cysteine degradation ( S2 Data ) . Alterations in the methionine cycle have not been directly associated with mitochondrial dysfunction , although channeling of 1C units toward transsulfuration of homocysteine to cysteine , a branch point in the methionine cycle , has been recently reported [8 , 9] . However , the degradation of methionine can ultimately input into the TCA cycle by contributing pyruvate ( through cysteine ) and succinyl-CoA through aminobutanoate [10–12]; this would provide a link between mtDNA depletion and methionine degradation . Nevertheless , it was surprising to identify these changes at day 3 when no significant alterations in mitochondrial function were identified [4] . Concomitant to the degradation of methionine , we observed DEGs involved in the recycling ( or salvage ) of this amino acid through betaine , which was likely an attempt to maintain methionine levels ( S1 and S2 Data ) . The 52 genes downregulated at day 3 were enriched for lipid metabolism , presumably to spare acetyl-CoA , and endothelial nitric oxide synthase ( eNOS ) signaling ( S2 Data ) . The 2 , 135 DEGs identified at day 6 enriched for pathways involved in cell signaling , cell cycle regulation , and inositol metabolism , which were driven by the upregulated genes ( S2 Data ) . The 1 , 071 downregulated genes enriched primarily for inhibition of cholesterol biosynthesis , which is in line with the suppression of fat metabolism initiated at day 3 ( S2 Data ) . Because cell proliferation is affected at day 6 [4] and cholesterol has roles in membrane structures , inhibition of cholesterol biosynthesis—in addition to sparing acetyl-CoA—may be a response to loss of cell division . When mtDNA was fully depleted at day 9 , the 805 upregulated genes enriched for serine and glycine metabolism , as was recently reported by others [8 , 9] , and for methionine salvage through betaine . The use of betaine to recycle methionine , which is a folate-independent pathway , may reflect serine-associated folate being channeled to purine metabolism [9] . We also identified changes in tRNA charging , which suggests an attempt by the cell to preserve cytosolic protein synthesis ( S2 Data ) . Inhibition of cholesterol biosynthesis , as found at day 6 , was the top category identified with the 467 DEGs that were downregulated ( S2 Data ) . We found at day 9 that the degradation of several proteinogenic amino acids was inhibited and that the TCA cycle was suppressed ( S2 Data ) ; this is consistent with their utilization for protein synthesis rather than , for instance , supplying precursors for the TCA . IPA can also predict upstream regulators involved in driving the transcriptional programs identified . Activating transcription factor 4 ( ATF4 ) is a transcription factor recently linked to a mitochondrial stress response [13] and was predicted only when evaluating the genes that were upregulated under our experimental conditions , irrespective of the degree of mitochondrial dysfunction ( S2B Fig ) . Conversely , several upstream regulators were predicted to be associated with the downregulated genes , including tumor protein p53 ( TP53 ) , MYC , and peroxisome proliferator activated receptor alpha ( PPARα ) . The only gene consistently predicted to play a role in the inhibitory responses at all times was the major facilitator superfamily domain-containing protein 2a ( MFSD2A ) ( S2B Fig ) , which has been recently linked to fatty acid oxidation [14] . We previously performed a metabolomics analysis in DN-POLG cells at days 0 , 3 , 6 , and 9 and showed that many metabolites were changed during mtDNA depletion [4] . To gain more insights into the progressive remodeling of the metabolome as a function of mtDNA depletion , and to explore the relationship with the transcriptome changes , we used the metabolite data to identify the pathways that were enriched over time . We started by determining those metabolites that were statistically different at any given point relative to day 0 , using adjusted p ≤ 0 . 05 and an effect size of 1 . 15-fold ( for more information , see Methods ) . We found a total of 459 metabolites using these statistical criteria , of which 231 were significantly different at day 3 , 396 at day 6 , and 345 at day 9 ( S3A Fig and S3 Data ) ; common to all time points were 179 metabolites ( S3A Fig and S3 Data ) . We then performed pathway enrichment analysis using the 459 metabolites , which revealed the dynamic nature of the metabolic changes over time . For example , most pathways progressively enriched between days 3–9 , while some initiated at day 6 , and others decreased by day 9 ( S3B Fig ) . The top enriched pathways involved purine nucleotides and the superpathway of methionine degradation , which was also the most significantly enriched pathway across the experimental time course ( S3B Fig ) . The fact that methionine degradation was captured at the transcriptional level already at day 3 ( S1 and S2 Data ) and was also the highest significant metabolic pathway engaged over time revealed an unexpected connection between methionine metabolism and loss of mtDNA . This finding was consistent with the overall amino acid response identified from the transcriptome data . The metabolite analysis showed the engagement of both catabolic and biosynthetic amino acid pathways; a summary of the main pathways is schematically represented in Fig 1D . Many of enriched pathways for amino acid degradation involved those that can input into the TCA to make acetyl-CoA , like leucine , valine and lysine , or other intermediates such as malate , succinyl-CoA , or α-ketoglutarate ( Figs 1D and S3B ) . Biosynthesis of other amino acids—such as serine , cysteine , and glutamate—was also observed ( Figs 1D and S3B ) . Consistent with amino acid degradation , the urea cycle that recycles ammonia derived from amino acid catabolism was enriched; linked to it was the biosynthesis of citrulline ( S3B Fig ) . The degradation of putrescine , which can input into the TCA as succinate , was also identified ( S3B Fig ) ; this was in line with the transcriptome data ( S2 Data ) . It is noteworthy that the urea cycle provides ornithine , the precursor of putrescine , thus offering a constant supply of these metabolites in the DN-POLG cells . The urea cycle , while mostly connected with the liver , occurs partially in the kidneys [15] . Several ( although not all ) genes involved in this pathway are expressed in different tissues [16 , 17] . The identification of the urea cycle as enriched in HEK293 cells is likely a reflection of activation of components of the pathway to recycle ammonia , rather than the canonical liver urea cycle , under our experimental conditions . Also , increased degradation of choline—the precursor of betaine—and glycine/betaine metabolism were enriched ( S2 Data ) , which is in agreement with the RNA-seq findings that suggested that methionine levels were maintained through salvage pathways . Various examples of the relationship between the transcriptome and metabolic remodeling can be found in S3C–S3G Fig . We assumed that the changes found at day 3 would reveal the drivers of the global metabolic response to mtDNA depletion . To define those drivers , we ranked the relevance of the pathways based on the ones most significantly enriched at day 3 , focusing arbitrarily only on the ones with a p ≤ 10−7 . What we found were 3 main nodes that essentially centered around purines , the TCA , and redox reactions ( S3H Fig ) . The levels of some metabolites involved in these pathways are shown in Fig 1E . These data suggest , despite the lack of detectable changes in mitochondrial function , that the level of mtDNA depletion achieved at day 3 remodels metabolism in a way that prepares the cells to adjust nucleic acid metabolism ( transcription , DNA repair , and replication ) , cell cycle , protein translation , methylation reactions , and redox homeostasis . This analysis also revealed 6 pathways that were not significantly enriched at day 3 but that were identified at later time points ( S3B Fig ) . These pathways were associated with overt mitochondrial dysfunction and included pyrimidine ribonucleotide interconversion , biosynthesis of cysteine , glutathione , glutamine , and the polyamines spermidine and spermine ( S3B Fig ) . It was surprising that the biosynthesis of cysteine and glutathione was not engaged at day 3 , since mtDNA depletion was recently shown to induce serine biosynthesis ( also shown here , at day 3 p = 10−2; S3B Fig and Fig 1F ) , channeling 1C metabolism to cysteine and glutathione production through transsulfuration [8 , 9] . It is worth noting that serine is also involved in the formation of formyl-methionine by feeding into the mitochondrial folate cycle [1] . Formyl-methionine is the unique amino acid used to initiate translation of mtDNA-encoded proteins [18] . Despite significant loss of mtDNA at day 3 ( S4A Fig ) , levels of mtRNA transcripts were stable ( S4B Fig ) , and mtDNA-encoded proteins were not significantly affected [4] . Thus , we hypothesized that serine biosynthesis at day 3 serves to maintain mitochondrial protein translation and sustain organellar function; at later time points , it likely supports cysteine and glutathione production , as shown by others [8 , 9] . In agreement with this hypothesis , levels of formyl-methionine were higher at day 3 compared to days 6 or 9 ( Fig 1G ) , whereas that of cysteine followed the opposite trend ( Fig 1H ) . The reason why the serine biosynthetic pathway is activated upon mtDNA depletion remains unclear . Carbon units derived from folate-1C metabolism are used for the synthesis of purines and the generation of S-adenosyl-methionine ( SAM ) , which is considered the universal methyl donor for DNA , RNA , lipids , and proteins [19 , 20] . Levels of SAM are also influenced by polyamine synthesis , which uses decarboxylated SAM for the production of spermidine and spermine from putrescine , generating 5-methyl-thioadenosine ( MTA ) . MTA is recycled back into the methionine cycle through a salvage pathway that also produces adenine , thus feeding into the purine pool [21] . Interestingly , MTA has been shown to be the major source of de novo adenine in human cells [22] . Our transcriptomic and metabolic data suggest that the progressive mtDNA depletion achieved over 9 days significantly affects the methionine cycle in various ways , including ( i ) by channeling homocysteine to transsulforation , ( ii ) by increasing the utilization of betaine as a folate-independent methionine precursor , ( iii ) by promoting the degradation of methionine , and ( iv ) by altering polyamine synthesis and degradation that , in turn , affects MTA recycling ( Fig 2A ) . However , whether these changes impact the levels of SAM , influencing methylation reactions , remains unknown . We examined the metabolites associated with the methionine cycle ( Fig 2A ) and found that while homocysteine levels decreased over time ( Fig 2B ) , levels of methionine ( Fig 1E ) , serine ( Fig 1F ) , glycine ( Fig 2B ) , and cysteine ( Fig 1H ) increased . Choline ( Fig 2B ) , betaine , SAM , and MTA levels were maximal at day 6 , returning to levels closer to basal at day 9 ( Fig 2B ) . Levels of S-adenosyl-homocysteine ( SAH ) , the byproduct of SAM metabolism , increased at day 6 and decreased at day 9 below basal levels ( Fig 2B ) . A high SAM/SAH ratio is favorable to methylation reactions since SAH inhibits the methyltransferases [10 , 23] . Steady state levels of the polyamines putrescine , spermidine , and spermine followed an interesting trend . While putrescine decreased by day 6 and increased by day 9 ( Fig 1E ) , the levels of spermidine and spermine decreased over time ( Fig 2B ) . This effect on the steady state levels of the polyamines is also reflective of an increased catabolism of spermine and spermidine through spermine/spermidine N-acetyl-transferase ( SAT1 ) , which is upregulated at the transcriptional level in the DN-POLG ( S1 Data ) and whose net product is putrescine [24] . Since previous observations that DNA methylation is influenced by mtDNA depletion and mitochondrial dysfunction in cultured cells and animal models [2 , 3] , we hypothesized that the changes in SAM we observed could drive this effect . Specifically , we predicted that the DNA would be hypermethylated , with maximal levels at day 6 . To test this hypothesis , we evaluated whole genome DNA methylation status at a single nucleotide resolution using the Illumina 450K platform . We found that mtDNA depletion progressively increased DNA methylation in promoters , gene bodies , or intergenic regions ( S5A Fig ) , with hypermethylation peaking at day 6 and decreasing at day 9 ( Fig 2C ) . Although the changes we detected were somewhat modest ( full range of Δ%mCG: −30% to +40%; see Fig 2C ) we reasoned they reflected the short time frame of the experiments . Indeed , when evaluating DNA methylation using the same approach in cells chronically depleted of mtDNA ( rho0 ) in the 143B background , we found that methylation changes were more prominent , ranging between −60% and +60% with respect to cells with endogenous mtDNA levels ( rho+ ) in the same 143B background ( S5B Fig ) . The increased methylation of the DNA is consistent with the increased levels of SAM and with the kinetics of availability of SAM/SAH amounts over time . However , changes in other TCA metabolites could also play a role in this phenotype . For example , α-ketoglutarate is a cofactor of the Ten-eleven translocation ( TET ) enzymes , which are involved in the DNA demethylation reactions . Also , succinate , fumarate , and 2-hydroglutarate ( 2-HG ) can compete with α-ketoglutarate in the active site of the TETs , inhibiting their function [25] . Thus , decreased α-ketoglutarate , increased succinate , fumarate , and/or 2-HG could also lead to hypermethylation of the DNA . However , no changes in the levels of α-ketoglutarate were observed ( S3 Data ) , and no increases in the succinate or fumarate to α-ketoglutarate ratios were identified over the time course of the experiments ( Fig 2D ) . Despite the fact that 2-HG increased as mtDNA was depleted , only a small change was observed at day 6 , and maximal accumulation was observed at day 9 ( Fig 2E ) , which is inconsistent with the kinetics of DNA hypermethylation ( Fig 2C ) . Levels of methylated cytosines ( 5meC ) were increased , while no changes in the levels of 5-hydroxy-methyl-cytosine ( 5hmeC ) —the product of TET reaction—were identified in cells chronically depleted of mtDNA ( S5C and S5D Fig ) . We also showed enhanced DNA methyltransferase ( DNMT ) activity ( Fig 2F ) . Collectively , these data are in support of DNA hypermethylation resulting from increased DNA methylation and not from inhibition of the demethylases . In order to determine whether the changes in global methylation influenced gene expression , we cross-referenced the coordinates of the promoters differentially methylated at days 3 , 6 , or 9 with those of the DEGs . We found that 1 , 627 ( approximately 57% ) of the DEGs showed significant alterations in their promoter methylation when compared to day 0 ( S4 Data ) . The number of differentially methylated DEGs increased over time from 63 at day 3 ( 27% ) , 978 ( 46% ) at day 6 , and 879 ( 70% ) at day 9 ( S5E Fig ) . The odds ratio ( OR ) of a gene being differentially expressed and having a change in its promoter methylation was OR = 0 . 81 , p < 0 . 01 ( S5F Fig ) , suggesting that incidence of promoter DNA methylation changes is different for DEGs and genes not differentially expressed . To better understand the relationship between differential methylation , gene expression , and mitochondrial dysfunction , we performed IPA on the DEGs that were differentially methylated . This analysis revealed that genes involved in key pathways that responded to mtDNA depletion were targets of differential methylation . For instance , at day 3 , the 63 differentially methylated and expressed genes enriched for methionine degradation; at day 6 , for cholesterol biosynthesis; and at day 9 , for the metabolism of several amino acids , cholesterol , and the TCA ( S5 Data ) . Similar findings were observed when evaluating the 143B rho0 cells chronically depleted of mtDNA that also showed hypermethylation of the DNA . In those cells , 621 DEGs were also differentially methylated ( S6 Data ) and enriched for pathways involved , for instance , in folate transformations ( S5G Fig ) . While DNA methylation is not the only parameter governing gene expression , we attempted to define the level of concordance between the changes in DNA methylation status over time with the directionality of expression of the DEGs harboring those changes . Whether we combined the entire methylation profile of genes or considered only promoter marks , the concordance ranged from 30%–50% over the 9 days of mtDNA depletion ( S5H Fig ) . Taken together , these findings suggest a correlation between DNA methylation changes and the expression of a fraction of DEGs responding to progressive mitochondrial dysfunction . It is possible that the mechanism connecting mtDNA depletion to SAM and DNA hypermethylation involves serine biosynthesis and 1C-folate remodeling , which in turn can affect the methionine cycle [8 , 9] . While this is feasible , the fact that choline/betaine are engaged in maintaining methionine salvage independent of folate would argue against this possibility . Alternatively , the methionine cycle may be directly affected by mtDNA depletion through changes in both methionine and polyamine metabolism . These molecules are not only linked in the regulation of SAM levels [10] , but they can provide intermediates such as pyruvate , succinyl-CoA ( a precursor of succinate ) , and succinate to the TCA in their catabolic pathways . An increase in their degradation to feed the TCA could set a cascade of compensatory changes that impacts the SAM pool . To test this hypothesis , we took advantage of the DN-POLG cells overexpressing NDI1/AOX , which are cells that have the ability to oxidize NADH and maintain TCA flux despite the complete loss of mtDNA [4] . We reasoned that if the methionine cycle is directly impacted by the TCA , in these cells methionine-associated intermediates should not be changed . We reanalyzed the metabolomics data that we previously generated with the NDI1/AOX cells [4] using the same criteria as for the DN-POLG cells ( S3 Data ) . We then focused on the intermediates associated with the methionine , serine , folate , and polyamine pathways . We found that in the NDI1/AOX cells , the levels of SAM , SAH , MTA , and the polyamines were maintained over time ( Fig 3A ) ; the levels of serine , cysteine , methionine , betaine , choline , and folate followed the same pattern as was observed with the DN-POLG cells ( compare Figs 3A and 1E–1G ) . Most notably , levels of succinate , which were increased at day 9 in the DN-POLG , were decreased in the NDI1/AOX cells ( Fig 3B ) . Taken together , these results support the hypothesis that polyamine and methionine metabolism are directly responding to changes in TCA flux , likely as contributors of succinate . Furthermore , these data suggest that serine biosynthesis and folate-1C remodeling caused by mtDNA depletion are not responding to changes in NADH oxidation or TCA flux . We also evaluated whole genome methylation using the Illumina 450K platform in NDI1/AOX cells . We used cells at days 0 and 9 , since we gauged that mtDNA would be fully depleted at this latter time and would provide the largest effect . Remarkably , no significant changes in DNA methylation were observed in the cells expressing NDI1/AOX , despite complete loss of mtDNA ( Fig 3C and 3D ) . We then focused specifically on the coordinates of the 1 , 626 DEGs that were differentially methylated in the DN-POLG cells at day 9 ( S5A Fig ) . However , we found that average DNA methylation change in those sites was only approximately 2% in the NDI1/AOX cells ( Fig 3E ) . Hence , we conclude that changes in polyamine synthesis and the MTA salvage pathway , which in turn affect SAM levels , seem to be critical for differential DNA methylation in the nucleus of DN-POLG cells . We performed gene expression analysis in the NDI1/AOX cells using microarrays in order to determine whether the promoter methylation status has the potential to impact the differential expression of the 879 genes identified in the DN-POLG cells at day 9 . Unexpectedly , we found no significant DEGs in the NDI1/AOX cells between days 0 and 9 when adjusting for false discovery rate ( FDR; S7 Data ) . Relaxing statistical thresholds based on pairwise comparisons without multiple testing corrections revealed 23 genes that were differentially expressed between days 0 and 9 ( S6 Data ) , 4 of which were also differentially expressed in the DN-POLG at day 9 , as gauged by RNA-seq . To rule out that these results were due to a lack of sensitivity of microarrays to detect the relatively small changes in gene expression identified by RNA-seq , we performed microarrays in DN-POLG cells at days 0 and 9 . We found 1 , 408 genes with adjusted p ≤ 0 . 05 that were differentially expressed between days 0 and 9 in this cellular background ( S7 Data ) . These results indicate that it is the maintenance of NADH oxidation in the mitochondria , in the context of mtDNA depletion , that prevents the differential expression of genes . To better understand the effects of NDI1/AOX expression in the presence of mtDNA , we next compared the microarray data from DN-POLG cells with those from NDI1/AOX cells at day 0 . Again , no DEGs were detected when adjusting for FDR . Using unadjusted p-values , we found 842 genes that were differently expressed between the 2 cell types at day 0 ( S8 Data ) . However , Kyoto Encyclopedia of Genes and Genomes ( KEGG ) pathway analysis identified little to no overlap to the findings obtained when utilizing the DEGs identified in the DN-POLG when mtDNA was depleted ( S8 Data ) . Thus , we conclude that expression of NDI1/AOX does not cause significant off-target effects . Nevertheless , the maintenance of NADH oxidation provided by these enzymes is sufficient to prevent the DNA methylation and transcriptomic changes that result from mtDNA depletion , independent of mitochondrial ATP production or the ΔΨm , which were not rescued by NDI1/AOX expression [4] .
Our understanding of how changes in mitochondrial function can impact the epigenetic control of gene expression in the nucleus is still incomplete . Despite the fact that mitochondrial dysfunction has been shown to affect histone modifications and DNA methylation , mechanistic links between these processes have not been elucidated , particularly in terms of methylation reactions . Earlier studies proposed a prominent role for ROS or 2-HG as inhibitors of the DNA or histone demethylases [26–29] . However , a direct demonstration that the demethylases are inhibited as mitochondria become dysfunctional is still lacking . In this study , we used a novel cell culture system of progressive mtDNA depletion , an isogenic counterpart cell line that was engineered to maintain NADH oxidation , despite loss of mtDNA , and a widely used cell line that is chronically depleted of mtDNA to demonstrate that ( i ) the methionine cycle responds to loss of TCA function; ( ii ) salvage pathways of methionine , including through MTA , are engaged in the context of mtDNA loss; ( iii ) DNA hypermethylation is associated with higher SAM concentrations , 5meC levels , and DNMT activity; ( iv ) changes in DNA methylation occur predominantly in genes differentially expressed as a result of mtDNA depletion; and ( v ) genes involved in key pathways responding to mtDNA depletion are targets of differential methylation . Collectively , these findings provide new mechanistic insights that connect mitochondrial function and epigenetics in a way that is likely to have broader relevance to health and disease . In view of their potential impact , further studies to validate and explore these findings in different cell types and in vivo are warranted . Our transcriptomic analysis revealed a dynamic relationship between the loss of mtDNA and the genes that respond to the resulting mitochondrial dysfunction . Our results confirm the serine response that was recently reported by others [8 , 9 , 13] , but we found that it involves a series of additional amino acids , including methionine . We also identified that inhibition of fat metabolism , perhaps as an additional means of sparing acetyl-CoA , started early in the progression of mitochondrial dysfunction . The identification of methionine degradation as an early response to mtDNA depletion was unexpected . To our knowledge , no direct link between these processes have been previously reported . Our data with the NDI1/AOX cells clearly suggest that resuming TCA flux can turn off the methionine response involving the salvage pathway through MTA . Methionine salvage from MTA can also contribute to the generation of α-ketoglutarate , and because it is intimately linked to polyamine synthesis , where putrescine can generate succinate , we propose a model in which the methionine cycle responds to mtDNA depletion based on changes in TCA intermediates ( Fig 3F ) . At the same time , MTA can also contribute to the purine pool , whose imbalance seems to be an early response to mtDNA loss , perhaps as an additional means to maintain homeostasis . It had been previously shown that , at least in cancer cells , serine contributes to SAM , DNA , and RNA methylation by de novo ATP synthesis [30] . However , maintenance of TCA flux in the NDI1/AOX cells had no impact on serine biosynthesis under our experimental conditions , which rules out that serine is limiting for SAM levels under conditions of mtDNA depletion . It is currently unclear how ( and whether it is that ) changes in flux through the TCA cycle or changes in the levels of particular TCA metabolites are sensed outside of the mitochondria . Given that acetyl-CoA is an important intermediate of the TCA cycle , which is used both for biosynthetic purposes and for posttranslational protein modifications [31 , 32] , it is possible that its levels are sensed by other parts of the cell . Changes in these levels initiate an entire cascade to ultimately preserve a level of acetyl-CoA that is compatible with maintenance of key cellular functions . We suggest that a sensitive but yet-unidentified pathway that senses and regulates TCA intermediates , such as acetyl-CoA ( or flux ) , within the mitochondria must exist and efficiently communicate to the rest of the cell . The activation of serine biosynthesis and the remodeling of mitochondrial folate and 1C metabolism toward transsulfuration to produce cysteine and glutathione have recently been the subject of various studies . It was shown that this pathway is consistently engaged upon in vitro and in vivo mtDNA depletion , by the inhibition of the ETC with agents such as rotenone or antimycin C , or by compounds that alter protein homeostasis [8 , 9 , 13 , 33] . Our data revealed that the remodeling of 1C metabolism toward transsulfuration is a response to overt mitochondrial dysfunction but does not take place when the organelle is still able to maintain ETC function . It remains unclear why the mitochondrial folate pool and serine biosynthesis are engaged upon mitochondrial dysfunction , although it has recently been shown that mammalian target of rapamycin ( mTOR ) and the transcription factor ATF4 are involved in these processes [8 , 13 , 33] . While we envision that alterations in 1C metabolism can effectively alter nucleotide pools , redox , and methylation reactions—thus potentially impacting cell cycle , transcription , replication , and signaling concomitantly—the exact signal that arises from mitochondria remains to be identified . It has been proposed that ATF4-dependent serine biosynthesis arises from oxidative stress due to a stalled respiratory chain [8] . However , our data do not support this hypothesis , since we found no changes in respiratory function at day 3 [4] and , most importantly , that maintenance of NADH oxidation in the NDI1/AOX cells does not turn off the serine biosynthesis response . Further studies will be required to resolve this issue . Our finding that there is an extensive cellular metabolic rewiring associated with mitochondrial dysfunction centered on amino acid and lipid metabolism was not fully surprising . What was unexpected was that the maintenance of NADH oxidation in NDI1/AOX cells prevented , most significantly , the changes in methionine metabolism and polyamine synthesis . To our knowledge , this is the first report that directly connects these pathways to mitochondrial function . The roles of polyamines in cell biology are still poorly understood and are linked to effects on cell proliferation , chromatin configuration , gene transcription , and even mitochondrial calcium homeostasis [34 , 35] . Whether the changes in polyamine levels we identified to be associated with mitochondrial dysfunction are sufficient to affect any of these processes requires further studies . It is worth noting that a mouse completely deficient in spermine synthase activity was identified in a cohort of female irradiated offspring [36 , 37] . The complete loss of polyamines is embryonic lethal in vivo [38] . Most interestingly , these mice have many phenotypes that resemble mitochondrial diseases , including deafness , sterility , neurological abnormalities , and reduced life span [39 , 40] , which supports a potential link between polyamine synthesis and mitochondrial health . Finally , our data revealed that many of the genes that are differentially expressed in response to mtDNA depletion are also differentially methylated . Moreover , we showed these changes in methylation and gene expression can be prevented by maintaining NADH oxidation in the NDI1/AOX cells . These findings support the notion that the epigenetic changes caused by mtDNA depletion are intimately associated with the differential expression of genes in the DN-POLG cells . It is possible that posttranscriptional modifications of specific proteins , and not transcriptional changes of specific genes , account for the lack of differential gene expression in the cells overexpressing the NDI1/AOX transgenes . However , we think this is unlikely to be the case . Alternatively , it can be argued that it is the metabolic rescue provided by NADH oxidation in the mitochondria that is directly responsible for turning off the transcriptional response in these cells . Given the continued activation of the metabolism of serine , folates , and others , despite maintenance of TCA flux , we do not favor this possibility . More studies are required to better address these issues . The remarkable parallels between our in vitro results and the data obtained with in vivo mouse models and patient samples of mitochondrial disorders [9 , 33] suggest that our findings may be relevant to human health . In fact , careful analysis of the metabolic data from heart and muscle of the Deletor mouse strain indicate that the methionine salvage pathway and polyamine synthesis are altered based on increased steady state levels of choline , betaine , ornithine , and MTA ( S6 Fig ) [9] . Similar findings were observed in the liver of another mouse model of mtDNA abnormalities driven by a thymidine kinase mutation [41] in which MTA and adenosine levels are higher than wild-type controls ( S6 Fig ) . However , whether the DNA is also hypermethylated in those models and which genes may be affected by it remain to be addressed . It also remains to be determined the extent to which the flux from polyamines to the methionine cycle end up in methylation reactions and whether these changes are drivers or contributors of the overall response to mtDNA depletion . It is also unclear whether these same effects occur in the context of other types of mitochondrial dysfunction . This will be especially important for studies to reveal how environmental toxicants that target the mitochondria change the biology of the cell . Irrespective of these limitations , our findings have the potential to fundamentally change our understanding about the role and impact of mitochondrial metabolism in health and disease .
HEK293T cells carrying a tetracycline ( Tet ) -on inducible DN-POLG from [42] were used to generate derivatives also ectopically expressing AOX and NDI1 and cultured as described previously [4] . The osteosarcoma cell line 143B and its rho0 derivative , graciously obtained from Dr . Eric Schon at Columbia University , were routinely grown in DMEM high glucose ( 4 . 5 g/L ) supplemented with 10 mM pyruvate , 50 μg/mL of uridine , 10% FBS , and 1% penicillin/streptomycin under 37°C and 5% CO2 . Except for ChIP-seq experiments ( N = 2 ) all experiments were performed on N = 3 independent biological replicates . RNA was extracted from 3 independent cell cultures of DN-POLG cells at days 0 , 3 , 6 , and 9 using RNAeasy Mini and QIAshredder kits ( QIAGEN ) and was used for both RNA-seq and microarrays; RNA from NDI1/AOX cells was obtained at days 0 and 9 and used for microarrays only . In all cases , samples from 3 independent experiments were collected ( N = 3 per time point per cell model ) . DNMT activity was assayed using radioactive filter-binding assay , as previously described [43] . Briefly , 143B cells from rho+ or rho0 cells were lysed and the nuclear fraction enriched using differential centrifugation . Then , cell lysates were used to monitor the incorporation of tritiated ( 3H ) methyl groups into a poly-IC duplex DNA oligonucleotide . The unreacted ( methyl-3H ) was separated from the radiolabeled DNA using filter binding . The 3H–CH3-containing duplex DNA was then quantified by liquid scintillation . Data were normalized to protein content and presented relative to the detected activity in rho+ cells . Samples from 3 independent replicates were collected ( N = 3 per 143B derivative ) . RNA from DN-POLG cells at days 0 , 3 , 6 , and 9 ( N = 3 each timepoint ) was poly-A-selected and sequenced with a HiSeq 2000 system ( Illumina ) . Following 3′ adapter trimming and base-calling filtering ( phred score > 20 ) , we obtained approximately 100 million 126-nt paired-end reads per individual sample ( 7–8 flow cell lanes/sample ) , which were aligned to the hg19 human reference genome ( Genome Reference Consortium GRCh37 from February 2009 ) [44] with TopHat-Fusion function [45] . Composite RPKM counts within genomic coordinates of 20 , 304 nonhaplotype HGNC-annotated genes were used to calculate gene expression differences based on log2-transformed fold-change ( log2FC ) relative to average gene RPKM at day 0 at a significance level p < 0 . 05 adjusted for multiple comparisons [46] . DEGs were detected using weighed two-way ANOVA ( gene × time ) of log2-transformed expression fold change measurements with respect to the average composite RPKM at day 0 ( log2FC ) ; N = 12 ( 3 biological replicates per time point ) . Gene-wise log2FC values were weighed by a relative metric of sequencing representation ( cumulative hazard of significance scores from gene-wise RPKM rate modeling with an exponential distribution and inverse link function ) . A total 2 , 854 HGNC-annotated DEGs were detected in DN-POLG cells at a significance level p < 0 . 05 adjusted for multiple comparisons [46] , filtering against a minimum gene-wise effect size δlog2FC > 0 . 3 × σlog2FC , and post hoc pairwise significance ( Student t test p < 0 . 05 ) between log2FC values at days 3 , 6 , or 9 versus day 0 . For gene-level effect size filtering , δlog2FC = 0 . 3 × σSSR is 5% of the 6σ-spread log2FC regression error with respect to a gene’s grand mean ( where [σSSR]2 = [SSRlog2FC] / [N– 1] ) compared to 5% of the 6σ-spread in measurement error about the mean log2FC at each time point in the gene ( where [σlog2FC]2 = [SSElog2FC] / [N-1] ) . For microarrays analysis of gene expression , the Affymetrix Human Genome U133 Plus 2 . 0 GeneChip arrays were used . Samples were prepared as per manufacturer’s instructions . Arrays were scanned in an Affymetrix Scanner 3000 and data were obtained using the GeneChip Command Console and Expression Console Software ( AGCC , Version 3 . 2; Expression Console , Version 1 . 2 ) using the MAS5 algorithm to generate CHP-extension files . ANOVA was used to identify statistical differences between means of groups at α < 0 . 05 level among HG-U133 Plus 2 . 0 probe sets unambiguously mapped to UCSC known gene transcripts . Differentially enriched metabolites were detected for DN-POLG and NDI1/AOX cells separately using two-way ANOVA ( metabolite × time ) of log2-transformed relative changes in abundance versus untreated cells ( log2RC ) ; N = 16 ( 4 biological replicates per time point in each DN-POLG and NDI1/AOX ) ; refer to previously published original data elsewhere [4] . Data with significance level p < 0 . 05 adjusted for multiple comparisons [46] were then filtered against minimum effect size δlog2RC ≥ 0 . 3 × σlog2RC = 0 . 20 ( approximately 1 . 15-fold change ) . The δlog2RC corresponds to the smallest estimate between DN-POLG and NDI1/AOX cells of metabolome-wide effects at 5% of the 6σ-spread in log2RC measurement error across all metabolite × time groups ( where [σlog2RC]2 = [SSElog2RC] / [N– 1] ) . Genomic DNA was extracted from 3 independent cell cultures of DN-POLG cells at days 0 , 3 , 6 , and 9 and NDI1/AOX cells at days 0 and 9 and bisulfite-converted using an EZ DNA Methylation kit ( Zymo Research ) following the manufacturer’s protocol . Differential methylation at the CpG dinucleotide level was conducted using Human Methylation450 v1 BeadChip arrays ( Illumina ) following the InfiniumHD methylation protocol . Data were obtained using Illumina’s GenomeStudio software ( version 2011 . 1 ) using no background subtraction and no normalization parameters . Probes in a probe × cell × time block with >1 failed reads or >1 outliers ( 1 . 5 IQR rule on residuals around probe × cell × time sample means ) were discarded from analysis . Probe-level groups with N = 2 after failed read or outlier filtering were brought to N = 3 by substitution with probe × cell × time trimmed mean values adjusted by imputed array-wise residual estimates using the pairwise correlation matrix of cell × time statistical groups . Probe methylation percentage was quantified from fluorometric signal intensities of methylation ( mCG ) and unmethylation ( CG ) in terms of ß = [mCG/ ( mCG+CG ) ] × 100 . ANOVA was used to identify statistical differences between the means of groups at a significance level p < 0 . 05 adjusted for multiple comparisons [46] using JMP software ( Version 11 ) followed by post hoc pairwise significance testing ( p < 0 . 05 ) with respect to day 0 in DN-POLG or NDI1/AOX cells .
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Epigenetic changes in the nucleus play a role in the regulation of gene expression , and metabolism has been shown to affect the epigenome . As mitochondria are not only the powerhouses but also important metabolic hubs in cells , changes in mitochondrial metabolism are likely to affect the epigenome and , as such , gene expression . However , it remains unclear whether mitochondrial function can affect epigenetics , and if such effects alter gene expression . In this work , we used cell culture systems in which mitochondrial function was genetically manipulated to simultaneously study the effects on metabolism , the epigenome , and gene expression . Such approach revealed that loss of mitochondrial respiration leads to a cell-wide metabolic rewiring primarily centered on amino acids , which altered DNA methylation in the nucleus by affecting methionine and polyamine metabolism . We found that these changes preferentially occur in genes responding to mitochondrial dysfunction . Most notably , all these effects could be reversed by maintaining nicotinamide adenine dinucleotide reduced ( NADH ) oxidation in the mitochondria , revealing a novel link between these organelles and DNA methylation . Given the involvement of mitochondria in many disease conditions , this work opens new challenges and opportunities to understand and potentially manipulate mitochondrial function in health and disease .
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2018
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Mitochondrial nicotinamide adenine dinucleotide reduced (NADH) oxidation links the tricarboxylic acid (TCA) cycle with methionine metabolism and nuclear DNA methylation
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The progression of viral infections is notoriously difficult to follow in whole organisms . The small , transparent zebrafish larva constitutes a valuable system to study how pathogens spread . We describe here the course of infection of zebrafish early larvae with a heat-adapted variant of the Infectious Hematopoietic Necrosis Virus ( IHNV ) , a rhabdovirus that represents an important threat to the salmonid culture industry . When incubated at 24°C , a permissive temperature for virus replication , larvae infected by intravenous injection died within three to four days . Macroscopic signs of infection followed a highly predictable course , with a slowdown then arrest of blood flow despite continuing heartbeat , followed by a loss of reactivity to touch and ultimately by death . Using whole-mount in situ hybridization , patterns of infection were imaged in whole larvae . The first infected cells were detectable as early as 6 hours post infection , and a steady increase in infected cell number and staining intensity occurred with time . Venous endothelium appeared as a primary target of infection , as could be confirmed in fli1:GFP transgenic larvae by live imaging and immunohistochemistry . Disruption of the first vessels took place before arrest of blood circulation , and hemorrhages could be observed in various places . Our data suggest that infection spread from the damaged vessels to underlying tissue . By shifting infected fish to a temperature of 28°C that is non-permissive for viral propagation , it was possible to establish when virus-generated damage became irreversible . This stage was reached many hours before any detectable induction of the host response . Zebrafish larvae infected with IHNV constitute a vertebrate model of an hemorrhagic viral disease . This tractable system will allow the in vivo dissection of host-virus interactions at the whole organism scale , a feature unrivalled by other vertebrate models .
It is often quite difficult to locate viral infections , as viruses are invisible to the light microscope and are generally noticed by the relatively non-specific symptoms they cause . Specific tools such as monoclonal antibodies allow their detection with techniques that cannot be carried out at the whole-body scale using classical virology models such as rodents . Therefore , important reservoir organs may pass unnoticed and the mechanisms of viral dissemination are hard to establish . The development of systems that allow the detection of viruses in entire animals would help understanding how antiviral treatments or host resistance factors contribute to curb viral infections . They would be especially valuable to assess differential tissue-specific impacts of antiviral responses and treatments . The zebrafish Danio rerio ( Hamilton ) , a well-known model of developmental biologists , is now also turning into a prominent model for the study of host-pathogen interactions [1] . Zebrafish larvae provide a remarkable compromise between ease of imaging , genetic tractability , and homology with human genes and cell types . Their transparency and small size offer a unique possibility to image a whole vertebrate , at medium resolution such that individual cells can be distinguished , or to focus on organ-sized regions where subcellular details can be resolved , using both fluorescence and differential interference contrast ( DIC ) microscopy . Larvae are easy to anesthetize and can be kept under the microscope for hours or even days . They still lack an adaptative immune response – acquired only at the juvenile stage , by 4–6 weeks of age [2] - but already harbor a powerful innate immune system , with macrophages [3] and neutrophils [4] being the major effector cells . In addition , the zebrafish genome is almost fully known , and overexpression or knockdown of targeted genes in early larvae can readily be achieved in vivo by injection at the one-cell stage of synthetic mRNA or antisense morpholino oligonucleotides , respectively . Innate antiviral defenses of teleost fish share many similarities with those of mammals , including the role of interferons as the main orchestrating cytokines [5] . Although no natural virus of the zebrafish is known so far , several viruses from other fish species have been used to experimentally infect zebrafish , including Spring Viraemia of Carp Virus ( SVCV ) [6] , [7] , [8] , Snakehead Rhabdovirus ( SHRV ) [9] , Infectious Hematopoietic Necrosis Virus ( IHNV ) [10] , [11] , Infectious Pancreatic Necrosis Virus ( IPNV ) [10] , Viral Hemorrhagic Septicemia Virus ( VHSV ) [12] , Nervous Necrosis Virus ( NNV ) [13] and Infectious Spleen and Kidney Virus ( ISKNV ) [14] . To fully exploit the genetic and optical assets of zebrafish , we are mostly interested in viruses that can infect early larvae within their normal temperature range ( 22–32°C ) and yield highly reproducible clinical signs within a convenient time frame . Zebrafish larvae challenged with SHRV by bath [9] or injected with SVCV [6] or with NNV [13] succumbed readily , within less than 36 hours , making it very difficult to identify conditions that could accelerate the course of infection . Bath challenge with SVCV results in slower kinetics [7] but with high inter-individual variation for onset time of infection signs ( JPL , unpublished observations ) , with only a fraction of fish being infected ( as for SHRV ) , complicating comparisons between treatment groups . In contrast , we found that inoculation of zebrafish with a heat-adapted IHNV resulted in highly reproducible infection courses with convenient kinetics [11] , making it the most tractable system to identify the virus target tissues and compare infection spreading in various conditions . We therefore selected it for further analysis . IHNV is a rhabdovirus first isolated from Pacific salmons in the west coast of North America in the 1950's and later also found in Europe and Asia [15] . It can infect various species of salmonids in the wild , and outbreaks in fish farms represent a significant threat to the salmonid culture industry . In susceptible salmonids , most organs appear to be potential targets of the virus , although according to initial histological examinations , hematopoietic tissues were recognized to be more specifically damaged than others , hence the designation of the virus [16] . Whereas histochemical studies have suggested that leukocytes and endothelium are primary sites of infection [17] , the use of a recombinant virus expressing luciferase has revealed the base of the fins to be the entry site of the virus in waterborne-challenged juvenile rainbow trouts [18] . In early experiments performed with adult zebrafish at an unreported temperature , no infection with IHNV could be observed upon bath infection , but intraperitoneal injections resulted in transient viremia and depletion of erythrocyte precursors [10] . However , as IHNV is a cold water virus that normally hardly replicates above 18°C , the tropical zebrafish is not naturally susceptible to the virus; although adult zebrafish may tolerate water temperature below 20°C , larvae do not . We have avoided this problem by using a variant of IHNV that has been adapted to growth at higher temperatures , upon serial in vitro passaging on EPC cells at progressively increasing temperatures [11] . The strain used , IHNV25 . 70 ( hereby referred to as IHNV25 ) can replicate at up to 25°C . We describe here the outcome of the infection of zebrafish larvae with IHNV25 at 24°C . Prominent clinical signs include slowdown and stop of blood flow , loss of reactivity , hemorrhages and edemas , with death occurring within three to four days . This is accompanied by a continuous rise in virus titer . Patterns of infection in entire larvae could be established using whole-mount in situ hybridization ( WISH ) and whole-mount immunohistochemistry ( WIHC ) . Early virus staining coincided with the major blood vessels . Using transgenic reporter zebrafish , infection and loss of endothelial cells were demonstrated , which may explain much of the observed pathogenesis . By shifting the larvae to a temperature of 28°C , non-permissive for viral replication , we found that a critical threshold resulting in irreversible damage was reached in less than a day , before the first visible clinical signs appeared . This was also found to occur before the onset of a detectable host response in terms of gene expression .
We previously reported that zebrafish larvae were susceptible to intravenous ( iv ) infection with the IHNV25 strain when incubated at 24°C [11] . We studied the clinical signs of infection in more detail . Zebrafish larvae aged ∼72 hours post fertilization ( hpf ) were injected iv with 60 to 120 plaque forming units ( pfu ) of IHNV25 in the enlarged venous plexus located posteriorly to the urogenital opening ( Figure 1A ) . They were then incubated individually in 24-well plates at 24°C and monitored at regular intervals under the dissecting scope . During the first 30 hours post infection ( hpi ) , larvae appeared to be clinically healthy . Then the blood flow started to slow down , until it stopped completely , often first in the tail , then in the entire body , by approximately 48 hpi ( Figure 1B ) . This qualitative observation could be confirmed by quantitative assessment of blood speed ( Figure S1 in Text S1 ) . This was not due to an arrest of the heart , which continued to beat , although more weakly . Larvae then gradually lost reactivity , with progressively weaker reaction upon gentle pricking , until they became completely inert . Death - defined by complete absence of movement , including any residual heartbeat , and readily followed by decomposition - occurred for all the fish , generally between 65 and 96 hpi . For subsequent experiments , and to facilitate future studies that will assay in vivo susceptibility to IHNV , we defined a simple clinical score from 0 to 3 , based on these signs of infection that can be easily scored without anesthesia of larvae: loss of blood flow in the tail , loss of reactivity to touch , and death ( see material and methods ) . As illustrated on Figure 1B , these criteria define three progressive steps of pathogenesis which were translated into scores providing richer information than endpoint mortality . Inoculations of varying doses of virus yielded a clear dose-dependent response ( Figure 1C ) ; however , even if kinetics were slowed down at lower doses , signs occurred in a similar order . The 50% lethal dose over 7 days was quite low , inferior to 10 pfu . The dose of 100 pfu , however , was kept as the standard inoculum for further experiments , because it yields less inter-individual variation . Other signs of infection were frequently observed , although not as consistently as the previous ones . When blood started slowing down , accumulation of erythrocytes could often be observed in various places , such as around an eye ( Figure 1D ) , in the duct of Cuvier just upstream of the heart , on the top of the head , or in the caudal venous plexus ( not shown ) . Although it was difficult to discern whether this resulted from vessel leakage or from accumulation inside a vessel , some cases clearly resulted from hemorrhage , as when erythrocytes were observed inside the pericardial cavity ( Figure 1E ) . Skin damage was also frequently seen , especially along the lateral midline of the trunk and on the ventral side of the yolk ball . Edemas were also commonly observed , affecting mostly the pericardial cavity and the head . At late stages , necrotic foci were often visible in the brain ( not shown ) . In order to better understand the course of IHNV infection in this system , we assessed the spread of the virus over time by different quantitative methods . Firstly , the numbers of infectious virions were measured by plaque assays on monolayers of EPC cells . A few dozens particles were detectable by 6 hpi; then , near-exponential growth was found ( Figure 2A ) , providing definitive evidence for functional viral replication in zebrafish . At 48 hpi , up to one million pfu per larva were found . Since a 5dpf zebrafish larva weighs about a 0 . 5 mg [19] , this translates to viral concentrations in the order of 109 pfu/g . Secondly , we measured the expression of a viral mRNA transcript by qRT-PCR on whole larvae , choosing the N gene as the most highly expressed viral gene [20] . Increases of N-IHNV gene expression paralleled the rise of viral titers ( Figure 2B ) . Thirdly , we quantified viral negative and positive genomic strands ( genome plus antigenome ) by qRT-PCR; predictably , levels were lower than for the N transcript but progression was comparable ( Figure 2B ) . Finally , the spatial distribution of infected cells was determined by WISH with a probe complementary to the N gene . Stained cells could be detected in infected larvae at least as early as 6 hpi ( Figure 2C ) , and their number increased then steadily over time , in accordance with our previous quantifications . The distribution of infected cells was variable from larva to larva , but some common patterns were observed . Early infection was almost systematically detected at the location of the main veins at this developmental stage [21]: in the tail , the cardinal vein; in the head , the dorsal longitudinal vein , posterior cerebral vein , primary head sinus , and inner optic circle; in the anterior ventral region , the duct of Cuvier . A few infected cells were also systematically detected in the heart . Observation of larvae fixed at 12–24 hpi points revealed a more intense staining in all these areas; examination of stained larvae at higher magnification suggested a spread from endothelium to adjacent cell layers ( Figure 2D ) . At 48 hpi the strongest staining was systematically observed in the branchial arches ( Figure 2C ) . WISH patterns suggested that the vascular endothelium was a primary target of IHNV . To ascertain this we infected fli1:GFP transgenic larvae , which express GFP in all endothelial cells [22] . Instead of WISH , which destroys GFP fluorescence , the distribution of virus-infected cells was analyzed by whole-mount immunohistochemistry ( WIHC ) , using the 4B3 and 19B7 monoclonal antibodies ( mAb ) directed against the P and G protein of IHNV , respectively . This technique was found to be less sensitive than WISH due to a higher background , especially with 4B3 ( Figure S2 in Text S1 ) , but the general staining patterns were similar , supporting the specificity of our labelings . fli1:GFP larvae were infected with IHNV25 , fixed at 24 hpi , processed for WIHC with the 4B3 mAb , and analyzed by fluorescence confocal microscopy ( Figure 3 ) . Most cells stained with the antibody ( in red ) were found at a position close to the expected location of a vessel . Co-localization with GFP ( in green ) was relatively rare , and vessels generally appeared to be disrupted near places of viral P protein expression ( Figure 3B–D ) . Nevertheless , in some cells , unambiguous co-localization of GFP ( in both cytoplasm and nucleus ) and P-IHNV ( in cytoplasm only ) was observed ( Figure 3E–H ) . This suggested that infection of an endothelial cell with IHNV quickly resulted in the death of the cell , or at least loss of GFP expression . This was further strengthened by observations of some infected intersomitic vessels ( Figure 3I–K ) : the dorsal half of one vessel was found to be virus free and expressing GFP , while no GFP expression was found on the ventral-most third , where , in contrast , cells stained for P-IHNV were found at the expected vessel location . One doubly-labeled cell is visible just below the midline . Again , frequent staining of cells just next to the vessel location suggested that the infection spread from the endothelial cells to underlying tissue . Observations of P-IHNV expressing cells in the heart were generally more consistent with infection of isolated myocardial cells rather than endocardial cells ( not shown ) . The anti-G mAb allowed us to detect infected cells as early as 10 hpi ( but not at 6 hpi ) , and we used it to conduct a time-course IHC analysis from 10 to 24 hpi . The number of infected cells was observed to increase steadily over time , and the majority of infected cells were found at places where endothelial cells are expected , often ( but not always ) expressing GFP ( Figure S3 in Text S1 ) . Some infected cells were located outside of the vessels , but this was less frequent at early time points . In conclusion , these observations establish that some vascular endothelial cells are infected with IHNV prior to the appearance of clinical signs . They also suggest that this rapidly results in disruption of blood vessels and dissemination of the virus to neighboring cells . The overall loss of GFP expression by endothelial cells in fli1:GFP larvae could be readily observed in live imaged animals; from 48 hpi the difference between infected and control larvae was striking ( Figure 4A ) . Erythrocytes ( which are nucleated in zebrafish ) and their precursors were also likely targets of the virus; anemia has been described after IHNV injection to adult zebrafish [10] and these cells are as exposed as endothelial cells with iv inoculation . To test this , we infected and live imaged gata1:DsRed reporter larvae , in which DsRed is expressed in erythrocytes and their precursors [23] . The distribution of DsRed-expressing cells was different between control and infected animals and consistent with accumulation of red blood cells in various spots due to loss of blood flow; however , the overall level of DsRed expression did not appear to be decreased at 48 hpi ( Figure 4B ) , indicating that in contrast to endothelial cells , erythrocytes are spared during IHNV infection . This conclusion was further strenghtened by careful examination of fli1:GFP larvae stained with the 4B3 or 19B7 mAbs ( see above ) , where no viral P or G protein expression could be detected in cells inside the lumen of blood vessels ( Figure 3 and not shown ) . We took advantage of the fact that the IHNV25 strain does not grow above 25°C to stop the progression of infection in zebrafish larvae at any stage , with simple temperature shift experiments . First , we ensured that either growth or cytopathic effect of IHNV25 can be observed in vitro at 24°C but not at 28°C ( Figure S4 in Text S1 ) . Larvae were infected iv as previously , incubated at 24°C for a certain time , and then shifted to the non-permissive temperature of 28°C . During the entire course of the experiment , individual larvae were regularly observed for occurrence of symptoms ( Figure 5A ) . If the shift was performed immediately , no pathology occurred . When the shift was performed at 6 hpi , no subsequent signs of infection could be detected in almost all larvae . In contrast , if the shift was performed at 24 hpi or later , irreversible pathogenesis ensued for all larvae . The critical turning point in the infection , with approximately 50% of the larvae being rescued without any of the above-described clinical signs , was 12 to 15 hpi . Before dying from the infection , temperature-shifted larvae displayed the same signs as described previously for unshifted larvae , in the same order , but delayed ( Figure 5B ) ; in addition , they exhibited edemas of impressive proportions ( Figure 5C ) . Quantification of IHNV titers or N-IHNV transcripts in T°-shifted larvae revealed , as expected , that infection was reduced as compared to non-shifted larvae ( Figure 5D ) . However , high amounts of virus were still detectable , indicating that T° shift to 28°C did not destroy the virus and suggesting it did not rescue already infected cells . The T° shift probably prevented infection of new cells , interfering with either viral entry , replication or assembly . We have previously shown [11] that larvae can be partially protected from IHNV infection by injection of recombinant interferon ( IFN ) a few hours before viral challenge and that expression of both ifnφ1 and ifnφ3 is induced at 48hpi by IHNV infection . Both interferons induce the expression of many genes including viperin ( also known as vig1 or rsad2 ) and MXA . To analyse the kinetics of expression of host antiviral genes during the course of the infection , we measured by qRT-PCR the expression of ifnφ1 , ifnφ3 , and viperin at 6 , 8 , 12 , 24 , 30 and 48 hpi ( Figure 6 ) . Potent induction of all these genes could only be detected at 30 or 48 hpi . Stastically significant , but very weak ( less than 4-fold ) induction of viperin or MXA was detectable at 24 hpi . Levels of IFNφ3 were sometimes slightly elevated ( about 2-fold ) early after infection . As T°-shift experiments have shown that IHNV infection causes irreversible damage before 24 hpi , this result strongly suggests that the endogenous host response comes too late to exert any significant control over the viral infection . Even if overdue , the host IFN response may be responsible for some of the disease signs , which are also observed after the point of no return . To test this , we injected 72 hpf fli1:GFP larvae with recombinant IFN , and carefully monitored them afterwards . We tested both groups of fish IFNs by using either 100 pg of IFNφ1 or 1 ng of IFNφ2 , doses that result in strong viperin induction 6 hours post-injection , and to significant resistance to a challenge with IHNV25 when compared with BSA-injected controls ( [11] and data not shown ) . We observed the larvae injected with IFN , but not challenged with virus , for any sign linked to the disease , such as mortality , loss of reactivity , decrease of blood flow , haemorrhages , or edemas , and found no difference with control larvae . We also imaged them by fluorescence microscopy at 6 , 24 and 48 hours post-injection of the cytokine , and did not observe any dampening of the GFP signal in endothelium ( data not shown ) . These negative results were obtained in two independent experiments . We conclude that disease signs are unlikely to be caused by the host IFN response , but probably reflect virus-caused damage .
We describe in this paper the spread of a viral infection throughout an entire organism , something that , to our knowledge , has not been done before in a vertebrate . Taking advantage of the small size and optical accessibility of zebrafish larvae , it is possible to identify infected cells anywhere in the body . This provides us with a very useful model to study the effects of antiviral drugs or of the various elements of the host response . A particular advantage of this system over other approaches resides with the possibility to directly compare organ specificity . Many viruses are known to take up residence in reservoir organs where they are harder to detect and are less exposed to drugs and/or immune responses , such as the central nervous system [24] , [25] . Although the approaches we developed here could be readily applied to other viruses using the adequate probes or antibodies , the heat-adapted IHNV virus has specific advantages . First , gross clinical signs of infection are easy to follow , reproducible , and occur in a highly synchronous fashion in groups of infected larvae ( Figure 1 ) , making it simple to compare experimental situations . The kinetics of the infection is convenient: death does not occur in the precipitous ways seen with other viruses such as SVCV [6] -making it possible to identify factors that would accelerate infection- yet signs occur early enough to allow the use of synthetic mRNA and morpholino-based gene gain- and loss-of-function approaches available in zebrafish larvae . Moreover , using very simple temperature shift experiments , it is possible to manipulate the replication of the virus in this poikilothermic animal ( Figure 5 ) . Finally , this virus is amenable to reverse genetics . This system also has some significant drawbacks . IHNV is not a natural pathogen of zebrafish - however none has been characterized so far . The virus has to be microinjected to establish infection , precluding the study of events involved in virus entry . Nevertheless , it affords a reliable system to study the subsequent systemic spread of the virus . Although some other viruses can enter zebrafish larvae by more natural routes , they do not result in the highly predictable infection course obtained with this IHNV strain , and are therefore less amenable to experimental manipulation . Our observations highlight vascular endothelial cells as the primary targets in the pathology of this experimental infection . The first cells expressing viral genes are found where major veins are localized ( Figure 2 ) ; infected endothelial cells could be observed ( Figure 3 ) . As the infection progresses , the vessels become disrupted and other cells are found infected next to the former location of the missing endothelial cells , suggesting that the virus spreads to the neighboring tissues mostly by cell-to-cell contact , even though direct translocation of bloodborne virus to these tissues through fenestrated endothelium cannot be ruled out . Disruption of vessel integrity can explain much of the observable signs of disease , such as slowing down and arrest of blood flow despite continuing heartbeat , hemorrhages , and edemas . There is probably a threshold level of damage to the endothelia , below which the larvae can still maintain or regenerate vessel integrity , as suggested by temperature shift experiments: many larvae could fully recover when shifted to the non-permissive temperature before 18 hpi , despite the fact that infected vessels were revealed by WISH in all animals at 6 hpi . There seems to be a preferential infection of veins over arteries , at least in the earlier phases of the infection; this may be explained by the higher endocytic capacity of zebrafish venous endothelial cells ( PH , unpublished data ) reflecting a general property of certain subsets of endothelial cells in all vertebrates [26] . Are there other cells types infected by IHNV , and what is their contribution to the pathology ? Our observations of gata1:DsRed transgenic larvae indicate that erythrocytes and their precursors are not early targets of the virus ( Figure 4 ) . Our preliminary , unpublished observations also suggest that neither neutrophils nor thrombocytes are targeted by the virus . The apparent tropism of the virus for endothelium among blood-exposed cells clearly deserves more investigation . Fibronectin has been shown to act as a primary receptor for IHNV in trout cells [27] , and further experiments performed in vitro with zebrafish cells have pointed out that IHNV entry is mediated by a minor truncated isoform of fibronectin ( FN2 ) located at cell surfaces [28] . It would be interesting to check whether this isoform is specifically expressed by vascular endothelial cells . Unfortunately , almost all of the sequence of the FN2-encoding transcript is also included in the transcript encoding the main fibronectin isoform , precluding WISH analysis . We also plan to study in more detail the infection of non-hematopoietic tissues; notably , it will be of particular interest to establish how the virus propagates in the brain ( in which necrosis is often observed at late stages ) from infected brain vasculature , as it exemplifies one of the strategies that allow pathogens to cross the blood-brain-barrier . As shown here , zebrafish larvae are unable to mount a detectable interferon response before irreversible damage has been caused by the infection ( Figure 6 ) . This is clearly not the consequence of an immature state of the immune system , as a response to SVCV could be detected much earlier [6] . We suspect that , like other rhabodviruses [29] , IHNV has the ability to hinder or delay the induction of the host interferon response . Identifying the precise molecular mechanisms at play will be an important goal in the future . In conclusion , the IHNV/zebrafish model we have established constitutes the first example of a system where a viral infection can be imaged in an entire vertebrate host . Our observations suggest the following scenario of viral dissemination: first , via an hematogenous route , leading to infection of vascular endothelial cells throughout the body . The ensuing destruction of endothelial cells disrupts blood flow , causing hemorrhages and edemas . The infection of a sufficient number of vascular cells is probably sufficient to yield irreversible damage . However , it also results in a second mode of infection , affecting underlying tissue via cell-to-cell or very short distance virus transfer . This sequence of events is likely to hold true for a number of human viruses causing hemorrhaging diseases . The validity of this hypothetical scenario is testable , as it predicts that experimental manipulations that result in overexpression of genes with antiviral activity ( i . e . appropriate IFN-stimulated genes ) specifically in vascular endothelial cells should result in efficient protection of the host with reduced side effects compared to ubiquitous overexpression . Thanks to the already available genetic tools , endothelium-specific inducible expression would be relatively easy to achieve in zebrafish; the endocytic properties of veinous vascular cells may also be exploited to target drugs to these cells , and this could be monitored in real time . Combined with the assessment of organ-specific distribution of virus in the organism , such studies have the potential to help designing more targeted , safer treatment regimens for human viral diseases .
All the animal experiments described in the present study were conducted at the Institut Pasteur according to the European Union guidelines for the handling of laboratory animals ( http://ec . europa . eu/environment/chemicals/lab_animals/home_en . htm ) and were approved by the Institut Pasteur animal care and use committee and by Direction Sanitaire et Vétérinaire de Paris under permit #A-75-12-22 . Wild-type AB , initially purchased from the ZIRC ( Zebrafish International Resource Center , Eugene , OR ) , transgenic fli1:GFP [22] , and transgenic gata1:DsRed [23] were raised in our fish facility . Eggs were obtained by marble-induced spawning , bleached according to protocols described in The Zebrafish Book [30] , and then kept in petri dishes containing Volvic source water supplemented with 0 . 3 µg/ml of methylene blue . Depending on the desired speed of development , embryos were raised at 28°C or 24°C before infection; all staging in the text refers to the standard 28 , 5°C developmental time . A few hours before injection , embryos were dechorionated manually . Larvae were anesthetized with 200 µg/ml tricaine ( Sigma-Aldrich ) . Generation of the IHNV25 . 70 strain has been described in [11] . The virus was propagated on EPC cells ( ATCC# CRL-2872 ) . Virus-containing cell culture supernatants were aliquoted and stored at −80°C until use . Just before injection , the virus was diluted ( if necessary ) to the appropriate concentration with PBS containing 0 . 1% phenol red . Larvae were infected by iv microinjection in the caudal vein or aorta as described in [31] . Infected larvae were then distributed in individual wells of 24-well culture plates , containing 1 ml of Volvic water each . Larvae were regularly observed with a stereomicroscope to check for the appearance of clinical signs of infection . A clinical score from 0 to 3 was determined without anesthesizing the larvae by checking for movement of blood cells in the tail and by gently pricking the side of the head with a soft paintbrush . Larvae with visible blood flow in the tail - precisely , in any vessel located posterior to the urogenital opening - , which were always reactive , were attributed a score of 3 . Larvae with blood arrested in the tail ( even if flowing elsewhere ) but that still swam away ( at least one body length of distance ) when pricked were given a score of 2 . Larvae that did not swim away after three pricking attempts , but still had any detectable heart beat when oriented on their side were assigned a score of 1 . Larvae with no movement whatsoever were considered dead with a score of zero . Scoring has been performed in a blind fashion at least once for each type of test . Imaging was performed as described in detail in [31] . Briefly , video-enhanced DIC images of live larvae were taken using a Nikon Eclipse 90i microscope equipped with a Hitachi HV-C20 camera and movies captured on miniDV tapes; single frames were later captured using the BTVpro software . Images of larvae stained by WISH were taken with a Leica MZ16 stereomicroscope using illumination from above . Images of whole live larvae were taken with a similar stereomicroscope fitted with a Nikon DS-5Mc camera , using oblique illumination . Confocal images of live or fixed larvae were taken with a Leica SPE inverted confocal microscope . Images were processed with the LAS-AF ( Leica ) , ImageJ and Adobe Photoshop softwares . Titers of infectious virions were measured by plaque assay on monolayers of EPC cells . Larvae to be assessed were anesthetized with tricaine , transferred as groups of 5 larvae to a microtitration tube with no more than 30 µl of water , snap-frozen on a bed of dry ice and stored at −80°C until processing . Larvae were homogeneized by grinding them with a pestle fitted to the tubes , and 100 µl of culture medium supplemented with 2% FCS was added . Supernatants were cleared by a 5 min centrifugation at 930 g , and serially diluted in duplicates for the plaque assay . The infection was performed at 24°C under a layer of methylcellulose ( 0 . 75% final concentration ) for three days after an adsorption step at 14°C for one hour in liquid phase . The plaques were then counted after treatment by formaldehyde ( 10% ) and staining using crystal violet ( 1% final dilution ) . RNA was extracted from snap-frozen larvae using Trizol ( Invitrogen ) . cDNA was obtained using M-MLV H- reverse-transcriptase ( Promega ) with a dT17 primer , except for IHNV genome quantification where a random N10 primer was used . Quantitative PCR was then performed on an ABI7300 thermocycler ( Applied Biosystems ) using SYBR green reaction power mix ( Applied Biosystems ) . The following pairs of primers were used: EF1α: GCTGATCGTTGGAGTCAACA and ACAGACTTGACCTCAGTGGT N-IHNV: CACTGGACTCAGAGACATCA and CTGCAAGCTTGTTGTTGGGA IHNV genome: CACTGGGTGGAATTCCCTTT ( in G gene ) and CAATACTCGCTGCATCCTCT ( in NV gene ) IFNφ1: TGAGAACTCAAATGTGGACCT and GTCCTCCACCTTTGACTTGT IFNφ3: GAGGATCAGGTTACTGGTGT and GTTCATGATGCATGTGCTGTA viperin: GCTGAAAGAAGCAGGAATGG and AAACACTGGAAGACCTTCCAA MXA: GACCGTCTCTGATGTGGTTA and GCATGCTTTAGACTCTGGCT Quantifications were performed on triplicate wells , and taking into account the previously measured yield of the reaction as described in [32] . To normalize cDNA amounts , we have used the housekeeping gene EF1α transcripts , chosen for its high and very stable expression from 12 to 120 hpf [33]; error bars represent standard deviation of the measured ratios . WISH was performed using standard protocols [30] . To generate the probe , the full-length coding sequence of N-IHNV [34] was subcloned in antisense orientation in the pCS2+ vector , which was then linearized with NotI and transcribed in vitro with SP6 polymerase ( Promega ) . The signal was very high and revealed in five to ten minutes . WIHC was performed as described [35] using , as a primary antibody , either the 4B3 mAb antibody specific of IHNV P ( phosphoprotein ) or the 19B7 mAb antibody specific of IHNV G ( glycoprotein ) [36] diluted 1/500th; and , as a secondary antibody , Cy3-labelled goat anti-mouse antibody ( Jackson Immunoresearch ) diluted 1/300th . Larvae were counterstained for 45 min at room temperature with 2 µg/ml Hoechst 33342 ( Molecular Probes ) before being progressively transferred to 80% glycerol . zebrafish genes or proteins: EF1α: NM_131263; IFNφ1: NM_207640; IFNφ2: NP_001104552; IFNφ3: NM_001111083; viperin: NM_001025556; MXA: NM_182942 IHNV genes or proteins: Genome: NC_001652; N: NP_042676; P: NP_042677
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The zebrafish larva is uniquely amenable to imaging among vertebrate models because of its small size , transparency , and ease of anesthesia , making it a useful model to understand host-pathogen interactions . We have performed the first detailed analysis of a viral infection in zebrafish . Infection of zebrafish larvae with a salmonid rhabdovirus adapted to growth at the appropriate temperatures resulted in a predictable succession of pathological signs before death . Detection of infected cells in whole larvae revealed that blood vessels were a major target of the virus , providing an explanation to hemorrhages and subsequent loss of blood flow observed in infected larvae . Destruction of vascular cells caused by the viral infection was readily observed in transgenic larvae with fluorescent endothelium . We could identify the critical moments of the infection with simple temperature shift experiments . This work provides a basis to dissect the role of host factors in controlling the propagation of viral infections .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Material",
"and",
"Methods"
] |
[
"virology/animal",
"models",
"of",
"infection",
"immunology/innate",
"immunity",
"infectious",
"diseases/viral",
"infections",
"virology/host",
"antiviral",
"responses",
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"invasion",
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] |
2011
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Whole-Body Analysis of a Viral Infection: Vascular Endothelium is a Primary Target of Infectious Hematopoietic Necrosis Virus in Zebrafish Larvae
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Recent studies in simple model organisms have shown that centromere pairing is important for ensuring high-fidelity meiotic chromosome segregation . However , this process and the mechanisms regulating it in higher eukaryotes are unknown . Here we present the first detailed study of meiotic centromere pairing in mouse spermatogenesis and link it with key events of the G2/metaphase I transition . In mouse we observed no evidence of the persistent coupling of centromeres that has been observed in several model organisms . We do however find that telomeres associate in non-homologous pairs or small groups in B type spermatogonia and pre-leptotene spermatocytes , and this association is disrupted by deletion of the synaptonemal complex component SYCP3 . Intriguingly , we found that , in mid prophase , chromosome synapsis is not initiated at centromeres , and centromeric regions are the last to pair in the zygotene-pachytene transition . In late prophase , we first identified the proteins that reside at paired centromeres . We found that components of the central and lateral element and transverse filaments of the synaptonemal complex are retained at paired centromeres after disassembly of the synaptonemal complex along diplotene chromosome arms . The absence of SYCP1 prevents centromere pairing in knockout mouse spermatocytes . The localization dynamics of SYCP1 and SYCP3 suggest that they play different roles in promoting homologous centromere pairing . SYCP1 remains only at paired centromeres coincident with the time at which some kinetochore proteins begin loading at centromeres , consistent with a role in assembly of meiosis-specific kinetochores . After removal of SYCP1 from centromeres , SYCP3 then accumulates at paired centromeres where it may promote bi-orientation of homologous centromeres . We propose that , in addition to their roles as synaptonemal complex components , SYCP1 and SYCP3 act at the centromeres to promote the establishment and/or maintenance of centromere pairing and , by doing so , improve the segregation fidelity of mammalian meiotic chromosomes .
During the first meiotic division , homologous chromosomes pair , recombine and dissociate . Successful completion of these processes is required for a pair of homologous chromosomes ( bivalent ) to mount the meiotic spindle . Organization of the chromosomes into pairs ensures orderly segregation of homologous chromosomes to opposite spindle poles at the first meiotic division , ensuring that each gamete receives one copy of each chromosome . Errors in meiotic homologous chromosome segregation are the leading cause of human aneuploidy . Some examples of hereditary diseases caused by aneuploidies are several types of Ataxias and Down , Klinefelter , Edwards and Turner Syndromes [1] . The molecular basis of aneuploidy in humans is poorly understood . Identification and description of mechanisms used to promote meiotic fidelity are essential to improve this understanding . One component of the meiotic process that is critical for ensuring high fidelity chromosome segregation is recombination . Chiasmata , the cytological manifestation of product of recombination , provide a physical link that holds the homologs in pairs and facilitates their orientation on the spindle at meiosis I [2] . Consequently , mutations that reduce the amount of recombination are invariably associated with increased errors in meiotic chromosome segregation . Indeed , in yeast , mice , and humans , chromosome pairs that fail to recombine have an increased chance of mis-segregating [3] . However , in yeast and flies it has been shown that such error-prone chromosomes do not segregate randomly . Instead , a high proportion of them are partitioned correctly using segregation-promoting mechanisms that lack chiasmata [4] . In yeast , pairing between centromeres promotes proper segregation of non-recombined meiotic chromosomes [5] and also contributes significantly to the segregation fidelity of chromosomes that have recombined [6] . Similarly , in Drosophila , pairing between blocks of peri-centric heterochromatin has been shown to orient non-recombined partner chromosomes that have not become tethered by a chiasmata [7] , [8] . We tested the hypothesis that in a mammalian system , centromere pairing links homologous centromeres in a way that has been shown in other model systems to promote their proper attachment to microtubules from opposite poles of the meiotic I spindle . While centromere pairing has been observed in a number of organisms ( reviewed in [2] ) , its existence and roles in meiosis of mammals have not been explored . An intriguing characteristic of centromere pairing is that synaptonemal complex components in yeast ( Zip1 ) and Drosophila ( C ( 3 ) G ) are required for maintenance of centromere pairing late in meiotic prophase [6] , [9] , [10] . The mammalian synaptonemal complex protein SYCP1 appears to be the functional homolog of Zip1 and C ( 3 ) G [11] . Previous work has shown that Sycp1 knockout spermatocytes reach advanced stages of prophase I with an absence of homolog synapsis including the centromeres [12] . In this work we explore whether SYCP1 and SYCP3 are present at the paired centromeres in earlier and later stages of mouse spermatogenesis and discuss the possible significance of centromere pairing with closely linked processes such as kinetochore assembly or bi-orientation of centromeres at the meiosis I division . A possible function of centromere pairing is to promote the proper loading/assembly of kinetochore-specific proteins at the meiotic kinetochore . Kinetochores are located on the outside face of centromeres and function to attach chromosomes to the meiosis I spindle . Ultrastructurally , kinetochores are distinct trilaminar structures . On mitotic chromosomes , there is an inner plate , constituted by chromatin containing a centromeric histone H3 variant , CENPA , auxiliary proteins and DNA . There is an outer plate composed of proteins involved in the process of binding microtubules . The region between the two mitotic sister kinetochores is called the inner centromeric domain and is defined by the presence of a chromosome passenger complex ( INCENP , AURORA B , SURVIVIN , BOREALIN and AURORA C ) ( reviewed in [13] ) . Assembly of mitotic kinetochore structures on meiotic chromosomes could lead to segregation of sister chromatids away from each another at meiosis I , which is thought to be one of the most common types of meiotic segregation errors in humans . Little is known about the process by which cells assemble meiotic rather than mitotic centromere structures . However , recent studies in mouse spermatocytes have made clear there is a program of assembly of the meiosis I outer kinetochore after the time at which chromosomes have synapsed with their partners in prophase I and when sister kinetochores are tightly cohered [14] . Persistence of synaptonemal complex components at the centromeres as the cell progresses towards metaphase has been demonstrated in model organisms [6] , [9] , [10] . This may suggest new roles for these synaptonemal complex proteins at the centromere . Indeed we find that SYCP1 and SYCP3 proteins remain at centromeres co-incident with the time of outer kinetochore assembly , and appear to promote steps in the establishment and/or maintenance of centromere pairing until the centromeres begin their attachment to the meiotic spindle .
We have characterized events of centromere pairing in male mouse meiosis by analyzing the kinetics of centromere pairing in cells at different stages of prophase in meiosis I . Parallel observations are made by Qiao et al . in the accompanying study [15] . To score the number of centromeres we immunostained structurally intact preserved nuclei from squashed seminiferous tubules with CREST antibodies specific for kinetochores ( Figure 1 and Figure S1 ) . Mice have 20 pairs of chromosomes ( in males 19 pairs of somatic chromosomes and a pair of heteromorphic sex chromosomes ) . The sex chromosomes pair only at the PAR region , which includes the distal telomeric but not the centromeric region . Complete pairing of homologous centromeres in pachytene spermatocytes would be expected to yield 21 centromeric CREST foci while completely dispersed centromeres would yield 40 foci . We first analyzed cells in the very early stages of spermatogenesis . B type spermatogonia , which are engaged in pre-meiotic proliferation , show an average of 28 . 5±1 . 9 CREST foci per cell ( n = 100 ) . For pre-leptotene spermatocytes , which are in meiotic S-phase , or have just passed premeiotic S , as shown by incorporation of EDU into replicating DNA ( Figure S1 ) , we observed an average of 27 . 1±1 . 8 CREST foci per cell ( n = 100 ) ( Figure 1A and Table 1 ) . This intermediate level of CREST foci could result from either partial pairing of centromeres , or from telomere pairing; because each centromere is adjacent to one of the telomeres of the chromosome , one-half of randomly paired telomeres would bring together two centromeres and reduce the number of CREST foci from 40 to about 30 . To distinguish between these possibilities we stained chromosomes for the telomere-associated protein , RAP1 [16] ( Figure 1B and Table 1 ) . Most nuclei in early prophase exhibited almost exactly the number of foci predicted if all of the telomeres are in pairwise associations ( 39 . 2±1 . 8 and 39 . 1±1 . 6 RAP1 foci for B type spermatogonia and pre-leptotene cells respectively ) . These results suggest that most of the 80 telomeres are arranged in pairs or clusters in early prophase nuclei . To test whether this pairing was between homologous regions , we performed fluorescence in-situ hybridization ( FISH ) , with a point probe specific for the centromeric region of chromosome VIII ( which is associated with the proximal telomere ) . The results showed that in most B type spermatogonia and pre-leptotene meiocytes this centromere and its nearby telomere are not associated with their homologous partners ( only 17% homologous pairing was observed for early prophase cells . Figure S2 ) . Together these results suggest that in very early meiosis in mouse spermatocytes , centromeres do not exhibit an extended period of centromere coupling as seen in some other organisms . Instead , the telomeres associate with one another , but not with their homologous partners , and this telomere pairing sometimes brings pairs of the telocentric centromeres close together . In budding yeast the coupling of non-homologous centromere pairs in very early meiosis ( leptotene ) requires Zip1 [17] , the budding yeast homolog of mouse SYCP1 , and does not require other known components of the synaptonemal complex [18] . We asked whether this would be the case in mouse spermatocytes . We performed co-localization experiments to test whether the synaptonemal components SYCP1 or SYCP3 associate with centromere regions in early prophase when telomere associations are occurring ( using CREST and SYCP1 or SYCP3 immunostaining ) . In leptotene we detected no SYCP1 staining , and from early to late zygotene the few traces of foci of SYCP1 mostly did not co-localize with centromeres ( 1–11 . 9% , Figure S3 ) . However , SYCP3 is present at early leptotene and , unexpectedly , 97 . 8% of CREST foci co-localize with SYCP3 signals at this stage ( Figure S3 ) . These results indicate another contrast to the situation in yeast; while yeast centromere coupling requires Zip1 but not axial element components , the mouse centromeres at a similar stage of meiosis exhibit co-localization with an axial element component ( SYCP3 ) but not the Zip1 homolog SYCP1 . The period of apparent telomere associations ( B type spermatogonia and pre-leptotene , Figure 1 ) precedes the time at which we first detect clear association of SYCP3 with centromeres ( Figure S3 ) . Nonetheless we tested whether SYCP3 might play any role in early centromere association by scoring the numbers of CREST foci in Sycp3 knockout mice . We observed a significant increase in the number of CREST foci in SYCP3 knockout spermatocytes with respect to wild-type at the stages of B type spermatogonia , pre-leptotene , and zygotene ( Figure 1A and Table 1 ) . Whereas the data may suggest that SYCP3 promotes early associations of telomeres ( and associated centromeres ) the lack of detectable SYCP3 foci in B type spermatogonia and pre-leptotene ( result not shown ) limits the conclusions . While we contemplate the possibility of some level of centromere pairing in very early meiosis , the data above can be explained by a period of telomere pairing in early spermatogenesis that brings some centromeres together simply because centromeres are adjacent to telomeres . Furthermore , associations of pericentric heterochromatin clusters that have been observed in spermatogonia could play a role in these associations [19] . In early meiotic prophase we observed an average of 36 . 1±2 . 6 CREST foci per leptotene cell ( n = 220 ) and 36 . 2±2 . 1 ( n = 190 ) and 35 . 1±0 . 9 ( n = 190 ) CREST foci per cell in early and late zygotene respectively . We also observed an average of 66 . 4±1 . 7 RAP1 foci per leptotene spermatocyte and 65 . 9±1 . 6 RAP1 foci per early/late zygotene spermatocyte . These results are consistent with little or no centromere pairing and a loss of the telomere associations seen in pre-leptotene cells . However , centromeres did appear to cluster primarily on one side of the nucleus as previously described for a bouquet formation [20] ( Figure S1 , leptotene and zygotene ) . In pachytene , consistent with completion of homologous chromosome synapsis , we observed an average of 21±0 . 6 CREST foci per nucleus and 38±1 . 5 RAP1 foci per nucleus ( n = 200 ) ( Figure 1A and 1B and Table 1 ) . We made a remarkable observation when we assayed chromosomes in preserved diplotene cells . The prevailing model for meiotic chromosome behavior is that as cells exit pachytene ( towards diplotene ) the homologous chromosomes de-synapse and remain joined only at the sites of recombination ( chiasmata ) which are usually located along their arms . If this model were correct , then we would expect a significant increase in the number of CREST signals as cells move into diplotene . However , in whole cell preparations we observed an average of 22 . 9±0 . 7 CREST foci per spermatocyte at mid diplotene ( n = 220 ) and 22 . 7±0 . 9 CREST foci per spermatocyte at late diplotene ( n = 220 ) ( Figure 1A and Table 1 ) . This important finding indicates that , while the chromosome arms of homologous partners dissociate , their centromeric regions remain paired , just as has been recently reported for yeast [6] , [9] and Drosophila females [10] . Given that mouse chromosomes are acrocentric and each centromere is located adjacent to a ( short arm ) telomere , the question arises as to whether it is an association between telomeres , not centromeres , that is responsible for the reduced number of CREST signals observed in late stages of prophase I . To address this we examined the configuration of individual chromosome pairs in chromosome spread preparations . These preparations are more disruptive than the whole cell preparations used above but offer high resolution views of chromosome configurations ( Table 2 ) . Chromosome spreads were stained with SYCP3 to reveal the chromosome axes . In late prophase , nuclear spreads revealed that bivalents frequently exhibited one paired end and one splayed end with internal connections representing chiasma ( Figure 1C ) . For these chromosome figures , tethered by only a central chiasma ( for chromosomes experiencing only one exchange event the chiasma is typically located in the central region of the chromosome [21] ) we used CREST antibodies to determine whether it was the end with the centromeres that was paired . We observed a strong preferential pairing of the centromeric chromosomal end over the distal telomere ( Figure 1C ) . This supports a model in which the centromeric regions of chromosomes remain paired after chromosome arms dissociate , consistent with Brinkley's first descriptions of mouse centromere behaviors [22] . Intriguingly , we observed that a fraction of homologous chromosomes in the stage of late diplotene show no apparent chiasma ( potentially non-exchange ) and are only tethered by paired centromeres ( Figure 1D , tailed arrows and Figure S4 ) . The frequency of apparent non-exchange chromosomes ( 4 . 6% , n = 619 ) is similar to previous reports ( 2–4% ) [21] , [23] , [24] . The configuration of the apparent non-exchange chromosomes suggests they have no chiasma , though chromosomes with a single chiasma in the pericentric chromatin would have a similar appearance . We think it is unlikely that many of these chromosomes have pericentric chiasma as genetic exchange is rare in this region [21] and the distribution of MLH1 foci ( which mark sites of crossing overs ) on our chromosomes indicates that pericentric recombination was rare ( Figure S4B ) . Our observation that centromeres remain paired between apparent non-exchange partners suggests a possible role of centromere pairing in tethering non-exchange chromosomes , which , as described in simple model organisms , may improve their proper segregation . In summary , our data suggest that centromere pairing in late prophase I is a conserved component of the meiotic process . The fact that in unicellular model organisms this pairing of centromere regions promotes bi-orientation on the meiotic spindle [5]–[9] , suggests that mammals might also use this mechanism to achieve high fidelity meiotic segregation . The evaluation of centromere pairing throughout meiosis I , described above , allowed us to address the possibility that centromeres are involved in the initiation of synapsis , as has been suggested from studies in budding yeast [25] . In budding yeast , the centromeres , which are rich in synaptonemal complex components , act as primary initiation sites for chromosome synapsis [25] . We analyzed the partially synapsed chromosomes from spermatocytes in the synapsis process to determine whether centromeres are the first sites of synapsis ( Figure 2 ) . Chromosome spreads were stained with antibodies against SYCP3 to visualize the synapsing chromosome axes , SYCP1 to evaluate synaptonemal complex formation and CREST antibodies to reveal the disposition of the centromeres ( Figure 2A ) . The analysis of over one thousand individual partially synapsed chromosomes ( Figure 2B ) revealed that they fell into several categories . Most common were chromosomes with a single stretch of synaptonemal complex at the non-centromeric end ( Figure 2C , 50 . 8% ) , and chromosomes with an internal stretch of synaptonemal complex with both ends not yet synapsed ( Figure 2C; 37% ) . In contrast to the situation in budding yeast , chromosomes consistent with initiation of synaptonemal complex at the centromeres ( Figure 2C; 1% ) were rare . These findings are consistent with observations in many other organisms where synaptonemal complex appears to initiate at internal sites rather than at centromeres . In many instances the internal sites of synapsis initiation appear to be associated with the sites at which recombination initiates ( reviewed in [26] ) . Previous studies in yeast and Drosophila have shown that the homologs of mouse SYCP1 are required for late centromere pairing [6] , [9] , [10] . We therefore tested whether SYCP1 is present at the paired centromeres of mouse spermatocytes at later stages of prophase I using both chromosome spreads and intact cells ( squashes of seminiferous tubules ) . In squashes we observed that approximately 71% of the CREST foci in mid/late diplotene stage spermatocytes co-localized with SYCP1 signals ( 16 . 2±2 . 8 out of 22 . 8±0 . 8 CREST foci , n = 430 ) and observed similar values in chromosome spreads ( 64 . 3% , n = 124 ) ( Table 2 ) . The co-localization of SYCP1 with centromeres in diplotene , when the synaptonemal complex has disassembled is reminiscent of the situation in yeast where Zip1 localization promotes centromere pairing in late prophase . To test whether there is a correlation between SYCP1 centromeric localization and persistent centromere pairing in late prophase we also analyzed CREST and SYCP1 co-localization on individual chromosome pairs that did or did not exhibit centromere pairing . We observed that while 99 . 1% chromosomes with paired centromeres exhibited co-localization of SYCP1 with the centromeres , only 8 . 5% of chromosomes with distal telomere pairing ( but not centromere pairing ) and only 20 . 2% of chromosomes held by chromosome arms but not by either centromeres or distal telomeres gave detectable SYCP1 at the unpaired centromeres ( Table 3 ) . In sum , the results indicate that as spermatocytes transit through diplotene and metaphase I , SYCP1 is removed from the arms of the chromosomes but remains between paired homologous centromeres ( Figure 3A–3F , Table 2 and Table 3 ) . We also analyzed the distribution of components of the central element ( SYCE1 , SYCE2 and TEX12 ) . As observed for SYCP1 , at later stages of prophase I these central element components are removed from chromosome arms but remain at paired homologous centromeres ( Figure 3 and Table 2 ) . The analysis of synaptonemal complex proteins distribution on individual chromosome pairs in spread preparations reveal that , as observed for paired centromeres , SYCP1 and components of the central element remain at chiasmata sites ( Figure 3 ) . This finding may reveal the existence of a specialized mechanism common for maintenance of synaptonemal complex components at chiasma and paired centromeric areas ( see Discussion ) . Similar observation are made by Qiao et al . in the accompanying study [15] . To determine whether SYCP1 is necessary for centromere pairing in late prophase we tested whether the absence of SYCP1 leads to loss of centromere pairing in spread chromosomes . In spermatocytes harvested from Sycp1 knockout mice the homologous chromosomes were aligned in prophase as described previously [12] . However , in contrast to wild-type spermatocytes ( CREST foci 21±0 . 6 ( n = 200 ) , homologous centromeres were not paired ( Sycp1 38 . 1±1 . 8 ( n = 100 ) . Instead they were located side-by-side but not tightly associated ( Figure 4A–4H ) . Because Sycp1 knockout results in meiotic prophase arrest , we collected spermatocytes from these mice and drove them in vitro through the end of prophase I by treating with okadaic acid [27]–[29] . Here too , without SYCP1 , spermatocytes show no association between the homologous centromeres ( Figure 4I–4K ) . Our results showing the retention of synaptonemal complex components at the centromeres in late prophase ( Figure 3 and Table 2 ) , together with the previous demonstration that the lateral element protein SYCP3 remains at centromeres after lateral element disassembly [29]–[32] suggests that these proteins may play important roles at meiotic centromeres . To evaluate the relative behaviors of SYCP3 and synaptonemal complex central region components we first monitored the kinetics of SYCP1 and SYCP3 sub-chromosomal distribution relative to one another in late prophase I on spread chromosomes ( Figure 5 ) . SYCP3 and SYCP1 are both retained at centromeres in diplotene following synaptonemal complex disassembly but SYCP1 was not detectable by late diplotene and diakinesis . In contrast , as described previously , SYCP3 persists until metaphase I ( Figure 5 ) [29]–[31] . If centromere pairing , mediated by either of these proteins promotes bi-orientation on the emerging spindle , SYCP1 and SYCP3 might persist at the centromeres as microtubule attachments begin to be established . To examine this possibility , indirect immunofluorescence was used to monitor the distribution of SYCP1 and SYCP3 , in cells from meiotic squashes , relative to the emergence of the spindle that is formed as cells progress from late prophase to metaphase . Cell squash preparations were used as these , in contrast to surface chromosome spreads , allow staining of tubulin , which can be used as a marker for nuclear envelope dissolution and meiotic spindle assembly . After removal from chromosome arms SYCP1 is preferentially retained , in spermatocytes at mid diplotene , at punctate foci that correspond to centromeres ( as was shown in the chromosome spreads in Figure 5 ) . These foci are indicated by white arrows in the single plane images of the stained cells ( shown in Figure 6b ) . In a subsequent stage ( late diplotene ) SYCP1 becomes undetectable before nuclear envelope break down and before any clear assembly of microtubules around the chromosomes occurs ( Figure 6C ) . In contrast , SYCP3 is removed primarily from the arms of chromosomes by diplotene but is maintained at paired centromeres as microtubules begin to assemble around the chromosomes . SYCP3 remains associated with the sister centromeres until anaphase I ( Figure 6G–6K ) . Whereas persistence of SYCP3 has been interpreted as evidence for a role of SYCP3 in the diplotene-metaphase I transition [29]–[31] , some observations argue against this hypothesis [33] . In summary , we observed striking differences in the timing of disappearance/relocation of the SYCP1 and SYCP3 synaptonemal complex proteins from paired homologous centromeres . Both proteins persist at or between centromeres following synaptonemal complex disassembly . However , most SYCP1 leaves the centromeres in late diplotene while SYCP3 persists through the stages of microtubule attachment to kinetochores and meiosis I separation of the homologous partners .
Active pairing of meiotic centromeres has been observed in a variety of organisms and occurs at two different stages of meiotic prophase I . Pairing of centromeres by apparently homology-independent processes in early meiosis has been seen in a variety of organisms , and in yeast has been termed centromere coupling [17] . At present , the function of centromere coupling is not understood . However , in budding yeast , it is mediated by the synaptonemal complex central element component Zip1 and does not require other proteins that normally participate in synaptonemal complex assembly [18] . In mouse , we observed that spermatocytes do not exhibit prolonged period of nearly complete centromere coupling ( Figure 1A and Table 1 ) . Surprisingly , we found evidence for a period in which telomeres appear to be arranged in pairs or small groups independent of homology . Our data can be explained by a period of telomere pairing that brings some centromeres together simply because centromeres are adjacent to telomeres [19] . If there is a period of nearly complete centromere pairing in early prophase mouse spermatocytes , as is seen in some other organisms [2] , [17] , [34]–[39] , such pairing must be transient . In a variety of organisms , pairing between homologous centromeres in late prophase has been implicated in promoting proper meiosis I segregation . Studies focused on the meiotic behavior of non-exchange homologous chromosomes in Drosophila females strongly suggests that pairing between regions of pericentric heterochromatin allow the chromosome pairs to attach to the spindle in a bipolar fashion that mediates disjunction at meiosis I [7] , [8] . Similarly , in yeast , pairing between the homologous centromeres promotes bi-orientation of both non-exchange partners and homologous partners that have experienced crossovers [2] , [5] , [9] . In both budding yeast and Drosophila oocytes , centromeric associations in late meiotic prophase require components of the synaptonemal complex , which persist at the centromeres when the rest of the synaptonemal complex is disassembled [2] , [10] . Our results demonstrating centromere pairing in later stages of prophase , and the participation of SYCP1 and SYCP3 in the process , parallel those reported in budding yeast and Drosophila . In those organisms centromere pairing significantly improves segregation of non-exchange chromosomes and may well improve the segregation fidelity of exchange chromosomes as well . Based on these similarities , we propose that also in mice centromere pairing may promote proper segregation of homologous chromosomes . Indeed , we have observed that SYCP1 and SYCP3 may play separate roles in keeping homologous centromeres together at different stages of prophase I . The stage at which SYCP1 is lost from the arms and maintained at the homologous centromeres is co-incident with the time that certain kinetochore-specific proteins re-assemble onto the chromosomes and load at centromeres [6] , [10] , [14] ( Figure S5 ) . We propose that SYCP1 may act at the G2/M transition by contributing to the assembly of kinetochores that will promote meiosis I specific patterns of segregation ( Figure 7 ) . Although SYCP1 is not detectable between paired homologous centromeres at late diplotene , directly or indirectly it contributes to this pairing , as centromere pairing is not seen in SYCP1 knockout mice . Thus , the presence of SYCP1 at centromeres in earlier stages of meiotic prophase may be a prerequisite for establishing paired structures that persist into diplotene after SYCP1 is normally removed from centromeres , thus SYCP1 may be required more for the establishment than the maintenance of centromere pairing . In late diplotene , after removal of central region proteins between homologous centromeres , SYCP3 remains only at centromeres . We propose that SYCP3 maintains centromere pairing and contributes to bi-orientation of homologous centromeres and to spindle attachment that prepares the homologous chromosomes for the first meiotic division ( Figure 7 ) . As spermatocytes transit from pachytene ( complete synapsis ) to diplotene , synaptonemal complex proteins are lost from the chromosome arms but persist at the paired centromeres ( Figure 3 ) . Phosphorylation of synaptonemal complex components correlates with their removal/dissociation from chromosomes [29] , [40] , and Polo-like kinase ( PLK1 ) promotes synaptonemal complex disassembly in yeast and mice [29] , [41] , [42] . Our results suggest that removal of synaptonemal components is mechanistically different at the arms compared to the centromere . This might be explained if centromeres are paired by structures distinct from the synaptonemal complex . However , we saw no evidence of this since all the elements of the synaptonemal complex are present at paired centromeres ( Figure 3 ) . In an alternative hypothesis we propose that the synaptonemal complex proteins are in the same structures on arms and centromeres , but are protected from removal at the centromeres during disassembly . The existence of a specialized mechanism for maintenance of synaptonemal complex proteins at centromeric regions has support in previous reports . Here , Shugoshin ( SGO2 ) /PP2A was shown to protect cohesin complexes at centromeres , when arm cohesins are lost during the metaphase I to anaphase I transition , by antagonizing the action of kinases [41] , [43]–[45] . Indeed , SYCP1 and SYCP3 have potential PLK1 phosphorylation sites , and PLK1 only loads on meiotic centromeres at later stages of meiosis I coincident with the time when SYCP1 and SYCP3 are retained at centromeres [14] ( Figure S5 ) . Based on these results , we hypothesize that a dynamic interplay between PLK1 and SGO2-PP2A controls SYCP1 and SYCP3 phosphorylation , which then regulates retention of these proteins at centromeres with consequent regulation of centromere pairing .
Mice used in this study were as follows: Wild-type ( C57BL/6 ) , Sycp3 knockout [46] , Sypc1 knockout [12] . Experiments conformed to relevant regulatory standards and were approved by the IACUC Institutional Animal Care and Use Committee . Adult male C57BL/6 mice 4–8 weeks old were euthanized by CO2 inhalation followed by cervical dislocation . The testes were then removed and detunicated , and seminiferous tubules processed for squashing . For squashing , we followed a technique previously described [14] . Briefly , seminiferous tubules were fixed in freshly prepared 2% formaldehyde in 1× PBS containing 0 . 1% Triton X-100 . After 5 min , several seminiferous tubule fragments were placed on a slide and squashed , and the coverslip removed after freezing in liquid nitrogen . Samples were washed with 1× PBS and stored up to 4 days before use . We employed established experimental approaches for the visualization of chromosomes in both structurally-preserved nuclei ( seminiferous tubules squashes ) and surface spreads [47] . Incubations with primary antibodies were carried out for 1 h at room temperature in 1× PBS plus BSA 2% . To detect SYCP1 and SYCP3 we used polyclonal rabbit antibody raised against mouse SYCP1 at 1∶200 dilution ( Novus Biologicals ) and polyclonal mouse antibody raised against mouse SYCP3 at 1∶300 dilution ( ABcam ) . Centromeres were detected using the human centromere protein antibody ( CREST , Antibody Incorporated ) at 1∶50 dilution . Other primary antibodies used in this study were as follows: polyclonal mouse antibody raised against human AURORA B at 1∶50 dilution , polyclonal rabbit antibody raised against human PLK 1 at 1∶50 dilution ( Upstate ) , polyclonal mouse antibody raised against human BUB1 at 1∶50 dilution ( a gift from S . Taylor [48] ) , polyclonal mouse antibody raised against human CDC20 at 1∶50 dilution ( a gift from J . Weinstein [49] ) . Following three washes in 1× PBS , slides were incubated for 1 h at room temperature with secondary antibodies . A combination of fluorescein isothiocyanate ( FITC ) -conjugated goat anti-rabbit IgG ( Jackson laboratories ) with Rhodamine-conjugated goat anti-mouse IgG and Cy5-conjugated goat anti-human IgG each diluted 1∶250 were used for simultaneous triple immunolabeling . Slides were subsequently counterstained for 3 min with 2 µg/ml DAPI containing Vectashield mounting solution ( Vector Laboratories ) and sealed with nail varnish . For CREST and RAP1 focus counts , nuclei were staged using the extent of SYCP3 staining and synapsis as markers for meiotic prophase progression . Quantification of co-localizing CREST with SYCP1 , SYCE1 and TEX12 were carried out by superimposing images of the corresponding fluorescent channels in a single plane image . When two CREST foci were observed together without any gap in between them , we considered those signals as two distinct foci . We use Axiovision SE 64 ( Carl Zeiss , inc . ) for imaging acquisition and processing . Statistical tests were as described in the table legend .
|
Meiosis is the key developmental program of gametogenesis during which haploid gametes are generated to cope with the doubling chromosome number that occurs after fertilization . During the first meiotic division , homologous chromosomes pair , recombine , and dissociate . Errors in any of these processes are commonly linked to human infertility , spontaneous abortions , and severe aneuploidy-based birth defects . Chiasmata , the cytological manifestations of recombination , provide a physical link that holds the homologous maternal and paternal chromosomes in pairs , facilitating their segregation , and that guarantees each gamete receives only one copy of each chromosome . Recently , however , studies in lower eukaryotes have suggested that , in the absence of recombination , pairing between centromeric regions promotes proper segregation of these non-recombined meiotic homologous chromosomes and contributes significantly to the segregation fidelity of chromosomes that have recombined . We show here that the SYCP1 and SYCP3 proteins are required for centromere pairing in mouse . Our findings define structures and possible mechanisms of a process that was not previously known to occur in mammals , which may act to insure that the correct numbers of chromosomes are transferred to the next generation .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"medicine",
"meiosis",
"molecular",
"cell",
"biology",
"chromosome",
"biology",
"nucleic",
"acids",
"centromeres",
"dna",
"recombination",
"dna",
"biology",
"genomics",
"molecular",
"biology",
"genetics",
"and",
"genomics"
] |
2012
|
Synaptonemal Complex Components Persist at Centromeres and Are Required for Homologous Centromere Pairing in Mouse Spermatocytes
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Cowpea mosaic virus ( CPMV ) is a plant comovirus in the picornavirus superfamily , and is used for a wide variety of biomedical and material science applications . Although its replication is restricted to plants , CPMV binds to and enters mammalian cells , including endothelial cells and particularly tumor neovascular endothelium in vivo . This natural capacity has lead to the use of CPMV as a sensor for intravital imaging of vascular development . Binding of CPMV to endothelial cells occurs via interaction with a 54 kD cell-surface protein , but this protein has not previously been identified . Here we identify the CPMV binding protein as a cell-surface form of the intermediate filament vimentin . The CPMV-vimentin interaction was established using proteomic screens and confirmed by direct interaction of CPMV with purified vimentin , as well as inhibition in a vimentin-knockout cell line . Vimentin and CPMV were also co-localized in vascular endothelium of mouse and rat in vivo . Together these studies indicate that surface vimentin mediates binding and may lead to internalization of CPMV in vivo , establishing surface vimentin as an important vascular endothelial ligand for nanoparticle targeting to tumors . These results also establish vimentin as a ligand for picornaviruses in both the plant and animal kingdoms of life . Since bacterial pathogens and several other classes of viruses also bind to surface vimentin , these studies suggest a common role for surface vimentin in pathogen transmission .
Cowpea mosaic virus ( CPMV ) is a member of the comoviridae family of plant viruses . The 31 nm-diameter capsid has a pseudo T = 3 symmetry composed of 3 beta-barrel domains formed from 2 capsid proteins , and is structurally related to animal picornaviruses that include such viruses as poliovirus , coxsackievirus , and Theiler's murine encephalomyelitis virus ( TMEV ) [1] . Within the picornavirus-like superfamily these viruses also share a similar genetic organization and along with CPMV are thought to derive from a common ancestor [2] , [3] . The mechanisms of evolution of the picorna-like viruses within the kingdoms of life , and possible cross-kingdom transmission during evolution , are unknown . In addition to its role as a plant pathogen , CPMV has received recent attention as a nanoscale scaffold for the design of vaccines and therapeutics [4]–[7] . The ability to generate nanoscale materials that can specifically target and image sites of disease is an important goal in biomedicine . A variety of nanoparticle strategies have been developed for targeting and imaging in vivo including antibodies [8] , dendrimers [9] , liposomes [10] , nanoshells [11] , quantum dots [12] , and viruses [13] , [14] . Viruses are particularly suited for these applications because they are naturally designed for efficient circulation and specific ligand-binding and cellular internalization . Recently interest has turned toward self-assembling plant viruses , bacteriophages [4] , and protein cage [15] architectures that can be adapted for in vivo targeting purposes without the pathogenic properties of animal viruses . However these viruses must generally be tailored to recognize their targets using specific ligands . As a nanoparticle , CPMV is a robust biomaterial that is systemically bioavailable through both oral and intravenous inoculation [16] . These properties have been integral to its use as a vaccine platform [17]–[19] . CPMV has also been studied for materials applications such as multilayer assembly and chemical scaffolds [20] . Recent studies have also shown that CPMV can be chemically modified with specific ligands to achieve tumor-specific targeting [14] . Although the host range for CPMV replication is restricted to plants , interestingly the unmodified CPMV capsid also naturally interacts with mammalian cells . Intravital imaging studies using fluorescently-labeled CPMV particles yielded high-resolution images of normal and tumor vasculature in vivo [13] . These imaging studies showed that CPMV particles were readily internalized in mouse and chick endothelial cells following intravenous administration in living embryos , and this internalization produced high-resolution images of vasculature in real-time using epifluorescence microscopy [13] . Tumor neovasculature in particular was labeled very strongly by CPMV , and differential internalization by arterial and venous vessels was also observed , however the mechanism of uptake was unknown [13] . We subsequently determined that CPMV binding is mediated by a specific interaction between CPMV and a surface-exposed , non-glycosylated 54 kD binding protein that is present on a variety of mammalian cells including human umbilical vein endothelial cells ( HUVEC ) [21] . Since the interaction between CPMV and the 54 kD protein correlated with such high-resolution intravital vascular images , we reasoned that identifying the 54 kD CPMV attachment protein would potentially reveal a useful endothelial marker for vascular imaging . We also hypothesized that understanding the mechanism of CPMV attachment to mammalian cells would provide important information regarding the relationships between plant and animal picornaviruses . Thus the aim of this study was to identify and characterize the 54 kD CPMV binding protein ( CPMV-BP ) using proteomics , biochemical assays , flow cytometry , and fluorescence confocal microscopy .
To identify the 54 kD CPMV-BP , a proteomics study was performed using liquid chromatography and tandem mass spectrometry ( LC-MS/MS ) . The 54 kD protein is found in the plasma membrane-enriched fraction of cells , lacks N- and O-glycosylation , and was identified by its ability to bind directly to CPMV particles using a Virus Overlay Protein Blot Assay ( VOPBA ) [21] . The VOPBA technique has identified many high-affinity virus receptors including those for coronaviruses [22] , [23] , adenoviruses [24] , and arenaviruses [25] . Mass spectrometry analysis focused first on enriched plasma membrane proteins that co-migrated with the 54 kD band on SDS-PAGE; this resulted in identification of 68 individual proteins ( Table 1 ) . Surface biotinylation of cells , followed by isolation of enriched plasma membranes and streptavidin-sepharose purification of biotinylated proteins , separation on SDS-PAGE and VOPBA , yielded a sample in the 54 kD range that was also analyzed by LC-MS/MS and yielded 7 proteins ( Table 1 ) . The third approach used the enriched plasma membrane fraction as starting material ( Figure 1A ) followed by sequential column chromatography ( Figure 1B ) . Here the membrane fraction was first run over a concanavalin A-sepharose column to remove glycoproteins , and the flow-through fraction was bound to an affinity matrix that was generated when surface lysine residues on purified CPMV particles were directly conjugated to N-hydroxysuccinimidyl ester-sepharose ( CPMV-sepharose ) . The CPMV-bound sample was washed several times , and then CPMV-sepharose beads were pelleted by centrifugation and bound proteins separated on SDS-PAGE ( Figure 1C ) . Three bands were easily visible by SimplyBlue ( Invitrogen ) staining , corresponding to the 54 kD CPMV-BP , the 42 kD large capsid subunit of CPMV , and the 24 kD small CPMV capsid subunit . The 54 kD band was excised from the gel , digested with trypsin , and analyzed by LC-MS/MS using nano-electrospray on a linear ion trap mass spectrometer ( Figure 1D ) . In this analysis two proteins were positively identified: vimentin and keratin . Keratin is a common laboratory contaminant that is isobaric with vimentin . Vimentin was also identified in all the preceding mass spectrometry analyses ( Table 1 ) . A complete listing of all proteins identified in each screen can be seen in Table S1 . Vimentin is a type III intermediate filament and a major component of the cytoskeleton . Expressed in cells of mesenchymal origin , vimentin plays a key role in intracellular dynamics and architecture [26] . Vimentin encodes head , rod , and tail domains , and these domains are identified based on sequence and function [26] . Although it has long been considered a cytosolic protein , surface-expressed forms of vimentin have recently been discovered on several cell types including apoptotic neutrophils and T cells [27] , [28] , activated macrophages [29] , platelets [30] , vascular endothelial cells [31] , brain microvascular endothelial cells [32] , Sezary T cells [33] , and skeletal muscle cells [32] . The mechanism by which vimentin reaches the cell surface , which domains are exposed , and its function at the surface , remain unknown . To evaluate whether surface-expressed or membrane associated vimentin interacted specifically with CPMV , VOPBA ( Figure 2A ) and western blotting ( Figure 2B ) were used to probe the interaction . Since vascular endothelial cells are known to internalize CPMV in vivo [13] , enriched plasma membrane proteins isolated from HUVEC were used as a positive control ( lane 1 ) , along with HeLa and KB tumor cells ( lanes 2 and 3 ) [21] . All cells contained the 54 kD band when probed with CPMV particles by VOPBA ( Figure 2A ) . Significant signal could be observed even when incubating the virus with membrane for as little as 5 minutes . Mouse embryo fibroblasts derived from knockout mice lacking the vimentin gene ( vim−/− , MFT-16; lane 5 ) [34] , [35] were negative for the 54 kD CPMV-interacting band , while membranes isolated from control vim+/+ fibroblasts ( MFT-6; lane 4 ) contained the 54 kD protein and bound CPMV by VOPBA . CPMV also bound to purified recombinant vimentin protein ( lane 7 ) , which migrated at the expected molecular weight . Expression of vimentin in the cell lines as detected by western blot using anti-vimentin antibodies ( Figure 2B ) correlated directly with binding of CPMV in VOPBA . CPMV capsid proteins were also included on the gels ( Figure 2A , lane 6 ) as a positive control in the VOPBA for detection by CPMV-specific polyclonal antibodies . As expected CPMV capsid proteins did not react with anti-vimentin antibodies in the western ( Figure 2B , lane 6; in addition , a loading control for the VOPBA and western blot samples is provided in Figure S1 ) . Together these results demonstrate that vimentin is present in the enriched plasma membrane fraction of human cells and binds directly to CPMV . The specificity of the vimentin-CPMV interaction was further probed in ELISA format . Purified protein ( vimentin , BSA , or no protein control ) was coated on ELISA plate wells overnight , and then incubated with varying concentrations of purified CPMV particles for one hour , followed by anti-CPMV polyclonal antibody and an alkaline-phosphatase conjugated secondary antibody ( Figure 2C ) . CPMV bound specifically to vimentin immobilized on the plates at an EC50 of 3 . 72 nM of CPMV . Binding affinities that have been established for other picornavirus-receptor interactions range from 100 nM to 10 µM [36]–[38] . It is important to note that the 3 . 72 nM value does not represent the KD of the CPMV-vimentin interaction , because ELISA assay does not rule out the role of avidity in binding . Nevertheless , this experiment further demonstrates a direct and specific interaction between CPMV and vimentin . CPMV binding could also be competed by vimentin-specific antibodies ( Figure S2 ) . The capacity of cell surface-expressed vimentin to mediate interactions with CPMV was further probed by flow cytometry at 37°C . Cells were incubated with CPMV for 30 minutes , fixed , and the amount of associated CPMV was detected with a CPMV-specific polyclonal antibody . HeLa and MFT-6 vim+/+ cells were capable of binding or internalizing CPMV , while MFT-16 vim−/− cells could not ( Figure 3 ) . Since CPMV does not replicate in mammalian cells , the virus detected represents input virus particles only . In order to determine whether complementing vimentin expression in MFT-16 vim−/− cells would increase the CPMV interaction , these cells were transfected with vimentin cDNA . Although MFT-16 vim−/− cells had low transfection efficiencies ( ranging from 0 . 1 to 8 . 0% of cells using a GFP-reporter plasmid , not shown ) , in the cell population that was transfected with vimentin , a statistically significant ( p = 0 . 036 ) increase in CPMV binding or uptake was observed when compared to mock-transfected MFT-16 cells . On average 1 . 21% of vimentin-transfected MFT-16 vim−/− cells were CPMV-positive ( data not shown ) . For comparison , under identical conditions 5 . 36% of mock-transfected HeLa cells were CPMV positive ( data not shown ) . Together these results demonstrate that the lack of CPMV binding observed in vimentin-null cells can be complemented by vimentin expression . To further test the specificity of CPMV for surface-expressed vimentin in cells , antibody-blocking studies were performed . HeLa cells were incubated with various vimentin domain-specific antibodies at varying concentrations for 30 minutes , followed by a 30-minute incubation with CPMV under the identical growth conditions , and CPMV detected as described before . Anti-vimentin monoclonal antibody V9 that targets the tail domain was best at reducing CPMV binding , however , all antibodies did provide some blocking of CPMV binding or entry ( Table 2 ) . This inhibition is not complete , suggesting that either the monoclonal or polyclonal antibodies do not bind directly to the CPMV-interacting domains , that additional cell-surface interactions participate in CPMV binding , or that particular domains of vimentin may be more surface-exposed than other domains . To further correlate CPMV uptake with surface-vimentin expression in cell culture , HeLa cells were examined for surface vimentin by confocal microscopy and flow cytometry . Surface vimentin staining ( Figure 4A ) was shown to be markedly distinct from controls ( Figure 4B and 4C ) and internal vimentin staining ( Figure 4D ) . The surface vimentin expression pattern observed in HeLa cells is virtually identical to confocal observation of surface vimentin expression previously reported in macrophages [29] . Fixation and staining procedures to verify cell surface and cytosolic staining were verified through the ability to detect β-COP , an intra-Golgi transport marker ( Figure S3 ) . Approximately 50% of HeLa cells exhibited surface vimentin expression by confocal microscopy , and surface vimentin expression was also quantified by flow cytometry when HeLa cells were stained using an anti-vimentin antibody ( Figure S4 ) . These data correlated with CPMV binding or uptake by flow cytometry ( Figure 4E ) . CPMV-positive cells were observed within the surface-vimentin-expressing population in FACS ( 41 . 3% of the total population ) , although not all of these cells interacted with significant quantities of CPMV . The apparent CPMV binding of a few cells expressing surface vimentin at low levels was attributed to background staining ( Figure S5 ) . Since we do not fully understand the expression , display , function , and availability of surface vimentin or its CPMV binding epitope it is difficult to hypothesize why some surface vimentin expressing cells are not also positive for CPMV . Nevertheless it is clear that surface vimentin is a prerequisite for CPMV interactions at the cell surface . The interaction between CPMV and surface vimentin was then examined in animals . We first confirmed our previous results that CPMV interacts specifically with endothelial cells in vivo by staining with the CD31 marker . To this end , a mouse was intravenously injected with CPMV-A555 , and after one hour the mouse was anesthetized , the aorta perfused with PBS and removed . The freshly isolated aorta was then incubated with antibodies recognizing the endothelial marker CD31/PECAM ex vivo , and under fluorescent microscopic observation there was strong co-localization between the CD31-expressing endothelial cells and CPMV ( Figure S6 ) . Next , studies to co-localize CPMV and surface vimentin were performed . It had previously been suggested that vimentin is expressed on the lumenal surface of vascular endothelial cells , in particular by identification of the endothelial-specific PAL-E antibody ( although the specificity of this antibody for vimentin is controversial ) [31] . Because the expression of murine vimentin is not efficiently recognized by the V9 mAb , we used rats for our studies to co-localize vimentin and CPMV in vivo . In order to focus on surface vimentin displayed on the lumenal surface of vascular endothelium rather than cytosolic vimentin , cylinder-shaped rat aorta segments were excised , and prior to sectioning were incubated with CPMV-A555 or V9 mAb , washed , and then embedded in OCT medium and 10 µm cryosections prepared . The sections were then stained with a secondary anti-mouse antibody . The expression of vimentin was observed on the lumenal surface of aortic endothelium , and co-localized with CPMV binding ( Figure 4F–J , and Figure S7 ) . The colocalization of CPMV and vimentin in vessels correlated with the observed vascular endothelial uptake of CPMV in vivo ( Figure S6 and [13] ) . Specificity of the staining procedure was also confirmed ( Figure S8 ) . There was no CPMV colocalization outside of the endothelial cell marker ( Figure S6 ) , or outside the surface vimentin expressing cells ( Figure 4F–J ) . Taken together , the CPMV colocalization with vascular endothelium , the CPMV interaction with living vasculature shown previously through intravital imaging [13] , and our current results indicating that surface vimentin facilitates this interaction , illustrates that endothelial cell targeting of CPMV is mediated via vimentin .
Together these studies identify the 54 kD protein that mediates binding of CPMV in mammalian cells as surface vimentin . These results demonstrate that CPMV is a useful nanoparticle probe for examining the expression of surface vimentin on endothelial cells and circulating cells in vivo . The ability of CPMV to efficiently visualize tumor neovasculature and differentiate arterial from venous tissues [13] may now be attributed to upregulation of surface vimentin . Upregulation of cytosolic vimentin has long been associated with tumor progression and metastasis during the epithelial-mesenchymal transition ( EMT ) [39] , however our findings suggest that increased surface vimentin is also a key feature of tumor endothelium as evident by ability of CPMV to preferentially image these areas [13] and may signal a role for surface vimentin in tumor metastasis or invasion , in addition to cellular adhesion and stress . The use of CPMV as a natural endothelial probe may also extend into the investigation of other vascular diseases such as atherosclerosis . Finally , the CPMV-vimentin interaction may provide a tool for understanding the display and internalization of surface-expressed vimentin , the mechanism and function of which is currently unknown . It is also not clear whether the CPMV-vimentin interaction is important for virion movement in its host plant species . CPMV is not known to be dependent on cellular receptors for cell-cell spread; rather like many plant viruses CPMV encodes a movement protein ( MP ) that mediates movement of virus particles within leaf tissue via the plasmodesmata [40] , [41] . The mechanism of CPMV loading and unloading from the plant host's vascular elements is not understood [42] . Access to plant vascular tissues may be mediated by direct virus capsid-cellular interactions independent of MP , and intermediate filament-like proteins may play a role in the vascular tropism of CPMV in plants . Interestingly the animal picornavirus TMEV has also been shown to interact directly with vimentin using a similar VOPBA strategy with isolated enriched plasma membrane proteins [43] . Coupled with our findings , this further strengthens the link between animal and plant picornaviruses not only structurally and genetically , but with regard to attachment mechanisms as well . The original characterization of CPMV bioavailability was performed following oral administration of virus or infected leaves , whereby virus was subsequently found in the blood circulation [16] . The stability of CPMV in the gastrointestinal tract and its subsequent systemic biodistribution provides an opportunity for interactions between CPMV and mammalian cells following ingestion [16] . While there is no evidence for CPMV replication in mammalian or avian cells , the conserved interaction with vimentin , coupled with the conserved capsid structures of the plant , insect and animal picornaviruses , supports the hypothesis that the picornavirus superfamily of viruses evolved from a common ancestor . The identification of conserved mechanisms of attachment and entry also point to a possible mode of cross-kingdom transmission . Other roles for vimentin during the picornavirus replication cycle include reorganization of cytosolic vimentin into cages that enclose autophagic vesicles at intracellular replication centers by TMEV and poliovirus [43]–[45] . The picornavirus encephalomyocarditis virus ( EMCV ) further induces an autoimmune response against vimentin after infection [46] . In addition to picornaviruses , several other pathogens use vimentin as a component of the cellular attachment mechanism , suggesting a conserved role for surface vimentin as a more general attachment factor for pathogen entry . These include mammalian porcine reproductive and respiratory syndrome virus ( PRRSV ) , which uses surface vimentin for cellular entry [47] . Bacteria such as Escherichia coli also interact with surface vimentin to mediate cellular attachment via the invasion factor IbeA [48] . Finally , upregulation of surface vimentin on injured skeletal muscle cells was recently shown to be a ligand for attachment of group A streptococci ( GAS ) and was associated with streptococcal toxic shock syndrome [32] . Together these studies highlight an increasingly important role for surface vimentin as a conserved component of pathogen attachment and internalization pathways , and suggest that disruption of these interactions may serve as broad-spectrum antimicrobial strategies .
HeLa cells were grown and maintained in DMEM media supplemented with 7% heat-inactivated fetal bovine serum ( ΔFBS ) , 50 units/mL penicillin , 50 units/mL streptomycin , and 2 mM L-glutamine . Murine Balb Cl 7 cells were grown and maintained in MEM media supplemented with 7% ΔFBS , 50 units/mL penicillin , 50 units/mL streptomycin , and 2 mM L-glutamine . HUVEC cells were grown and maintained using Endothelial Cell Growth Media Bulletkit ( Cambrex ) . KB cells were grown and maintained in MEM media supplemented with 10% ΔFBS , 50 units/mL penicillin , 50 units/mL streptomycin , and 2 mM L-glutamine . MFT-6 and MFT-16 cells ( a generous gift from Dr . Robert Evans , University of Colorado Health Sciences Center ) were grown and maintained in 1∶1 DMEM and F-12 HAMS medias supplemented with 50 units/mL penicillin , 50 units/mL streptomycin , 2 mM L-glutamine , and 5% and 9% ΔFBS respectively . All cells were grown at 37°C in 5% CO2/95% air humidified atmosphere . CPMV was grown , isolated , and when needed fluorescently labeled with AlexaFluor 488 or AlexaFluor 555 carboxylic acid , succinimidyl ester ( Invitrogen ) as described previously [13] . Labeled virus was calculated to have 65 AlexaFluor 488 molecules per virion or 55 AlexaFluor 555 per virion . Rabbit polyclonal anti-CPMV antibody was generated as previously described [21] . Antibodies against vimentin were rabbit polyclonal H-84 ( Santa Cruz Biotechnology ) , mouse monoclonal 3B4 ( Chemicon ) , whole goat antiserum V 4630 ( Sigma ) and mouse monoclonal IgG1 V9 ( Sigma ) . Primary rat monoclonal anti-PECAM ( CD31 ) was purchased from BD Biosciences . Secondary antibodies were donkey anti-goat IgG-HRP ( Santa Cruz Biotechnology ) , goat anti-rabbit IgG-HRP ( Pierce ) , goat anti-mouse Alexafluor 488 conjugated antibody ( Invitrogen ) , goat anti-rabbit Alexafluor 488 conjugated antibody ( Invitrogen ) , goat anti-mouse Alexafluor 647 conjugated antibody ( Invitrogen ) and goat anti-rat Alexafluor 488 conjugated antibody ( Invitrogen ) . IgG1 isotype control was purchased from BD Biosciences and donkey biotinylated anti-rabbit IgG antibody from Amersham Biosciences . Cell lines were propagated and enriched plasma membranes isolated and stored in 10 mM Tris/HCl , pH 8 . 0 , 10 µg/mL aprotinin and leupeptin ( Roche ) , and 0 . 5% n-octyl-β-D-glycopyranoside ( Sigma ) as described previously [21] . The surface membrane-impermeable biotinylation of cells surface proteins and isolation was performed using the Cell Surface Protein Isolation Kit ( Pierce ) as directed by the manufacturer . To create CPMV-sepharose beads , 100 µl of NHS-activated Sepharose 4 Fast Flow ( Amersham Biosciences ) beads were washed with 1 mL of 1 mM HCl for 5 minutes at 4°C . HCl solution was removed and 18 mL of 0 . 1 M KPO4 , pH 7 . 0 was added . 2 mL of 15 mg/mL CPMV in 0 . 1 M KPO4 , pH 7 . 0 was added to NHS-activated sepharose already in solution . This mixture was rotated slowly on a LabQuake rotator ( Cardinal Health ) at room temperature for 2 hours . The mixture was centrifuged for 2 minutes at 100 g to pellet beads and remove excess solution . 20 mL of 0 . 1 M Tris/HCl , pH 8 . 0 was then added and put on slow rotation using the LabQuake rotator overnight at room temperature to hydrolyze unreacted NHS-esters . The resultant CPMV-sepharose beads were then extensively washed with 0 . 1 M KPO4 , pH 7 . 0 . 10 µg of enriched plasma membrane protein isolates , from respective cell lines , were run on 4–12% Bis-Tris 1 . 0 mm NuPAGE gel ( Invitrogen ) unless otherwise specified . Proteins samples were then transferred electrophoretically to Immobilon-P transfer membranes ( Millipore ) . Transfer membranes were then blocked overnight with 5% w/v milk solution . The membranes were then washed 4 times for 5 minutes each with wash buffer consisting of PBS with 0 . 2% Triton X-100 ( Sigma ) . All antibodies and viral suspensions were diluted in wash buffer . For western blotting , samples were subject to one hour incubation with anti-vimentin whole goat antiserum V 4630 , washed 4 times with wash buffer for 5 minutes each , then incubated one hour with donkey anti-goat IgG-HRP , washed 4 times with wash buffer for 5 minutes each , visualized with chemiluminescence detection ( SuperSignal; Pierce ) and exposed to CL-XPosure film ( Pierce ) . For VOPBA , samples were subject to one hour incubation with 10 µg/mL CPMV in 1% milk solution with 5% glycerol , washed 4 times with wash buffer for 5 minutes each , then subject to one hour incubation with anti-CPMV polyclonal antibody , washed 4 times with wash buffer for 5 minutes each , then incubated one hour with goat anti-rabbit IgG-HRP , washed 4 times with wash buffer for 5 minutes each , visualized with chemiluminescence detection ( SuperSignal; Pierce ) and exposed to CL-Xpossure film ( Pierce ) . The excised gel bands for proteomic analysis were treated with 10 mM dithiothrietol to reduce disulfide linkages . Alkylation was performed with 55 mM iodoacetamide ( Sigma-Aldrich ) before digestion with trypsin ( Promega ) over night at 37°C using an estimated ( 1∶30 ) enzyme to substrate ratio in 50 mM ammonium bicarbonate . The liquid chromatography separation was performed on a laser pulled 100 µm ID C18 column with a tip of <5 µm that is also used as a nanoelectrospray emitter . An Agilent 1100 HPLC system equipped with a nanopump was used to perform the gradient elution at a flow rate of 300 nL/min with 0 . 1% formic acid/acetonitrile as the mobile phases , from 5% to 35% acetonitrile in 100 minutes , then up to 90% acetonitrile for 15 minutes . The MS/MS analysis was performed on a LTQ linear ion trap mass spectrometer ( Thermo Electron Corp . ) , as well as an Agilent LC/MSD Trap ion trap mass spectrometer . Data-dependent scanning was used to maximize the number of peptides sequenced in the highly complex mixture . This mode of operation uses preset criteria to select unique peptides on-the-fly for undergoing MS/MS . Over 10 , 000 MS/MS spectra were obtained during the runs . These were searched using MASCOT ( Matrix Science , Limited ) with the Sprot protein database . To improve searching efficiency , taxonomic category was limited to rodent proteins . Only peptides producing good quality fragmentation spectra and scoring higher than the threshold required for 95% confidence level for Mascot were used for protein identification . A protein identification was only validated if two or more peptides were identified with ion scores needed for 95% confidence level . One µg of vimentin , BSA or no protein at all , was suspended in 150 µL 0 . 1 M KPO4 pH 7 . 0 , was immobilized overnight in 96-well Immulon 2 HB plates ( Thermo ) . During the immobilization , plates were kept at room temperature and in buffer humidified containers . The next morning the protein solutions were discard and wells blocked for 2 hours at room temperature with 300 µL of 3% milk solution in 0 . 1 M TBS pH 7 . 3 with 0 . 05% Tween 20 . All washes were completed with 0 . 1 M TBS pH 7 . 3 with 0 . 05% Tween 20 , all viral and antibody dilutions were made in 150 µL 0 . 1 M KPO4 pH 7 . 0 and all incubations took place at room temperature unless specifically stated . After blocking wells they were washed and appropriate molar concentrations of virus were added to each well . For “no protein” wells the same amount of virus was used as was used in the vimentin wells . Viral incubations lasted 1 hour , was followed by 3 washes and 1 hour incubation with rabbit anti-CPMV polyclonal antibody . This was followed by 3 washes and 1 hour incubation with donkey biotinylated anti-rabbit IgG antibody . Then this was followed by 3 washes and 1 hour incubation with streptavidin-alkaline phosphatase ( Amersham Bioscience ) . Another 3 washes were completed and p-nitriphenyl phosphate ( Sigma ) was incubated for 20 minutes at 37°C or until the negative control started to barely change color . The reaction was stopped by addition of 2N NaOH for 10 minutes at room temperature . Signal was recorded at 405 nm on a VERSAmax tunable microplate reader ( Molecular Devices ) . All experiments were repeated in triplicate with average and standard deviation reported . To detect CPMV interactions cells were dissociated from growth flask using Hanks'-Based , Enzyme Free , Cell Dissociation Buffer ( Invitrogen ) , counted and resuspended in their respective growth media . These cells were then aliquoted into 96-well V-bottom plates . Plates were spun to collect cells after each addition of virus , fixative , antibody or washing . Cells were then incubated with wildtype CPMV in a ratio of 1×105 virions per cell ( V/C ) for 30 minutes at 37°C . Cell were washed three times with FACS buffer consisting of PBS , 1 mM EDTA , 25 mM HEPES and 1% FBS at pH 7 . 0 . Cells were fixed for 15 minutes with 2% formaldehyde in PBS and then washed three times with FACS buffer . Cells were then washed once with FACS buffer containing 0 . 5% saponin ( Sigma ) also called permeablization buffer ( PB ) . Cells were then incubated with rabbit polyclonal anti-CPMV antibody diluted in PB for one hour at room temperature and then washed three times with PB . Secondary goat anti-rabbit Alexafluor 488 conjugated antibody was diluted in PB and incubated with the cells for one hour at room temperature in the dark . Cells were washed a final three times with FACS buffer , fluorescence quantitated with a LSR-II Digital Flow Cytometer ( BD Biosciences ) and data analyzed used FlowJo software ( Tree Star Inc . ) . For antibody blocking experiment after HeLa cells were aliquoted they were incubated with varying concentrations ( 1∶50 , 1∶100 , 1∶500 or no antibody ) of H-84 , 3B4 , V4630 or V9 antibody for 30 minutes at 37°C , then addition of AlexaFluor 488 labeled virus for 30 minutes at 37°C and procedure continued as discussed above . For in vitro CPMV binding or internalization and surface vimentin staining flow cytometry the same procedure was used except: AlexaFluor 488 labeled virus was used , no PB was used and surface vimentin analyzed through use of V9 anti-vimentin monoclonal antibody in place of rabbit polyclonal anti-CPMV polyclonal antibody and secondary goat anti-rabbit Alexafluor 488 conjugated antibody replaced with goat anti-mouse Alexafluor 647 conjugated antibody . For surface vimentin staining in Figure S4 cells were fixed , not permeablized , and staining using V9 anti-vimentin or mouse IgG1 isotype control and goat anti-mouse Alexafluor 647 conjugated antibody as discussed above . For each experiment at least 10 , 000 events were collected and were repeated in at least triplicate with average and standard deviations calculated in Microsoft Excel and reported . The night before transfection 500 , 000 cells were seeded in 2 mL of growth media in 6-well plates and grown overnight to 90–95% confluence at 37°C in a 5% CO2/95% air humidified atmosphere . For each well of cells 4 µg of pCMV-SPORT6-vimentin ( Open Biosystems ) , a vimentin plasmid with CMV promoter , or no DNA ( mock transfection ) was diluted in 250 µl of transfection media ( growth media without ΔFBS or antibiotics ) . For each well 10 µl of Transfectin ( Biorad ) was diluted in 250 µl of transfection media , and incubate at room temp for 5 minutes . The diluted DNA and Transfectin was combined , mixed gently , and incubated at room temperature for 20 minutes . Growth media was aspirated from cells , and cells washed twice with PBS . The combined DNA and Transfectin was added dropwise to the well of cells and returned to 37°C in a 5% CO2/95% air humidified atmosphere . After 4 to 6 hours DNA/Transfectin mixture was aspirated off cells , cells washed twice with PBS , and 2 mL of growth media added to cells . Cells were returned to 37°C in a 5% CO2/95% air humidified atmosphere for 24 hours . Cells were removed from wells using Hanks'-Based , Enzyme Free , Cell Dissociation Buffer , counted and 500 , 000 cells placed in wells of a V-bottom 96-well plate . In V-bottom wells cells were then incubated with wildtype CPMV at 5×105 V/C or no virus for 2 hours . CPMV interaction was measured using the flow cytometry procedure listed above . Transfection efficiency varied per experiment ranging from 0 . 1 to 8% efficiency . Transfection efficiency was measured through permeablization of cells and identification of vimentin expression using V9 anti-vimentin monoclonal antibody and goat anti-mouse Alexafluor 647 conjugated antibody while using PB buffer in flow cytometry preparation listed above . All transfections were repeated in triplicate . HeLa cells were seeded in a 12-well plate containing 12 mm sterile glass cover slips at 5×104 cells/well and grown for 48 hours in RPMI1640 medium containing 10% ΔFBS , 50 units/mL penicillin , 50 units/mL streptomycin , and 2 mM L-glutamine at 37°C in a 5% CO2/95% air humidified atmosphere . On the day of the experiment , cells were fixed using 3% paraformaldehyde , 0 . 3% gluteraldeyde , 1 mM MgCl2 in PBS for 10 minutes . After 4 washes with PBS buffer , only the cells that were to be intracellularly stained , were permeabilized using 0 . 2% Triton X-100 in PBS for 2 minutes . Non-specific binding was blocked by incubating the cells in 5% goat serum in PBS for 1 hour . Incubations with either mouse monoclonal anti-vimentin V9 antibody , rabbit polyclonal anti-β-COP ( Affinity Bioreagents ) or purified mouse IgG1 isotype control were performed at room temperature for 45 minutes with gentle agitation . Unbound antibody was then removed by washing four times with PBS . Goat anti-mouse IgG AlexaFluor 555 conjugated antibody ( Invitrogen ) or goat anti-rabbit IgG AlexaFluor 488 conjugated antibody ( Invitrogen ) were added appropriately in 1% goat serum in PBS , and cells were gently agitated for a further 45 minutes . During the last five minutes of secondary antibody incubation , cell nuclei were stained by adding 100 µL of 4′ , 6-diamidino-2-phenylindole ( DAPI 1∶1000 dilution in water ) . Cells were then washed 4 times using PBS and cover slips covered with cells were mounted on slides using Vecta Shield mounting medium ( Vector Laboratories ) . Cells were imaged using a Bio-Rad ( Zeiss ) Radiance 2100 Rainbow laser scanning confocal microscope equipped with 60× oil-immersion objective . Animals used in this study were Harlan Sprague-Dawley male rats obtained from Charles River Inc . Animals were used in compliance with Institutional Animal Care and Use Committee ( IACUC ) approved protocols . On the day of the experiment , rats were anesthetized and the aorta perfused with ice-cold PBS for 10 minutes via the left ventricle . The aorta was then removed by cutting off minor branching arteries and rinsed in ice-cold PBS to remove adhering blood components . Aorta transverse segments were obtained and incubations with either mouse monoclonal anti-vimentin V9 antibody , purified mouse IgG1 isotype control , CPMV labeled with Alexafluor 555 ( 20 µg ) , or a combination of V9 and labeled virus were performed at 4C for 1 hr in the dark . V9 antibody was diluted 1 to 40 in 2% natural goat serum , 1% BSA in PBS . Incubation with IgG1 isotype control was performed so that the same amount of antibody as for V9 was used . The segments were then washed 3 times with ice-cold PBS in the dark and embedded in OCT ( Tissue-Tek ) . 10 µm sections were obtained using a Leica CM1850 cryostat , collected on glass slides and fixed in ice-cold 95% ethanol for 30 minutes at 4C . After rinsing the slides with PBS , goat anti-mouse Alexafluor 488 conjugated antibody was added for 1 hr in the dark . In the last ten minutes of secondary antibody incubation , nuclei were stained using 4′ , 6-diamino-2-phenylindole ( DAPI ) . Slides were then washed 4 times with PBS and mounted using Vecta Shield mounting medium . Aorta segments were imaged using a Bio-Rad ( Zeiss ) Radiance 2100 Rainbow laser scanning confocal microscope equipped with 60× oil-immersion objective . C57Bl/6J mice ( rodent breeding colony , TSRI ) were used in accordance with IACUC approved protocols . On the day of the experiment , mice were inoculated intravenously using 500 µg of CPMV labeled with Alexafluor 555 . After 1 hour the mice were anesthetized and the aorta perfused with ice-cold PBS for 10 minutes via the left ventricle . The aorta was then removed by cutting off minor branching arteries and rinsed in ice-cold PBS to remove adhering blood components . Aorta transverse segments were obtained and embedded in OCT . 10 µm sections were obtained using a Leica CM1850 cryostat , collected on glass slides and fixed in ice-cold 95% ethanol for 30 minutes at 4C . After rinsing the slides with PBS , blocking was performed using 10% natural goat serum in PBS for 30 minutes . The sections were then incubated with PECAM ( CD31 ) primary antibody in 5% goat serum in PBS . After 1 hour , slides were washed four times in PBS . Goat anti-rat Alexafluor 488 conjugated secondary antibody was then added in 5% goat serum in PBS . In the last ten minutes of secondary antibody incubation , nuclei were stained using 4′ , 6-diamino-2-phenylindole ( DAPI ) . Slides were then washed 4 times with PBS and mounted using Vecta Shield mounting medium ( Vector Laboratories ) . Aorta segments were imaged using a Bio-Rad ( Zeiss ) Radiance 2100 Rainbow laser scanning confocal microscope equipped with 60× oil-immersion objective .
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Cowpea mosaic virus ( CPMV ) , a plant virus that does not replicate in animals , is extensively used in material science and nanobiotechnology . CPMV has been found to specifically interact with mammalian cells after oral or intravenous administration , as well as in intravital vascular imaging studies that used a fluorescently modified form of CPMV . Binding of CPMV to mammalian cells was shown to be via a cell-surface binding protein ( CPMV-BP ) . Herein we identify this cell surface CPMV-BP through biochemical analysis , live cell experiments , and animal models . We found this surface exposed protein to be vimentin . Vimentin is principally a cytoskeletal protein that functions in the interior of cells to modulate architecture and dynamics . Our results now indicate surface vimentin can be used as a vascular endothelial marker and targeting option on the exterior surface of these cells . This work also unifies the relationship between CPMV and closely related mammalian viruses such as poliovirus , Theiler's murine encephalomyelitis virus ( TMEV ) , and coxsackie virus through the collective use of vimentin during their infectious cycle . Several other bacterial and viral pathogens use surface vimentin as an attachment receptor as well , and this research may lead to the development of broad-spectrum strategies to inhibit infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biotechnology",
"evolutionary",
"biology",
"virology"
] |
2009
|
Endothelial Targeting of Cowpea Mosaic Virus (CPMV) via Surface Vimentin
|
Body tissues are generally 15N-enriched over the diet , with a discrimination factor ( Δ15N ) that varies among tissues and individuals as a function of their nutritional and physiopathological condition . However , both 15N bioaccumulation and intra- and inter-individual Δ15N variations are still poorly understood , so that theoretical models are required to understand their underlying mechanisms . Using experimental Δ15N measurements in rats , we developed a multi-compartmental model that provides the first detailed representation of the complex functioning of the body's Δ15N system , by explicitly linking the sizes and Δ15N values of 21 nitrogen pools to the rates and isotope effects of 49 nitrogen metabolic fluxes . We have shown that ( i ) besides urea production , several metabolic pathways ( e . g . , protein synthesis , amino acid intracellular metabolism , urea recycling and intestinal absorption or secretion ) are most probably associated with isotope fractionation and together contribute to 15N accumulation in tissues , ( ii ) the Δ15N of a tissue at steady-state is not affected by variations of its P turnover rate , but can vary according to the relative orientation of tissue free amino acids towards oxidation vs . protein synthesis , ( iii ) at the whole-body level , Δ15N variations result from variations in the body partitioning of nitrogen fluxes ( e . g . , urea production , urea recycling and amino acid exchanges ) , with or without changes in nitrogen balance , ( iv ) any deviation from the optimal amino acid intake , in terms of both quality and quantity , causes a global rise in tissue Δ15N , and ( v ) Δ15N variations differ between tissues depending on the metabolic changes involved , which can therefore be identified using simultaneous multi-tissue Δ15N measurements . This work provides proof of concept that Δ15N measurements constitute a new promising tool to investigate how metabolic fluxes are nutritionally or physiopathologically reorganized or altered . The existence of such natural and interpretable isotopic biomarkers promises interesting applications in nutrition and health .
Nitrogen ( N ) metabolism in the body involves a complex network of various between- and within-tissues fluxes , consisting in the transport and/or transformation of various N compounds such as proteins ( P ) , amino acids ( AA ) , urea and ammonia . These various N transfers and metabolic processes are critical to the tissue assimilation of dietary N , the elimination of some dietary and endogenous N ( mostly as urinary urea ) and continuous exchanges of N compounds between different body compartments , thus ensuring a body N balance and P homeostasis . In particular , within each tissue , P synthesis and degradation fluxes ensure a continuous turnover of the P mass , which is essential to preserve lean mass and the numerous vital functions of body P . Moreover , free AA are constantly exchanged between tissues and used for P synthesis within tissues where they also enter the transamination and deamination pathways ( leading to the production of urea that is mostly excreted in urine ) as well as other secondary metabolic pathways . All these N fluxes are closely coordinated and their regulation implies changes in their amplitude , orientation or distribution , in both the short term , in order to deal with the discontinuous dietary intakes ( with daily cycles of fed and fasted states ) , and , in the long term , to adapt to changing nutritional or physiological conditions . However , dysregulation of this complex system of N fluxes may occur , involving metabolic perturbations , reorientations or imbalances and possibly leading to altered P homeostasis . Globally , little is still known about the inter-tissue N fluxes . The data available on different N fluxes are fragmented and dispersed because the classical investigative methods , mostly based on the administration of stable isotope-labelled metabolic tracers , usually focus on determining a specific type of flux ( e . g . , the administration of labelled AA to determine P synthesis rates , of labelled urea to study urea production and recycling fluxes , or of labelled dietary P to determine absorption kinetics , etc . ) [1]–[4] . Because of these methodological limitations , we still have a poor understanding of the complex network of N metabolic fluxes between and within tissues , how they are coordinated and regulated in standard conditions and how they may be modulated as a function of changes in nutritional conditions ( e . g . , P intake ) or dysregulated during a drift towards a pathological state . It is therefore necessary to develop new approaches that will provide an integrated insight into the whole-body distribution , partitioning and possible reallocations of N fluxes . In parallel , a large body of evidence , mostly from ecological and archaeological studies , suggests that the N stable isotope compositions of metabolic pools ( δ15N , the natural relative abundance of the rare stable isotope of N ) are not only dependent on the δ15N of the diet but are also closely related to N metabolism and its modulations [5] . It is indeed well known that animal and human tissues are generally 15N-enriched relative to their diet , and several studies have reported that the extent of this tissue-to-diet 15N discrimination ( Δ15N ) varies between tissues in the same individual and may also differ between individuals depending on their particular nutritional or physiological conditions [5]–[8] . Such a δ15N trophic shift , and intra- and inter-individual Δ15N variations , are likely to result from the existence of isotope fractionation associated with certain metabolic pathways ( e . g . , deamination or transamination ) that are sensitive to the isotope mass and use the two N isotopes at distinct rates [9] . When located at a metabolic branch point , isotope effects should theoretically lead to isotopic discrimination between the substrates and the competing products , with metabolic products having distinct isotopic values depending on the fractionation extent of the metabolic pathway from which they originate and the relative amplitude of the fluxes into the competing pathways [10]–[13] . Variations in the Δ15N of metabolic pools under specific nutritional or physiological conditions may therefore reflect underlying modulations in N fluxes , and , in particular , changes in the relative proportion of catabolism and anabolism and in the N balance [11] , [14]–[16] . This remains however a general concept and the principal factors responsible for Δ15N and its variations , as well as the integrated functioning of the body Δ15N system , are still poorly understood . This raises important questions as to which metabolic processes are actually fractionating , how Δ15N differences between tissues are established and what relationships exist between variations in metabolic fluxes and actual Δ15N values [11] , [17] . Furthermore , because of the complexity and intricacy of the metabolic pathways from which they originate , variations in Δ15N values cannot be interpreted directly in terms of the underlying rearrangements of body N fluxes that they might indicate . Mechanistic modeling approaches are therefore necessary to clarify the fractionating processes which lead to between-tissue Δ15N differences and to determine which variations in metabolic fluxes can explain between-subject Δ15N differences . This study proposes a new approach that combines measurements of the size and Δ15N values of numerous N metabolic pools in rats and their analysis by compartmental modeling . We first developed a multi-compartmental model which reproduces AA and P metabolism in the whole body and which is consistent with previous data in the literature regarding the principal N metabolic flux values ( absorption , excretion , urea production , P turnover , etc . ) and known structural and dynamic system characteristics ( metabolic compartmentation , differences in P turnover between tissues , etc . ) . Second , we showed that this model is able to reproduce the Δ15N variations observed experimentally among tissues and N fractions and thus to identify the fractionating processes that are responsible for such variations . Finally , model simulations enabled a clearer understanding of which flux modulations can impact tissue Δ15N values and , inversely , which , and in what way , Δ15N variations can reveal differences or rearrangements in N fluxes .
All sampled body N fractions were 15N enriched compared to the diet , except for the muscle free AA fraction and body urea , which were 15N depleted , and urinary urea , which had a δ15N similar to that of the diet . The pool-to-diet discrimination values ( Δ15Npool = δ15Npool−δ15Ndiet ) displayed major variations between the different sampled tissues and N fractions , with values ranging from −1 . 5 to 5‰ ( Figure 1 ) . Interestingly , in all the tissues sampled , P fractions had higher Δ15N values than non-P fractions , with differences that varied from tissue to tissue: they were for instance larger in muscle and heart and smaller in the kidney Δ15NP−Δ15NAA = 4 . 8‰ , 4 . 1‰ and 0 . 6‰ , respectively ) . Using the calibrated model , we performed model simulations to identify which flux modulations could explain and induce the Δ15N variations observed under specific nutritional or physiological conditions , and also conversely to determine which information could be inferred from Δ15N variations relative to underlying modifications in N metabolism . We assumed that ε factors were intrinsic parameters of the metabolic pathways so that they would not be impacted by changes in N fluxes induced by changes in conditions . Therefore , in this simulation phase , we only modified the values of the parameters k , to study the consequences of N flux value changes on tissue Δ15N . Model simulations were performed while changing the model fluxes either individually ( as reported in this section ) or under certain specific combinations ( as reported in the next section ) , so as to mimic the principal types of probable flux modulations occurring in response to changes in the physiological or nutritional conditions ( see the Material and Methods section for details on these model simulations ) . We first investigated the effect of individual changes in each of the main classes of N fluxes ( i . e . , tissue P turnover , tissue AA oxidation or AA transfers between plasma and tissues ) . We simulated tissue Δ15N trajectories in response to these specific changes in cases where the N amounts in compartments either evolved ( Simulation #1 with distinct initial and final elemental steady states , Figure 3A–D ) or remained constant as a result of flux compensations re-establishing homeostasis ( Simulation #2 with similar initial and final elemental steady states , Figure 3E–H ) . As a general rule , the model predicted that variations of fluxes located in a catenary structure with bidirectional exchanges ( e . g . , the bidirectional fluxes of P synthesis and degradation ) only transiently affected Δ15N values between two successive elemental steady states . More specifically , we predicted that modifications of the P turnover rates in tissues would not change the isotopic signatures of tissue P at steady state . Indeed , asynchronous variations in the tissue P synthesis and degradation fluxes , which impact tissue P size , induced only temporary changes in tissue AA and P Δ15N values during the transient phase of tissue P accretion or depletion , with Δ15N values returning to their initial levels at the final isotopic steady state ( Simulation #1 , Figure 3A–D ) . For instance in muscle , decreasing ( or increasing ) the P synthesis flux by decreasing ( or increasing ) the P synthesis capacity ( ksM ) induced a progressive decrease ( or increase ) in the P pool size and secondarily in the P degradation flux , until a new elemental steady state was reached . The transition between two distinct elemental steady states , during which an imbalance between the P synthesis and degradation fluxes created a P net loss ( or gain ) , was associated with a transient increase ( or decrease ) in the P Δ15N value . Moreover , we predicted the same variations in the P mass and Δ15N values with an increase ( or decrease ) in the P degradation capacity ( kdM ) than with a decrease ( or increase ) in ksM . More generally , the model predicts that in any tissue , a P accretion ( or depletion ) is associated with a temporary decrease ( or increase ) in P Δ15N . It should be noted that in all cases , the Δ15N variations predicted were quantitatively small ( Δ15N variations of only 0 . 1‰ for 20% changes in the P mass ) . By contrast , variations of fluxes located at a metabolic branchpoint that induced permanent changes in the allocation of fluxes between competitive pathways ( e . g . , changes in the relative orientation of tissue AA towards oxidation vs . P synthesis , or changes in AA transfers between plasma and tissues ) were predicted to result in more marked and , above all , persistent variations in Δ15N values , even without any variation in the elemental steady state . For instance , an increase in hepatic AA oxidation ( counterbalanced by an increase in urea recycling in order to maintain homeostasis ) induced a progressive and lasting increase in hepatic P Δ15N , with higher Δ15N values at the final than at the initial isotopic steady state ( Simulation #2 , Figure 3E–H ) . Globally , in terms of the flux variations that effectively impact tissue Δ15N values , our results can be summarized by considering changes in the tissue p ratio . The p ratio corresponds to an integrated index of the relative metabolic utilization of tissue free AA that we defined as the proportion of AA that are directed toward oxidation rather than used for net P synthesis or exported to the circulation ( p = fox/ ( fox+fout+fs−fd ) , Figures 3C and G ) . We indeed demonstrated that differences in the Δ15N of a given tissue between two steady states resulted from permanent changes in the p ratio , whereas changes in the bidirectional fluxes of P synthesis and degradation induced only transient changes in the p ratio and did not modify steady-state Δ15N values . The significance of p to steady-state Δ15N values was also analytically noticeable from the model equations ( Table S1 ) . For instance , the Δ15N steady-state value in muscle P ( Δ15NMP ) depends on only two factors , the Δ15N of the plasma AA supplied to muscle ( Δ15NPlAA ) and this integrated index p ( since Δ15NMP = Δ15NPlAA−p*εOX−εS , with εOX and εS being the fractionation factors for AA oxidation and P synthesis , respectively ) . Furthermore , when a metabolic change in a given tissue modifies its own P and AA Δ15N values , outward transport of this tissue AA consequently modifies the plasma AA Δ15N value and can thus also secondarily modify the Δ15N values of other body tissues , even if there are no associated metabolic changes in these tissues . For instance , after a concomitant increase in splanchnic oxidation and urea recycling , our model predicted that all body tissue Δ15N values were changed and that the Δ15N trajectories and the time required for tissue P to reach the new isotopic steady state varied between tissues ( Figure S3 ) , depending on their specific rates of plasma AA uptake and P turnover ( Table S4 for the characteristic times required to reach 50% and 95% of isotopic equilibrium in each tissue ) . A growing body of evidence in the literature suggests that the isotopic signatures of tissues vary according to the quality and quantity of dietary N intake . More specifically , several studies have reported an increase in tissue Δ15N with a decrease in dietary P quality ( i . e . , when the qualitative and/or quantitative supply of AA in dietary P do not match the AA demand of the individual ) [8] , [13] , [33]–[37] and in cases of dietary restriction or fasting [38]–[42] . However , the Δ15N variations reported have sometimes been conflicting and difficult to interpret because of differences in the experimental conditions and the presence of confounding factors , such as concomitant changes in both the quality and quantity of P intake or the heterogeneous extent of body mass depletion in the event of starvation . In all cases , the underlying mechanisms proposed for associated isotopic variations remain speculative . Using the calibrated model , we simulated several scenarios consisting in different N flux modifications that might result from moderate ( e . g . variation in P quality; Simulation #3 ) or severe ( e . g . fasting conditions; Simulation #4 ) nutritional modulations .
Our experimental data , as well as the model predictions for tissue Δ15N values , are consistent with the few findings available in the literature on rodents [13] , [33] , [34] , [48]–[52] ( Table S5 ) . In contrast , whereas in the literature urine is usually reported to be 15N-depleted compared to the diet [13]–[15] , [53]–[59] , in this study we observed and simulated Δ15N values in urine that did not differ significantly from zero . Given that urinary N accounts for the largest part of N losses , the isotopic composition of N losses was globally similar to that of N intake ( i . e . , null Δ15N in N losses ) . As a result , amounts of 15N intake and losses were equal , which ensured that the body was globally at isotopic steady state at the time of the measurements . A negative Δ15N in N losses has often been put forward to explain the trophic shift ( i . e . , positive Δ15N in body tissues ) , but this would mean a permanent and endless Δ15N increase in adult body tissues . Because no net gain of 15N or net loss of 14N occurs in an adult animal at isotopic steady state , the trophic shift probably result from 15N accumulation during the growth period before adulthood , when animals are in positive N balance . Since N deposited in tissues is 15N-enriched relative to excreted N , net gain of N in tissues during growth should be associated with preferential 15N bioaccumulation . In addition , the higher 15N abundance observed in P than in AA fractions of tissues is a novel and important finding that had not previously been reported , because tissues are usually analysed as a whole , without making a distinction between the AA and P fractions . It should be noted that some other N-containing compounds like nucleotides in tissues , creatine in muscle and uric acid in plasma are probably present , but in relatively small concentrations , in what we considered as the “free AA” fractions , since there is no way to separate these minor compounds from the main free AA . However , based on their known relative concentrations , these potential contaminants may not alter significantly our estimates of the free AA isotopic values . As suggested by in vitro studies [9] , [60]–[64] , our model confirmed that some metabolic pathways are associated with isotope effects that explain the well-known , but still poorly understood , δ15N trophic step , and also the observed , but also misunderstood , Δ15N differences between and within tissues . Whereas there are very few quantitative data in the literature concerning the amplitude of the isotope fractionation associated with metabolic pathways in vivo , one highlight of our work is that it enabled the localisation and quantification of these isotope effects ( Table S3 , ε values ) . Globally , according to our model , no net isotope effects were likely to be associated with pathways involving simple N transport without metabolic transformation ( e . g . , AA exchange fluxes between plasma and tissues , N transfers throughout the gastrointestinal tract and N losses via the faeces , hair and desquamation , etc . ) , inasmuch as these isotope effects were not required to reproduce intra-individual Δ15N variations . Conversely , we identified the existence of isotope effects associated with the tissue AA oxidation and urea production pathways . These predictions are in line with the fact that the most likely processes inducing isotopic fractionation are those which involve enzymatic transfers of amino groups such as deamination and transamination reactions [9] , [11] , [17] . However , although we were able to confirm the existence of an isotope effect associated with deamination , we showed that this mechanism alone could clearly not explain the δ15N trophic shift in tissues . Simple whole-body models , which do not distinguish between different body tissues and consider all body P as a single compartment , conclude that the isotopic fractionation associated with AA catabolism and N elimination is sufficient to explain 15N accumulation in tissues [11] , [12] , [16] , [65] . But thanks to the multi-tissue representation of our model , we were able to demonstrate that isotope effects with distinctive amplitudes are necessarily involved in several metabolic pathways to give rise to the Δ15N variations observed among tissues and among N fractions within tissues . More specifically , we predicted varied non-null ε values associated with urea production and urinary excretion fluxes , as well as with P synthesis fluxes in tissues and some intestinal secretion and reabsorption fluxes . It has to be noted that the non-null ε factors in our model do not strictly represent isotope effects associated to specific individual chemical processes , but rather aggregate several fractionation processes that may occur on different pathways . Generally speaking , non-null ε factors can reflect the heterogeneity of the precursor pool and the fact that only a subset of the compounds in the precursor pool ( some specific AA for instance ) , with a distinct δ15N , is used in a given pathway . In the case of exchanges that involve opposite reactions ( e . g . , intestinal absorption and secretion , or P synthesis and breakdown ) , non-null ε factors usually represent the net fractionation effect associated with the bidirectional exchange ( see Text S1 for a further discussion on the physiological plausibility of our estimated ε values ) . To avoid over-parameterization of the model , we also chose to represent all its N fluxes by linear , first-order dynamics . Indeed , on grounds of parsimony , it was not necessary to make the model equations nonlinear and more complex ( e . g . , using saturable transfer laws ) , since the modeling results were judged satisfactory with regard to the general knowledge on the functioning of the N metabolic system and our experimental data . From the model simulations , we observed that nutritionally-induced variations in P turnover and AA catabolism fluxes led to Δ15N changes that could be of varied extents and durations ( transient or permanent ) . Moreover , when comparing the initial and final steady states , we found that changes in the sizes and Δ15N of body N pools were not systematically coupled: compartment sizes may differ between two steady states without associated differences in Δ15N values , and vice versa . For instance , in the case of net P accretion or depletion , Δ15N values were similar at the initial and final steady states while the elemental steady states were different . Δ15N were only temporary changed during the period necessary to achieve the new steady state ( i . e . , when the P synthesis and degradation fluxes were unbalanced ) . More specifically , a permanent P accretion ( or inversely , depletion ) was associated with a transient decrease ( or increase ) in the tissue P Δ15N value ( Figures 3A–D ) . Because , according to our predictions , the isotopic variations induced by alterations to P synthesis and degradation fluxes are only transient and of small amplitude , they will probably be very difficult to detect in practice . Therefore such fluxes modulations are neither sufficient nor necessary to explain Δ15N differences that can be observed between two distinct metabolic states . The fact that tissue Δ15N values do not record the entire history of P anabolic and catabolic phases that specifically result from transient imbalances between P synthesis and degradation probably limits the degree of both the inter- and intra-individual Δ15N variability in a given tissue . In contrast to the limited impact of modulations in bidirectional fluxes , variations in fluxes involved in metabolic branched pathways , such as modifications of the relative orientation of tissue AA toward their different metabolic and transfer pathways , are predicted to lead to lasting changes in Δ15N values ( i . e . , with distinct final and initial isotopic steady states ) , even without a concomitant variation in the elemental steady state ( Figures 3E–H ) . Generally speaking , based on both our analytical ( model equations , in Table S1 ) and numerical ( model simulations , Figures 3–4 ) results , we can predict that the steady-state isotopic signature of a given tissue should depend both directly on its own metabolism and indirectly on the isotopic signatures of other tissues . Indeed , in peripheral tissues such as muscle , variations in metabolism would directly affect tissue AA and P Δ15N values through changes in the proportion of AA catabolism relative to net P synthesis and outward transport ( as represented by the integrated index p ) . Besides , because of blood-tissue AA exchanges , a metabolic-induced Δ15N change in a given tissue could modify plasma Δ15N values , and thus also secondarily those of other body tissues without the metabolism of the latter necessarily being changed . In splanchnic tissues , which have a more central and connected position in the metabolic network , steady-state Δ15N values are predicted to be affected by local tissue metabolism and also by the relative contribution of other metabolic pathways , such as urea recycling and salvage by N intestinal reabsorption ( see Table S1 for detailed equations ) . Furthermore , when simulating Δ15N trajectories in different body tissues after a metabolic change specifically affecting splanchnic tissues , we predicted that Δ15N values varied in all tissues but according to different kinetics , the new isotopic steady states being reached at different speeds ( Figure S3 ) . These results are of particular interest in terms of determining the time required for such metabolic alterations to become isotopically detectable , as a function of the tissue under study . This kinetic characteristic also paves the way to using isotopic measurements obtained concomitantly in several tissues to estimate the timing of a metabolic alteration , or , when used in ecological studies , to infer the time of a diet-shift or migratory movement in the context of dietary δ15N changes [17] , [66] . For such ecological applications , the predicted half-lives and times needed for tissues to reach their isotopic steady state after a dietary and/or a metabolic change are of considerable value ( Table S4 ) . We also used the model to investigate how tissue Δ15N values might vary under particular changes to dietary P intake and which N flux alterations would most likely be responsible for reported Δ15N variations under such conditions . Globally , under moderate qualitative or quantitative changes in the dietary P intake , which preserve the whole body N balance , our simulations suggested that Δ15N would be minimal when the P intake optimally matched AA demand and N requirements . Indeed , we predicted higher tissue Δ15N values when the N intake deviated qualitatively or quantitatively from an optimum intake . This results from the fact that an altered dietary P quality , due to a less well-balanced AA composition , or an excessive P intake , leads to a greater relative orientation of tissue AA to the catabolic vs . anabolic pathways , and consequently to less efficient tissue P synthesis and dietary P anabolic use . These predictions agree with the results of studies performed in several different species that have shown that Δ15N decreased as the dietary P biological value or anabolic use efficiency increased [36] , [67] , [68] . More specifically , we simulated different N flux modulation scenarios that could result from a change to dietary P quality . These scenarios consisted mainly in increasing tissue AA oxidation fluxes ( i . e . , decreasing tissue P synthesis efficiency ) in different tissues and to various extents . The model predicts that an increase in AA catabolism in splanchnic or peripheral tissues would result in contrasting Δ15N changes ( increase or decrease , respectively ) in the tissue P . Since published studies have mostly reported higher Δ15N values in tissues with dietary P of poorer quality [8] , [13] , [33] , [34] , [68] , our simulation results suggest that the higher urea production induced by a P of poorer quality is caused by an increase in the oxidation of splanchnic rather than peripheral AA . The model also predicts that the amplitude of increase in tissue Δ15N values after an increase in splanchnic AA oxidation would be all the larger as the resulting increase in urea production is not entirely balanced by an increase in urea recycling but , rather , associated with an alteration to peripheral metabolism ( Figure 4 ) . However , tissue Δ15N values would probably not constitute specific markers of the relative changes in urea recycling and whole peripheral metabolism , because similar Δ15N values could be obtained with distinct sets of urea recycling efficiency and peripheral AA delivery values . In addition , the Δ15N variations predicted in urinary and body urea result from numerous and possibly opposing isotopic variations in the splanchnic and peripheral tissues , so that Δ15N variations in urinary and body urea at an isotopic steady state are likely not to be informative about body N flux modulations . In contrast , faeces Δ15N might constitute an interesting marker of enterohepatic urea recycling efficiency ( Figure S5 ) . Globally , the simulations demonstrate that combined measurements of Δ15N changes in various tissues and N pools might help to disentangle the underlying intricate metabolic modulations associated with changes in dietary P quality . Our model also provides insight into isotopic variations under more stringent nutritional alterations to metabolic fluxes , such as during nutritional stress , fasting or starvation . Although muscle P wasting has been well described under prolonged starvation , the flux modulations involved have not been fully identified [69] . Our simulations showed that a drastically reduced or zeroed N intake could induce a global δ15N increase in most body and elimination pools . Amplitudes of the simulated δ15N variations differed between tissues and depended on the N flux modulations responsible for P mass loss ( Figure 5 ) . The predicted δ15N increases in urine and most tissues ( except red blood cells ) in response to starvation are in line with most literature values reported for mammals experiencing N imbalance [14] , [15] , [40] , [42] , although conflicting results have been reported across various tissues , species and conditions of nutritional restriction [5] , [6] , [29] , [30] . For instance , some studies showed a general increase in the δ15N values of various tissues in fasting or P deprived birds [29] , [30] , whereas other studies reported δ15N changes in only some tissues ( e . g . , in liver , SI mucosa and heart , but not in muscle , in fasting Arctic ground squirrels during hibernation [40] ) or no δ15N changes in tissues despite an increase in excreta δ15N [45] , [46] . Our model was able to reproduce qualitatively such different results and our simulations suggest that δ15N variations under starvation may be different depending on how and which metabolic fluxes are altered . We indeed found that a muscle mass loss that is mainly induced by an increase in the muscle P degradation , should lead to a similar increase in the δ15N values in all body tissues , which is consistent with reports on quails under starvation [39] . By contrast , when muscle mass loss is caused by an alteration to muscle P synthesis , together with an enhanced oxidative utilization of muscle AA , we predicted a greater δ15N increase in splanchnic tissues and almost no δ15N variations in muscle , as has been reported in hibernating squirrels [40] . A global body δ15N increase in response to starvation had also been predicted by previous simple models in the literature [11] , [16] , which considered all body P as a unique and homogeneous compartment . In such models , urinary N excretion was considered as the only fractionating process , with a preference for 14N , so that δ15N in the single-body P pool systematically increased in line with an increase in the proportion of excreted vs . ingested N . Unlike these over-simplified models , our multi-tissue model takes into account possible isotopic fractionating processes associated with between and within tissue N fluxes , thus explaining our seemingly divergent experimental results . Indeed , our model can explain the tissue-specific δ15N variations reported during starvation as resulting not only from enhanced urinary excretion but also possibly from a tissue-specific increase in endogenous P degradation , leading to an enhanced re-use of 15N-enriched AA for P synthesis after their inter-organ redistribution . More generally , in situations of N imbalance , our model is able to discriminate between variations in the P synthesis and breakdown fluxes leading to similar P mass variations . Our simulation results thus demonstrate the physiological plausibility of the model we have developed . The behaviour of the model is in line with general knowledge on the functioning of the N metabolic system and with the fragmented data that have been reported on nutritionally-induced Δ15N variations . Thanks to its multi-tissue representation , our model provides a detailed and integrated insight into the partitioning of different N metabolic fluxes between and within tissues , and a clearer understanding of the metabolic processes that generate isotopic fractionation and their interactions . We have shown that , contrary to the common hypothesis , urea production is not the only process responsible for the well-known , but poorly-understood , δ15N trophic shift ( i . e . , positive Δ15N values in tissues ) . Numerous other metabolic processes , such as P synthesis , AA intracellular metabolism , intestinal absorption and urea recycling through the colon , are actually likely involved in the accumulation of 15N in tissues . Interestingly , our findings suggest that tissue Δ15N could be used as an indicator of how well the diet matches the metabolic demand for AA in tissues . The existence of such a natural isotopic biomarker paves the way towards better assessing the notion of dietary P quality under various physiopathological conditions . In addition , using model simulations , we were able to highlight that tissue Δ 15N values are closely related to the distribution of N fluxes within the body , and that Δ15N measurements could therefore be used as biomarkers for the metabolic impact of nutritional conditions . Although in a given tissue Δ15N often seems to be a sensitive but rarely specific marker of particular dietary and metabolic conditions , we showed that simultaneous measurements of Δ15N in various tissues can be used to characterize a particular metabolic state . Accordingly , the present study thus constitutes proof of concept that natural N isotope abundances are interpretable biomarkers for the metabolic impact of nutritional conditions . A multi-tissue mechanistic modeling approach , such as that developed during this study , in order to understand the mechanisms underlying natural isotopic signatures , is a prerequisite for further research on their use in nutrition and physiopathology , in addition to their usual applications in ecology and anthropology [5] . Isotopic signatures at natural levels of abundance therefore appear to constitute a novel and promising tool to investigate how various N fluxes may be reorganised or altered in a coordinated manner to adapt to specific nutritional or physiopathological conditions . They offer interesting applications for the simple and early detection of such conditions and evaluation of the impact of nutritional strategies .
|
Body proteins ensure vital functions , and their constancy is maintained through the tight coordination of many nitrogen metabolic fluxes , but our understanding of how this flux system is regulated , and sometimes dysregulated , remains fragmentary and incomplete . Besides , body tissues are generally naturally enriched in the heavier stable nitrogen isotope ( 15N ) over the diet: this 15N bioaccumulation ( Δ15N ) varies depending on tissues and metabolic orientations , likely as the result of isotope effects associated to some metabolic pathways . We used a novel approach , combining multi-tissue Δ15N measurements and their analysis using modeling , to understand how body Δ15N values relate to nitrogen fluxes . The multi-tissue model we have developed provides a clearer understanding of the metabolic processes that generate isotopic fractionation , and of how tissue Δ15N values are modulated in response to changes in the body distribution of specific nitrogen fluxes . We show that Δ15N values tend to rise when the amino acids intake does not optimally fit the metabolic demand , and that Δ15N values constitute natural and interpretable signatures of nutritionally-induced variations in nitrogen fluxes . This approach constitutes a new promising tool to investigate how nitrogen metabolism is nutritionally or physiopathologically reorganized or altered , and promises interesting applications in many areas ( nutrition , pathology , ecology , paleontology , etc ) .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion"
] |
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2014
|
Natural Isotopic Signatures of Variations in Body Nitrogen Fluxes: A Compartmental Model Analysis
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The universally conserved J-domain proteins ( JDPs ) are obligate cochaperone partners of the Hsp70 ( DnaK ) chaperone . They stimulate Hsp70's ATPase activity , facilitate substrate delivery , and confer specific cellular localization to Hsp70 . In this work , we have identified and characterized the first functional JDP protein encoded by a bacteriophage . Specifically , we show that the ORFan gene 057w of the T4-related enterobacteriophage RB43 encodes a bona fide JDP protein , named Rki , which specifically interacts with the Escherichia coli host multifunctional DnaK chaperone . However , in sharp contrast with the three known host JDP cochaperones of DnaK encoded by E . coli , Rki does not act as a generic cochaperone in vivo or in vitro . Expression of Rki alone is highly toxic for wild-type E . coli , but toxicity is abolished in the absence of endogenous DnaK or when the conserved J-domain of Rki is mutated . Further in vivo analyses revealed that Rki is expressed early after infection by RB43 and that deletion of the rki gene significantly impairs RB43 proliferation . Furthermore , we show that mutations in the host dnaK gene efficiently suppress the growth phenotype of the RB43 rki deletion mutant , thus indicating that Rki specifically interferes with DnaK cellular function . Finally , we show that the interaction of Rki with the host DnaK chaperone rapidly results in the stabilization of the heat-shock factor σ32 , which is normally targeted for degradation by DnaK . The mechanism by which the Rki-dependent stabilization of σ32 facilitates RB43 bacteriophage proliferation is discussed .
The universally conserved molecular chaperone machines maintain cellular protein homeostasis by acting at almost every stage in the life of proteins [1] . In the bacterium Escherichia coli , the multifunctional DnaK ( Hsp70 ) chaperone machine ( the DnaK/DnaJ/GrpE complex ) performs key cellular functions under both physiological and stress conditions [2]–[4] . For example , it assists de novo protein folding and targeting to biological membranes , protein quality control , assembly or disassembly of oligomeric complexes , and signal transduction . It responds to multiple stresses leading to protein misfolding and aggregation [5] . Moreover , the DnaK machine controls the entire E . coli heat-shock response by binding specifically to the major stress sigma factor σ32 and facilitating its degradation by the membrane-anchored FtsH protease [6] . The multiple phenotypes associated with the loss of DnaK in E . coli attest to its central role in protein biogenesis [7] . The DnaK protein is composed of an N-terminal nucleotide-binding domain and a C-terminal substrate-binding domain connected by a conserved linker involved in conformational changes and stability [8]–[10] . While the ATP-bound DnaK exhibits a low affinity and fast exchange rate for its substrate , the ADP-bound form is characterized by high affinity and low exchange rates . Specific cochaperones regulate its switch from one state to the other , thus coordinating DnaK's various intracellular functions . For example , the cochaperone DnaJ ( Hsp40 ) stimulates DnaK's ATPase activity and targets specific substrates to DnaK [11] , resulting in the formation of a stable ADP-bound DnaK-substrate complex [12] . The nucleotide exchange factor GrpE stimulates ADP-ATP exchange by triggering substrate release , thus resetting DnaK's cycle [13] . All the DnaJ/Hsp40 cochaperones are characterized by the presence of a compact domain of about 70 amino acids , called the J-domain , which is essential for a functional interaction with Hsp70 . Therefore , these cochaperones are generally called JDPs for J-domain proteins [14] . JDPs have been divided into three classes . Adjacent to their J-domain , type I JDPs share a G/F-rich region , a zinc-binding domain and a C-terminal domain involved in substrate-binding [15] . Type II JDPs generally have a similar domain arrangement except that they do not possess a zinc-binding domain [16] . The type I and type II JDPs generally bind a large variety of unfolded substrates in response to stress and are thus considered generic cochaperones [17] . In contrast , type III JDP members only have the J-domain in common with the other JDPs , suggesting that they deliver specific substrates or confer specific cellular localization to Hsp70 [18] . In E . coli , the chaperone DnaK interacts with the type I and II JDPs , DnaJ and CbpA , respectively , as well as with the type III protein DjlA , which may confer to DnaK its membrane localization [7] , [19] . In general , the successful proliferation of viruses relies on both the efficient reprogramming of the host cell cycle and the rapid synthesis and subsequent folding of a large number of viral proteins necessary for genome replication , protein synthesis and capsid assembly [20] . Since molecular chaperones are generally involved in both processes , it is not surprising that many viruses utilize the host cellular chaperones at different stages in their life cycle . Among these chaperones , Hsp70 ( DnaK ) is often recruited by eukaryotic viruses to assist viral entry , replication , gene expression , folding and assembly of viral proteins , and to control the host cell cycle progression [21] , [22] . Some viruses , such as polyoma and Molluscum contagiosum , encode their own JDPs to hijack the host Hsp70 chaperone [22] . To date , the best characterized virus-encoded JDPs are the type III viral T-antigens from simian virus 40 ( SV40 ) , which use their N-terminal J-domain for transcriptional activation of viral genes , viral DNA replication and capsid morphogenesis , as well as modulation of the host growth control signaling pathways to facilitate viral replication ( review by [23] ) . Putative gene products showing sequence similarities with the J-domain also can be found in some mycobacteriophage and enterobacteriophage genomes ( [24] , [25]; http://phage . ggc . edu ) . In this work , we have identified and characterized the first functional bacteriophage-encoded JDP protein . We show that the ORFan gene 057w from the T4-related enterobacteriophage RB43 , encodes a bona fide type III DnaJ-like protein , named Rki , which specifically interacts with the E . coli host multifunctional DnaK chaperone . However , in contrast with other JDPs , Rki expression is highly toxic for E . coli growth and this toxicity is fully dependent on the presence of endogenous DnaK . Analysis of the rki mutant bacteriophage further revealed that interaction with DnaK is critical for RB43 proliferation . Finally , we show that recruitment of the host DnaK chaperone by Rki rapidly results in the stabilization of the heat-shock factor σ32 , thus facilitating bacteriophage proliferation .
The enterobacteriophage RB43 was originally isolated from sewage treatment plants in Long Island [26] . It shares only 40% ( 115/260 ) of its genes with T4 and is the representative member of a well-defined group of T4-related bacteriophages , including RB16 and most likely RB42 [27] , [28] . The ORFan gene 057w ( Uniprot Q56BZ1 ) of RB43 is the first gene of a locus of five genes of unknown function absent in bacteriophage T4 ( Figure 1A ) . Interestingly , this gene encodes a putative protein of 237 amino acids , with a N-terminal domain of about 75 amino acids having 63% similarity with the J-domain of the three known E . coli DnaJ cochaperones . Specifically , the essential His-Pro-Asp ( HDP ) tripeptide of the loop connecting helices II and III , as well as key residues from helices II and III of the DnaJ J-domain are well conserved . Nevertheless , the region corresponding to helix IV of DnaJ displays significantly lower sequence conservation ( Figure 1B ) [29] . With the exception of the four closely related 057w homologues found in other T4-related bacteriophages , i . e . , RB16 and RB42 , Klebsiella bacteriophage KP15 and Aeromonas bacteriophage 65 [27] , no significant sequence similarity with the remaining C-terminal region of the protein was found in databases ( Swiss-prot , TrEMBL ) . Since the C-terminal part of JDP proteins determines localization and/or substrate specificity , the lack of sequence similarity suggested to us that this family of bacteriophage-encoded JDP could recruit the host Hsp70 for specific and potentially novel bacteriophage-related function ( s ) . Surprisingly , in bacteriophage RB16 , gene 057w is fused in-frame with the downstream gene 058w ( Figure 1A; Uniprot Q56BZ0 ) . In this case , the stop codon of 057w ( TAA ) is replaced by a glutamate ( GAA ) at position 238 , resulting in a 565 amino acid long fusion protein ( Uniprot D9ICB9 ) . A similar fusion is also observed in the less related Klebsiella bacteriophage KP15 ( gp055; Uniprot D5JF99 ) , but not in RB42 or Aeromonas bacteriophage 65 ( http://phage . ggc . edu/blast/blast . html ) . This suggests that the adjacent 057w and 058w genes could somehow cooperate during bacteriophage infection ( see below ) . We first asked whether the 057w gene product indeed encodes for a functional JDP , by using domain swapping experiments [30] . Specifically , the J-domain of the E . coli DnaJ cochaperone was replaced by the putative J-domain of the 057w gene product , leading to the formation of the wild-type Jd57-DnaJ chimera . In addition , as a control for an inactive J-domain , we engineered the same chimera with the known inactivating His 38 to Gln ( H38Q ) substitution in the HPD tripeptide , equivalent to the well-characterized dnaJ259 mutant allele . This mutation abolishes functional interaction between a J-domain and its cognate Hsp70 [29] , [31] . Plasmids expressing various wild-type and chimeric proteins were introduced into an E . coli W3110 mutant strain lacking all three endogenous dnaJ homologs , namely dnaJ , cbpA and djlA [32] . As a consequence , this strain displays several DnaJ-dependent phenotypes such as temperature-sensitivity , resistance to bacteriophage lambda , and lack of motility [29] , [33] . Control experiments with plasmid-encoded wild-type DnaJ confirm that bacterial growth at the nonpermissive temperature of 43°C is indeed DnaJ-dependent ( Figure 1C ) . As anticipated , the Jd57-DnaJ chimera containing the wild-type bacteriophage J-domain efficiently rescues bacterial growth at high temperature , whereas the Jd57 ( H38Q ) -DnaJ mutant chimera does not . In agreement with the high temperature bacterial growth complementation result , bacteriophage λ growth and bacterial motility are also restored by expression of the wild-type Jd57-DnaJ but not by the mutant chimera ( Figure 1D and 1E ) . A control experiment presented in Figure 1F shows that the expression level of the chimeric proteins is comparable under the conditions tested . Taken together , these results demonstrate that the putative 057w gene product possesses a functional J-domain . Since similarity between the putative bacteriophage-encoded JDP and the other DnaJ family members is restricted to the J-domain , by convention this protein belongs to the type III group , like known JDPs of eukaryotic viruses [22] . We next asked whether the full length protein encoded by 057w displays some DnaJ function in vivo . However , multiple attempts to clone 057w under the control of its native promoter were unsuccessful , even when a pSC101 low copy number plasmid was used as a cloning vector . Finally , 057w was successfully cloned under the control of the tightly regulated ParaBAD promoter in the presence of glucose to minimize basal transcription levels and thus avoid toxicity . This plasmid construct was then tested for complementation of the temperature-sensitive phenotype of the triple dnaJ cbpA djlA mutant . As expected , expression of the full length bacteriophage JDP is highly toxic in the presence of L-arabinose inducer and is thus not capable of replacing the E . coli DnaJ protein ( Figure 2A ) . To investigate whether the severe toxicity is DnaK-dependent , we then expressed the bacteriophage JDP in the single dnaK , hscA or hscC mutants , the three Hsp70-encoding genes of E . coli [7] , and monitored its effect on bacterial growth . As in the wild-type strain , expression of the bacteriophage JDP exhibits a strong toxic effect in both hscA and hscC mutants . In sharp contrast , the JDP displays no toxicity when expressed in the single dnaK mutant ( Figure 2A and 2B ) , thus indicating that its toxicity is DnaK-dependent . As expected , the toxicity is restored when DnaK is co-expressed from a plasmid ( Figure 2B ) . Next , we showed that overexpression of the bacteriophage JDP harboring the H38Q inactivating mutation in its J-domain does not result in toxicity when expressed in the wild-type E . coli strain , thus demonstrating that the DnaK-dependent toxicity also requires a functional J-domain ( Figure 2B ) . Note that both the wild-type and H38Q JDP mutants showed comparable steady state expression levels ( Figure S1 ) . Toxicity of the bacteriophage JDP was exacerbated in the sole absence of DnaJ , the main cochaperone of DnaK in vivo ( and to a lesser extent in the presence of CbpA and DjlA ) , suggesting that the bacteriophage protein may compete with DnaJ for binding to DnaK during bacteriophage infection ( Figure 2A ) . Since the bacteriophage JDP and DnaK genetically interact , the gene 057w was named rki for RB43 DnaK-interactor . The contribution of the uncharacterized C-terminal domain of Rki to the DnaK-dependent toxicity remains unknown . Based on the predicted secondary structure of Rki ( and on the partial chymotrypsin proteolysis of purified Rki protein described below and in Figure S2 ) , we engineered a C-terminal deletion of Rki , after amino acid Met159 , within a predicted random coil region located approximately halfway through the putative C-terminal domain . The resulting Rki ( 1–159 ) construct was tested for both , its toxicity and its ability to replace the E . coli DnaJ cochaperone during bacterial growth at non-permissive temperature . Strikingly , robust overexpression of Rki ( 1–159 ) exhibits no toxicity at all , thus indicating that the C-terminal and the J-domain of Rki act in concert to exert toxicity . In addition , Rki ( 1–159 ) is also able to partially replace DnaJ as a functional DnaK cochaperone in vivo , even at the stringent temperature of 43°C ( Figure S1 ) . These results reveal that the DnaK-dependent toxic effect of Rki relies on both a functional J-domain and the C-terminal domain of unknown function . We next asked whether Rki and DnaK could indeed physically interact in vivo . To do so , an N-terminal Flag-tagged version of Rki was expressed in E . coli and used as bait in pull-down experiments . The results shown in Figure 2C clearly demonstrate that indeed Rki and DnaK form a complex . The fact that the H38Q substitution in Rki affects interaction with DnaK in this assay confirms that the interaction necessitates a functional J-domain ( Figure 2C ) . In addition , DnaJ participates in the complex with Rki and DnaK ( Figure 2C ) . However , as with DnaK , the complex between DnaJ and Rki is disrupted by the presence of the H38Q substitution in the Rki J-domain , thus indicating that the presence of DnaJ is DnaK-dependent and is not simply due to the formation of mixed oligomers between Rki and DnaJ . Taken together , these data demonstrate that Rki possesses a functional J-domain , which enables it to functionally interact with the host multifunctional DnaK chaperones in vivo . To further explore Rki functions in vitro , we purified both the wild-type Rki and Rki ( H38Q ) mutant proteins . SEC-MALLS experiments performed with purified Rki shows that Rki elutes as a single peak with an average molecular mass of 31 . 5 kDa ( Figure S2; Text S1 ) . This is in good agreement with the theoretical molecular mass of 29 . 15 kDa demonstrating that in contrast to the three E . coli J-domain cochaperones DnaJ , CbpA and DjlA , Rki is almost exclusively monomeric in solution . In addition , partial α-Chymotrypsin proteolysis followed by N-terminal sequencing of purified Rki indicates a two domain structure composed of the N-terminal J-domain ( residues 2 to 70 ) , a short putative linker region ( residues 71 to 75 ) and a larger C-terminal domain ( residues 76 to 237; Figure S2 ) . Purified Rki and Rki ( H38Q ) proteins were then tested for their ability to stimulate DnaK's ATPase activity in vitro under steady state condition , as described [33] . The results presented in Figure 3A show that Rki wild-type indeed stimulates DnaK ATPase , although less efficiently than does DnaJ . In contrast , Rki ( H38Q ) harboring the inactivating mutation the J-domain does not show any stimulation , thus indicating that Rki is capable of stimulating DnaK ATPase activity in a J-domain dependent manner . This result is in agreement with the domain swapping experiments shown in Figure 1 and further demonstrates that Rki possesses a bona fide JDP . We next asked whether Rki could assist DnaK in the refolding of the chemically denatured luciferase substrate . This assay is dependent on both a functional J-domain and a capacity to bind to and deliver an unfolded substrate to DnaK . A representative kinetic analysis of luciferase refolding in the presence of Rki , Rki ( H38Q ) or DnaJ is shown in Figure 3B . As expected , DnaJ efficiently stimulates DnaK-mediated refolding of luciferase . In contrast , both Rki and Rki ( H38Q ) do not stimulate DnaK's reactivation activity , even when Rki concentration was increased 2-fold above that of DnaJ . These results strongly suggest that although Rki interacts with DnaK both in vivo and in vitro , it does not possess a DnaJ-like , generic cochaperone function . This behavior is in sharp contrast to that of DnaJ , CbpA and DjlA [7] . It is known that DnaJ possesses intrinsic chaperone function , as it can bind unfolded substrate and efficiently prevents its aggregation [16] . The inability of Rki to support DnaK-mediated reactivation suggests that it may not efficiently bind denatured luciferase . Indeed , the results presented in Figure 3C clearly show that Rki alone does not prevent the aggregation of chemically denatured luciferase , even at a much higher cochaperone/substrate ratio , thus indicating , once more , that Rki displays no apparent generic chaperone function . In summary , the above results demonstrate that Rki specifically interacts with DnaK in a J-domain dependent manner . However , in sharp contrast with DnaJ , CbpA or DjlA , Rki is not capable of assisting DnaK as a generic cochaperone in vitro ( Figure 3B ) or throughout its multiple cellular tasks , as judged by its inability to replace DnaJ functions in vivo ( Figure 2 ) . To investigate a possible Rki function in vivo , we analyzed the presence of a putative bacteriophage promoter as well as the occurrence of rki transcripts during the course of RB43 infection . The putative rki gene promoter was identified and analyzed by a comparison with the consensus promoter described by Nolan et al . [34] . The putative rki promoter turns out to be very similar to the consensus RB43 early promoters with TAAAGT and TTGACA boxes located at −10 and −35 positions , respectively , and a consensus up element ( Figure 4A ) . Subsequently , we performed northern blot analysis using as controls two other genes known to be transcribed in the early ( g43 ) or late ( g37 . 2 ) phase of infection . As shown in Figure 4B , the rki transcript appears early , at 5 to 8 min following infection . These data are in agreement with the predicted presence of the rki early promoter . Finally , we asked whether the rki gene product is actually expressed during infection , by using a polyclonal antibody raised against Rki . The western blot analysis results presented in Figure 4C clearly show that , indeed , the Rki protein is expressed during the early phase of RB43 infection . It is known that at least some of the bacteriophage T4 proteins synthesized immediately following infection confer selective advantages to bacteriophages under specific environmental conditions , thus facilitating the timely progression from host to bacteriophage metabolism [35] . To examine such a possible role for Rki in vivo , we first engineered a deletion/replacement of rki by the gfp gene ( encoding green fluorescence protein ) by homologous recombination into RB43 genome . Because RB43 wild-type grows better on a dnaK mutant than on the isogenic wild-type strain in certain E . coli host backgrounds ( see below ) and because Rki toxicity is strictly DnaK-dependent , the Δrki::gfp mutant was isolated on a dnaK mutant host ( see the Materials and Methods section for details ) . Following recombination into the bacteriophage genome and PCR verification of the correct deletion/replacement , the absence of the Rki protein during bacteriophage infection at 30°C was confirmed by western blot analysis using polyclonal anti-Rki antibody ( Figure 5A ) . The RB43Δrki mutant and its isogenic parent were then tested for their ability to form plaques on wild-type E . coli hosts at various temperatures . Note that in sharp contrast with bacteriophage T4 , RB43 wild-type grows fairly well below 16°C and very poorly above 37°C ( Figure S3 ) . We found no significant difference at 37°C between the wild-type and RB43Δrki mutant when grown on the E . coli W3110 strain background . However , growth of RB43Δrki mutant was severely compromized at 14°C compared to the RB43 wild-type parent ( Figure 5B ) . The effect of the rki mutation on RB43 growth was significantly more severe when E . coli MC4100 was used as the host strain , as judged by the reduced plaque-forming ability of RB43Δrki mutant already observed at 30°C ( Figure 5C ) . To ensure that the phenotype was Rki-specific , we performed complementation experiments using Rki expressed from a plasmid under the control of an inducible promoter . The results presented in Figure 5D and Figure S4 , for MC4100 and W3110 strains respectively , show that the mutant growth defects are indeed due to the lack of Rki function . Taken together , these in vivo results indicate that although rki is not an absolutely essential gene , its presence confers a significant advantage to RB43 during infection , especially at more stringent temperatures ( i . e . , cold ) and can vary significantly depending on the particular E . coli host being infected . Next , we asked whether the phenotype of the Δrki mutant is indeed due to the lack of functional interaction with the host DnaK chaperone . To do so , we expressed the Rki ( H38Q ) mutant from a plasmid and tested its ability to complement the lack of Rki during bacteriophage infection . The results obtained in both the MC4100 ( Figure 5D ) and W3110 ( Figure S4 ) strain backgrounds clearly show that the J-domain mutant is not capable of complementing for the lack of Rki function at the non-permissive temperature of growth . In this case , expression of plasmid-encoded Rki ( H38Q ) was comparable to that of Rki wild-type ( Figure S4 ) . This result clearly demonstrates that Rki acts through a functional interaction with the DnaK chaperone in vivo during infection . The above results suggest that early during infection , Rki may recruit the DnaK chaperone function to directly facilitate various bacteriophage processes , such as transcription , DNA replication or protein folding . Yet , in sharp contrast with bacteriophages λ , P1 and P2 , T4 does not require the DnaK/DnaJ/GrpE chaperone machine for its DNA replication on an E . coli host [7] , [36]–[38] . Alternatively , Rki could inhibit a DnaK cellular function ( s ) detrimental to its proliferation , as it has been proposed for the host Hsp40 chaperone , which inhibits hepatitis B virus replication and capsule assembly [39] . To investigate this possibility , we first asked whether a mutation in dnaK restores growth to RB43Δrki . We used the MC4100 strain , which does not efficiently propagate RB43Δrki even at 30°C , a permissive temperature for a dnaK mutation , as a suitable host for such experiments ( Figure 5C ) [40] . We compared the ability of RB43 wild-type and RB43Δrki to form plaques on MC4100 and on its ΔdnaK52::CmR sidB1 ( BB1553 ) isogenic mutant derivative [40] . Note that the dnaK mutant strain BB1553 carries the sidB1 suppressor mutation in rpoH , allowing the cells to grow stably at 30°C [40] . As suspected , we found that the absence of DnaK efficiently suppresses the growth defect of RB43Δrki mutant ( Figure 6A ) . These results are in strong agreement with the DnaK-dependent toxicity of Rki and suggest that Rki , via its functional J-domain , could counteract some putative antagonistic function ( s ) of DnaK on bacteriophage RB43 growth . One of the main cellular functions of the DnaK/DnaJ/GrpE chaperone machine in E . coli is to control the entire σ32-dependent heat-shock response . Under normal conditions , it is known that DnaK and DnaJ can bind and target the heat-shock factor σ32 for degradation by the membrane-anchored FtsH protease , thus autoregulating their own synthesis and limiting that of the other σ32-dependent heat-shock proteins ( HSPs ) [41] . Following a heat stress , the DnaK chaperone is rapidly titrated away from σ32 by being recruited to unfolded and aggregated proteins , thus resulting in the stabilization of σ32 . In turn , stabilized σ32 binds to the RNA polymerase core leading to the transcription and induced transcription of more than one hundred HSP genes [42] , [43] . In agreement with such DnaK function , the deletion of dnaK leads to a 3–4 fold increase in the HSPs steady state levels , including the major stress chaperones ( e . g . , GroEL , HtpG , ClpB , IbpA/B ) and proteases ( e . g . , FtsH , Lon , ClpXP , HslUV ) . It is known that following infection with various eukaryotic viruses the synthesis of HSPs , including the chaperones Hsp27 , Hsp70 , Hsp40 and Hsp90 is induced ( review in [20] ) . In some cases , the increased level of HSPs directly helps viral replication as it has been observed with the SV40 , HIV-1 or CELO viruses [44]–[46] . Recently , Rawat and Mitra have shown that in human cell lines , the heat-shock factor 1 ( HSF1 ) , the major eukaryotic transcription factor that regulates transcription of the HSP genes in response to stress , is specifically induced during HIV-1 infection to directly drive viral gene expression and promote its own replication [44] . Taken all of the above observations together , we reasoned that immediately after infection , Rki may bind DnaK , thus triggering σ32 release and/or may somehow prevent its degradation by the FtsH protease . We first tested whether Rki expressed from a plasmid affects the levels of σ32 in the presence of DnaK . The results shown in Figure 6B demonstrate that indeed , expression of Rki rapidly leads to an increase in the endogenous σ32 levels . In sharp contrast , expression of the inactive Rki ( H38Q ) J-domain mutant does not affect σ32 levels , indicating that this process is DnaK-dependent . As expected , the level of HSPs was also concomitantly increased ( Figure 6C ) . Remarkably , further in vivo experiment revealed that co-overexpression of plasmid-encoded σ32 exacerbates Rki toxicity ( Figure S5 ) . This result strengthens the genetic link between Rki and σ32 and is in agreement with previous works demonstrating that high endogenous levels of σ32 are deleterious for E . coli at 30°C in the absence of a functional DnaK , possibly due to inappropriately high levels of HSPs [40] , [47] . We next asked whether the increased levels of endogenous σ32 in a wild-type E . coli background could help growth of the RB43Δrki mutant . The results presented in Figure 6D clearly show that indeed , expression of σ32 from a low-copy number plasmid fully suppresses the growth defect of RB43Δrki , even at the stringent temperatures of 22° and 39°C . The DnaK-dependent stabilization of σ32 by Rki suggests that Rki either inhibits DnaK , thus indirectly preventing σ32 transfer to FtsH at the membrane , or directly binds σ32 in complex with DnaK and prevents its degradation . To begin to answer such questions , we co-expressed a Flag-tagged Rki and wild-type σ32 in an ftsH mutant strain ( to avoid degradation of σ32 ) and performed in vivo pull-down experiments as described in Figure 2C . As a control , the same experiment was performed simultaneously with either a Flag-tagged DnaJ or the pBAD33 empty vector . The result presented in Figure 6E shows that as observed for DnaJ , Rki binds σ32 in vivo in the presence of DnaK . To investigate whether Rki binding to σ32 is dependent on DnaK , we next performed the same in vivo pull-down experiments using a DnaK depletion strain , in which chromosomally-encoded DnaK is under the control of a Tet-inducible promoter . Under the growth conditions tested , DnaK is barely detectable by western blot in the absence of anhydrotetracycline when compared to the isogenic wild-type strain ( Figure S6 ) . The results presented in Figure 6E clearly show that efficient binding of Rki to σ32 indeed depends on the presence of DnaK ( Figure 6E ) , thus suggesting that Rki could stabilize σ32 by acting directly on the DnaK-σ32 complex . How does stabilization of σ32 by Rki help RB43 growth ? Clearly , the increased levels of σ32 rapidly results in much higher intracellular levels of all HSPs , including GroEL which is absolutely essential for the proper folding of the bacteriophage RB43 major capsid protein Gp23 [48] . In agreement with this , Wiberg et al . ( 1988 ) showed that indeed the progeny yield of bacteriophage T4 increases dramatically when HSP synthesis is induced prior to bacteriophage infection , as does overexpression of the GroES/GroEL chaperone from a plasmid . However , in the case of Rki , induction of HSPs would occur shortly after infection , well before the synthesis of the capsid Gp23 protein . In sharp contrast with the full suppression exhibited by plasmid-encoded Rki and σ32 , we found that overexpression of GroESL only weakly suppresses the growth defect of RB43Δrki , as judged by the turbid plaques of RB43Δrki observed only at the less stringent temperature of 30°C on the MC4100 background ( Figure S6 ) . Nevertheless , in the context of infection , even a modest increase in GroEL levels could translate into an increase in Gp23 folding , resulting in a slight increase in bacteriophage production . Outside the laboratory , these seemingly minor increases would result in a small but significant selective advantage for maintaining rki in the genome . An alternative hypothesis is that stabilization of the heat-shock factor σ32 immediately after infection could directly help transcription of RB43 middle and/or late genes . Despite the fact that T4 encodes its own sigma factor gp55 for late transcription , it has been shown that a temperature upshift ( from 30° to 42°C ) performed a few minutes after infection by T4 dramatically affects transcription of late genes in the absence of σ32 , by an as yet unknown mechanism [49] . Such a mechanism involving σ32 could thus facilitate RB43 late gene expression under nonheat-shock conditions . In T4 , it is known that activation of transcription from middle promoters requires the host RNA polymerase and σ70 , as well as the two bacteriophage proteins MotA and AsiA [35] . Intriguingly , an in-depth comparative analysis of RB43 and T4 promoter regions neither detected middle promoter consensus sequences nor identified a motA ortholog in RB43 , thus suggesting a very different mechanism [34] . This work shows for the first time that bacteriophages can encode functional J-domain proteins capable of hijacking the host Hsp70 chaperone to facilitate viral proliferation . Our results show that , at least in the case of Rki , interaction with the host DnaK prevents degradation of the heat-shock factor σ32 via an unknown mechanism , thus conferring a selective advantage for RB43 under certain circumstances . As stated above , in bacteriophage RB16 the rki gene is fused with the downstream ORF058w , due to a single substitution in the stop codon of rki . The presence of the Rki-58 fusion protein , named Rki16 , during infection by RB16 was confirmed by western blot analysis , thus excluding the possibility of a DNA sequencing artifact ( Figure S7 ) . In addition , we found that overexpression of plasmid-encoded Rki16 fusion protein stabilizes σ32 and complements the RB43Δrki growth-sensitive phenotype , albeit considerably less efficiently than Rki . In agreement with this , the Rki-58 fusion protein is considerably less toxic than Rki ( Figure S7 ) . To date , nothing is known about the function of RB43 ORF058w , whose product possesses a weak similarity with an uncharacterized conserved domain PTZ00121 at its C-terminus ( http://www . ncbi . nlm . nih . gov ) . Yet , in the case of Rki , co-overexpression of the ORF058w gene product does not affect either the stabilization of σ32 or Rki toxicity ( Figure S7 ) . This indicates that within the limit of our experimental conditions , ORF058w does not significantly influence Rki function in RB43 . Interestingly , in addition to its J-domain protein Rki , the bacteriophage RB43 possesses two other uncharacterized small ORFan genes , namely ORF179c ( 61 amino acid residue gene product; Uniprot Q56BL9 ) and ORF191c ( 106 amino acid residue gene product; Uniprot Q56BK7 ) , whose gene products displays significant sequence similarity with the conserved zinc-binding domain of DnaJ , known to be critical for both substrate binding and activation of the DnaK chaperone cycle [50] . It is intriguing that RB43 potentially expresses several proteins that display homology with distinct domains important for DnaJ cochaperone function . One attractive hypothesis is that multiple DnaJ-like bacteriophage proteins could act in concert to hijack ( or inhibit ) the host DnaK/DnaJ/GrpE chaperone machine in order to facilitate bacteriophage proliferation under different environmental conditions .
Genetic experiments were carried out in E . coli K-12 MC4100 or W3110 strains . Strains MC4100 and BB1553 [40] , and AR3291 ( W3110 sfhC21 zad220::Tn10 ΔftsH3::KanR; [6] ) have been described . The strain FA1195 PtetdnaKJ is an MG1655 derivative in which the endogenous dnaKdnaJ promoter is replaced by the tetracycline promoter Ptet , together with the upstream terR repressor . In this case , expression of DnaK is dependent on the presence of anhydrotetracycline ( Frederic Angles , laboratory collection ) . Mutations were moved in different genetic backgrounds using bacteriophage P1-mediated transduction at 30°C . To construct the single , double or triple JDP mutants in the W3110 strain background , the Δ3 strain ( MC4100 dnaJ::Tn10-42 , ΔcbpA::kanR , ΔdjlA::ΩspcR; [33] ) was used as donor . The ΔdnaK52::CmR [2] , ΔhscC::kanR ( JWK0645; Keio Collection ) and ΔhscA::kanR ( JWK2510; Keio Collection ) mutant alleles have been described . Bacteriophages RB43 [26] , λcI , λcIdnaJ+ and P1 ( laboratory collection ) were maintained on W3110 at 30°C . The RB43Δrki::gfp deletion/replacement mutant was constructed as follows . The 717 bp long gfp gene was first amplified using primers RBGFP1 ( 5′- GAACGGAAAATGAGTAAAGGAGAAGAAC ) and RNGFP3 ( 5′-CATTACCGCTAATTTATTTGTAGAGCTCATCC ) . Thr 1212 bp region upstream rki was amplified using primers RB1 ( 5′-GCAGGATCCCTGGTGCAGACCGAACGG ) and RBGFP4 ( 5′-CTTTACTCATTTTCCGTTCCTCAAAATAAAAG ) , and the 835 bp region downstream rki was amplified using primers RBGFP2 ( 5′-CTACAAATAAATTAGCGGTAATGATATCTATG ) and RB3 ( 5′-CCCAAGCTTGGGCATGAGCCTTATCAACTGCTG ) . The three PCR fragments were assembled by the two-step fusion PCR method , resulting in a 2764 bp long fragment containing the gfp gene flanked by both the upstream and downstream genomic regions of rki . This fragment was then digested with HindIII and ligated into plasmid pMPMA6Ω previously digested with EcoRV and HindIII . Next , the E . coli B178 strain transformed with the resulting plasmid was grown to mid-log phase at 30°C in LB supplemented with ampicillin and 200 µl of the culture was then infected with 106 RB43 bacteriophages for 20 min at 20°C . Eight ml of LB amp were added and the culture was incubated at 37°C for 3 h with shaking until lysis occurred . Next , 100 µl of mid-log phase culture of B178 dnaK103 mutant strain was mixed with the bacteriophage lysate from above to obtain about 400 pfu per plate following overnight incubation at 30°C . Plaques were then transferred to nitrocellulose filters by Benton Davies method and DNA was bound with Stratalinker . The prehybridation took place at 68°C for 3 h and hybridation was carried out overnight at 68°C . These two steps were carried on with gfp DNA fragment labeled with Dig and the reaction tubes were boiled for 10 min . Then , the filters were washed at 65°C first in 2× SSC , 0 . 1% SDS and then in 0 . 1× SSC , 0 . 1% SDS before they were incubated with anti-Dig alkaline phosphate and revealed with NTB + BIPC . The genomes of both RB43 wild-type ( accession HE858210 ) and RB43Δrki::gfp mutant ( accession HE981739 ) used in this study were sequenced using the NGS/Illumina method ( LGC Genomics ) . Analysis of the wild-type genome revealed that the sequence ( with approximately 99% coverage ) of the RB43 bacteriophage used in this study differs from the published RB43 genome sequence by at least 107 nucleotides ( http://phage . ggc . edu/ ) . Apart from the Δrki::gfp deletion/replacement , 106 of these nucleotide differences were common to both RB43 wild-type and RB43Δrki::gfp mutant , whereas one mutation was different in the two bacteriophages but affected the same codon . This mutation was located in the hypervariable region of a putative adhesin gene 38 and corresponds to single nucleotide changes , CAA ( Gln100 ) to AAA ( Lys ) for the wild-type and to CGA ( Arg ) for the RB43Δrki::gfp mutant . Changes for lysine or arginine residues at this position in gp38 from bacteriophages RB42 and RB43 are known to facilitate recognition of the E . coli K-12 hosts [28] . Moreover , one mutation was found only in the RB43Δrki::gfp mutant . This mutation corresponds to a single nucleotide change GCT ( Ala5 ) to CCT ( Pro ) in gene 62 encoding for one subunit of the clamp-loader ( Gp44/Gp62 ) involved in T4 DNA replication and transcription of late genes [51] . Whether these mutations are linked to the simultaneous deletion of rki is unknown . Arguing against this possibility , the mutations were not present in another , independent , cold-sensitive RB43Δrki::gfp bacteriophage isolate . In addition , overexpression of the wild-type Gp62 from a plasmid did not rescue the cold-sensitive phenotype of either RB43Δrki ( Elsa Perrody , unpublished data ) . Plasmids pBAD22 , pBAD33 and pBAD24 ( Guzman et al . , 1995 ) , p29SEN ( Genevaux et al . , 2004 ) , pWKG90 ( pBAD22-DnaJ ) and pWKG90KPN ( pBAD22-DnaJ-H71T ) [30] , pGPPK [33] have been described previously . To construct plasmid pBAD22-DnaJFlag , containing DnaJ with the N-terminal Flag tag “MASDYKDDDDKSG” , the dnaJ gene was PCR-amplified using primers dnaJ-flagfor ( 5′-GCGAATTCATGGCAAGCGACTACAAAGATGACGACGATAAAAGCGGCATGGCTAAGCAAGATTATTACG ) and dnaJrev ( 5′-GCAAGCTTGCATGCTTAGCGGGTCAGGTCGTCAA ) , and pWKG90 DNA as template . The resulting PCR fragment was digested with EcoRI and SphI and ligated into pBAD22 previously digested with the same enzymes . Plasmid pBAD33-DnaJFlag was then constructed by subcloning of the EcoRV/SphI DnaJFlag fragment from pBAD22-DnaJFlag into EcoRV/SphI pBAD33 . Plasmid pBAD22-Rki was constructed as follows . The 714 bp long rki gene was PCR amplified using primers RB43DnaJfor ( GCGAATTCATGATTAACGAAAAAATGACA ) and RB43DnaJrev ( GCAGATCTAAGCTTTATGCGTCTAAGTGCTTGCG ) , digested with EcoRI and BglII and ligated into pBAD22 previously digested with the same enzymes . The pBAD22-rkiH38Q plasmid was constructed by the two-step PCR method using mutant primers H38Qfor ( 5′-CTCTGCGTAATCAGCCCGATCGTGG-3′ ) and H38Qrev ( 5′-CCACGATCGGGCTGATTACGCAGAG-3′ ) . To construct pBAD33-Rki , the rki gene was subcloned from pBAD22-Rki as an EcoRV/HindIII digested fragment and cloned into pBAD33 previously digested with the same enzymes . To construct pBAD24-RkiFlag , containing Rki with the N-terminal Flag tag , the rki gene was first PCR-amplified from pBAD22-Rki using primers RkiFlag-For ( 5′-GCTCCATGGCAAGCGACTACAAAGATGACGACGATAAAAGCGGCATGATTAACGAAAAAATGACACAT ) and Rki-Rev ( 5′- GAAAGCTTGGATCCTT ATGCGTCTAAGTGCTTGCGGAAAG ) . The resulting 749 bp fragment was digested with NcoI and BamHI and ligated into pBAD24 previously digested with the same enzymes . The same procedure was applied to construct pBAD24-Rki ( H38Q ) Flag using pBAD22-Rki ( H38Q ) as template . To construct pBAD33-RkiFlag , the rkiFlag gene from pBAD24-RkiFlag was subcloned as an EcoRV/HindIII digested fragment into pBAD33 previously digested with the same enzymes . To obtain p29SEN-Rki , the rki gene was PCR-amplified using primers EPw57f ( 5′-CGCAATTGTCATGATTAACGAAAAAATGACA ) and rkiCter-rev ( 5′- GCAAGCTTGGATCCTTATGCGTCTAAGTGCTTGCG ) and pBAD22-Rki as template . The resulting 733 bp fragment was digested with MfeI and HindIII and ligated into p29SEN digested with the same enzymes . The same procedure was followed for p29SEN-Rki ( H38Q ) with pBAD22-Rki ( H38Q ) as template . Construction of pET15b-RkiHis6 expressing Rki with an N-terminal 6×His tag was performed as follows . Both primers HisRB43Jfor ( 5′-GCCCCATGGGCAGCAGCCATCATCATCATCATCATAGCAGCATGATTAACGAAAAAATGACACAT-3′ ) and RB43J-rev ( 5′-GCAGATCTAAGCTTTATGCGTCTAAGTGCTTGCG ) were used to PCR amplify rki from pBAD22-Rki . The resulting rki-his PCR fragment was cloned as an NcoI/HindIII fragment into pBAD24 previously digested with the same enzymes . The rki-his gene was then subcloned as an NcoI/BglII digested fragment into pET15b vector ( Novagen ) previously digested with the same enzymes . The same procedure was used to construct pET15b-Rki ( H38Q ) His6 , except that pBAD22-Rki ( H38 ) was used as DNA template . The Rki-DnaJ and Rki ( H38Q ) -DnaJ chimeras containing the 77 amino acid long N-terminal J-domain sequence of Rki grafted into E . coli's DnaJ were constructed as described ( Kelley and Georgopoulos , 1997 ) . Briefly , the 231 bp long fragment containing the Rki J-domain was PCR amplified using primers BR43DnaJfor and SRB43JKpnIrev ( 5′-GCGGTACCCGCTGCGTGACGCGCTCGCAT ) , and RB43 DNA as template . The PCR products were cloned as EcoRI/KpnI fragements into pWKG90KPN plasmid [30] . To construct p29SEN-RpoH , the 855 bp long rpoH gene was PCR-amplified using primers rpohfor ( 5′-GAGAATTCCATATGACTGACAAAATGCAAAG ) and rpohrev ( 5′-GAAAGCTTGGATCCTTACGCTTCAATGGCAGCAC ) , and E . coli MG1655 genomic DNA as template . The PCR fragment was ligated as an EcoRI/HindIII fragment into EcoRI/HindIII p29SEN . All the constructs obtained by PCR were sequenced verified using the appropriate primers . Bacterial motility and bacteriophage λ plating assays were performed at 30°C as described [29] . To monitor bacterial viability , mid-log phase cultures of fresh transformants grown in LB medium ( tryptone 10 g/L , NaCl 10 g/L , yeast extract 5 g/L , thymine 20 g/L , NaOH 3 mM ) were serially diluted and spotted on LB agar plates ( agar 15 g/L ) supplemented when necessary with the appropriate antibiotics ( 100 µg/ml ampicillin , 20 µg/ml chloramphenicol , 20 µg/ml kanamycin ) and various L-arabinose or IPTG-inducers . Note that 0 . 2% glucose was added to overnight cultures in order to prevent Rki toxicity . RB43 plaque-forming ability was monitored as follows . Overnight cultures of E . coli grown in LB medium were diluted 1∶100 and grown with shaking to an OD600 of 0 . 7 at the indicated temperature . Cultures were then concentrated 10-folds in the same medium and bacterial lawns were prepared by mixing 300 µl of cells with 3 ml of pre-warmed H-Top medium ( tryptone 10 g/L , NaCl 8 g/L , Na citrate 2 . 4 g/L , glucose 3 g/L , NaOH 0 . 5 mM , agar 7 g/L ) and subsequently pouring the mix onto LB agar plates . Both , H-Top and LB plates were supplemented with the appropriate antibiotics and/or inducers when necessary . Serial dilutions of bacteriophage lysates were then spotted on bacterial lawns and plates incubated as indicated in the figure legends . Cells were grown in 100 ml LB supplemented with the appropriate antibiotics to an OD600 of 1 . 2 and harvested by centrifugation at 7000 rpm for 30 min at 4°C in a Beckman JA14 rotor . Pellets were resuspended in 1 ml of IP buffer ( 50 mM Tris-HCl buffer , pH 7 . 5 , 0 . 15 M NaCl , 20% ( v/v ) glycerol , 10 mM PMSF , 1 µl/ml Benzonase , 1 mg/ml lysozyme ) , sonicated twice for 20 sec and centrifuged at 14000 g for 30 min at 4°C . Supernatants were incubated 30 min at 25°C and 10 mM ADP , Hexokinase and 0 . 2% glucose was added for 15 min at 20°C . The samples were then incubated at 4°C for 2 h with 25 µl of anti-Flag M2-agarose suspension ( Sigma ) , washed with 6 ml TBS ( 50 mM Tris-HCl buffer , pH 7 . 5 and 0 . 15 M NaCl ) , and the bound proteins were eluted with 30 µl of TBS containing 5 µg of FLAG peptide ( Sigma ) . Proteins were separated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis ( SDS-PAGE ) ( 4–12% Biorad ) . Bacterial cultures ( 16 ml/infection ) were grown at 30°C in LB medium to a density of 4 . 108 cells/ml . Cells were concentrated 4-fold in the same medium and bacteriophage infections were initiated by mixing 4 ml of cells with the adequate volume of RB43 bacteriophage stock ( multiplicity of infection ( MOI ) of 10 ) . Cells were then incubated at 30°C with shaking and infections were stopped at the desired time by adding 400 µl of pre-heated RNA lysis buffer ( 0 . 5 M Tris-HCl , 20 mM EDTA , 10% SDS , pH 6 . 8 ) and incubating in boiling water for 2 min . One volume of phenol was added and after mixing one volume of chloroform . Samples were incubated for 10 min at 30°c under shacking and centrifuged in order to collect the aqueous phase . Three more phenol/chloroform extractions were carried out . Nucleic acids were precipitated by mixing 2 . 5 volumes of prechilled ethanol ( −20°C ) in the presence of 0 . 3 M sodium-acetate at pH 5 . 7 and incubating at −20°C for at least 1 h . The pellet was collected by centrifugation ( 8000 rpm , 30 min ) , dried and resuspended in 250 µl of DEPC treated water . Small samples ( usually 5 µl ) were examined for RNA degradation and DNA contamination by electrophoresis on agarose gel containing ethidium bromide . Each infection allowed us to collect 200 to 300 µg of viral RNA . 50 µg of RB43 RNA , prepared as described above were treated with 100 units of DNAse I FPLCpure ( Amersham ) and precipitated by mixing 2 . 5 volumes of prechilled ( −20°C ) ethanol and 0 . 3 M sodium-acetate at pH 5 . 7 and incubating at −20°C for at least 1 h . Pellet was collected by centrifugation ( 8000 rpm , 30 min ) , dried and resuspended in 17 . 5 µl of DEPC treated water . A mix containing 10 µl of 10× MOPS , 17 . 5 µl of formaldehyde and 50 µl of formamide was prepared and mixed to the resuspended RNA . Samples were then incubated at 55°C for 15 min . Ten µl of 10× RNA loading buffer ( 1 mM EDTA pH 8 , 50% ( v/v ) glycerol , 0 . 25% bromophenol blue , 0 . 25% xylene cyanol FF ) and 5 µl of ethidium bromide ( 10 mg/ml ) were added to the mix . 10 µl of each samples were used for adjusting the loading amount of RNA by running on an agarose gel . Samples ( usually 15 µl ) were then electrophoresed at room temperature for 3 h in 1% agarose gel ( 180 ml final volume ) prepared in 1× MOPS containing 9 . 7 ml of formaldehyde . RNA integrity was verified under UV lamps . The resolved RNA population was subsequently transferred on a positively charged nylon membrane ( Hybond-N+ membrane from Amersham pharmacia biotech ) by salt diffusion over-night . RNA was UV cross-linked to the membrane and the efficiency of transfer was examined by methylene blue staining . The membrane was then prehybridized for 30 min at 68°C in hybridization buffer ( 7% SDS , 250 mM NaPi ( 0 . 77 M Na2HPO4/0 . 22 M NaN2PO4 mix ) , 2 mM EDTA ) . Prehybridization buffer was discarded and replaced by fresh buffer . 32P-labeled probe ( see below ) was added and hybridization was carried out over night at 68°C . The membrane was then washed twice at 60°C in a 5% SDS , 250 mM NaPi and 2 mM EDTA solution for 20 min and once in a 1% SDS , 250 mM NaPi , 2 mM EDTA solution for 30 min . Detection of the signals on autoradiograms was performed by exposure of the membrane at −80°C for 5–12 h in presence of an intensifying screen . Probes consisted of PCR products obtained by amplifying the desired fragments from the RB43 genomic DNA using the pfu polymerase . The PCR products were purified from 1 . 5% agarose gels using the Qiaquick gel extraction kit from Qiagen ( cat . No . 28706 ) . 2 µl of the PCR products were used as a template for a new PCR reaction containing 32P-αdCTP ( 1 . 5 mM MgCl2 , 2 µM of each primers , 2 mM of dATP , dTTP , dGTP , 0 . 2 mM dCTP ( 0 . 1 mM ) , 5 µl of 32P-αdCTP ( 10 µCi/µl ) , 5 units of Hot-start Taq ( Qiagen , 1× buffer ) . The PCR products were separated from free radioactivity by using Qiaquick gel extraction kit according to the furnisher . 100 µl of sonicated salmon sperm DNA ( 10 mg/ml ) were added and the mixture was incubated at 95°C for 2 min and then diluted in 1 ml of hybridization buffer . Location of the different primers used is indicated in Figure 4 and their respective sequences were: for gene 43 probe ( 700 bp long ) : 43gp43 . 0 ( 5′-ATGAATGAATTTTATCTATCA-3′ ) and 43gp43 . 3 ( 5′-CACGCCATAAATTTCGTATCC-3′ ) . For gene 37 probe ( 342 bp long ) : 43gp372am6 ( 5′-TAATTTGCCTTTACTCCCTACTGGA-3′ ) and 43gp372am3 ( 5′- GGATCGGAAGTATTCTATTTTGTGTT-3′ ) . For ORF057 probe ( 480 bp long ) : RB43Jfor ( 5′-GCGAATTCATGATTAACGAAAAAATGACA-3′ ) and 43gpJDTM2 ( 5′- CCAAGCTTACATCAAACCTTTACCTTCTTC-3′ ) . To avoid the toxic effect of protein overexpression in wild type E . coli , Rki and RkiH38Q were purified from the BL21ΔdnaKdnaJ strain [33] . Fresh overnight cultures were diluted 1∶100 in 500 ml of LB broth supplemented with 100 µg/µl ampicillin and grown with vigorous shaking at 30°C . At an OD600 of 0 . 3 , 2 mM IPTG was added for 2 h . Cells were harvested at 7000 rpm for 30 min at 4°C in a Beckman JA14 rotor and pellets were stored at −80°C . Pellets were resuspended in 20 ml of lysis buffer ( 50 mM NaH2PO4 , pH 8 . 0 , 300 mM NaCl , 10 mM Imidazole ) , 1 mg/ml lysozyme was then added and the cell suspensions were kept on ice for 30 min . After addition of Protease Inhibitor ( Roche ) , cells were sonicated 6×20 s on ice and centrifuged at 12000 rpm for 30 min at 4°C in a Beckman JA25 . 50 rotor . Supernatants were collected , 45% ammonium sulfate was added and samples were incubated overnight at 4°C under mild shaking . Samples were then centrifuged at 10000 rpm for 10 min at 4°C in Beckman JA25 . 50 rotor . The supernatants were dialyzed twice for 2 h in 2 L of lysis buffer in a Spectra/Por® Membrane , MWCO 12–14000 cut off 3 . 5 kDa . The dialysates were applied to a 4 ml of nickel-nitrilotriacetic acid columns preequilibrated with 10 ml of lysis buffer . The following steps were performed as described in the procedure from Qiagen for the purification of His6-tagged proteins from E . coli using nickelnitrilotriacetic acid superflow under native conditions , using lysis buffer supplemented with 20 mM imidazole as washing buffer and using 250 mM imidazole as elution buffer . The proteins were stored at −80°C in buffer containing 25 mM HEPES buffer , pH 7 . 6 , 0 . 4 M KCl , 1 mM DTT , 10% ( v/v ) glycerol . DnaK purification was performed as described [33] , and DnaJ and GrpE were purchased from Stressgen . ATPase activity was essentially carried out as described [52] , with minor modifications . Reactions were performed in 10 µl reaction buffer ( 30 mM HEPES buffer , pH7 . 6 , 40 mM KCl , 10 mM NaCl , 4 mM MgAc , 2 mM DTT , 0 . 29 mg/ml BSA , 0 . 1 mM ATP ) in presence of 1 µM DnaK , 1 µM GrpE , 1 µCi [γ32P]ATP , and increasing concentrations ( 0 . 2 , 0 . 4 , 0 . 6 or 0 . 8 µM ) of DnaJ , Rki or RkiH38Q . Three µl of 0 or the 20 min reaction were spotted on thin layer chromatography and migrated in migration buffer containing 0 . 15 M LiCl and 0 . 15 M formic acid . The amount of liberated γ-phosphate was quantified using phosphrimaging . Firefly luciferase aggregation was performed as described [33] , except that luciferase was denatured for 90 min at 25°C and aggregation kinetics were followed at 25°C . The protein concentrations used are described in the figure legend . Reactivation of firefly luciferase was performed essentially as described [33] . Briefly , 25 µM luciferase ( Sigma ) was denatured for 2 h at 22°C in 30 mM Tris-HCl buffer , pH 7 . 6 , 6 M guanidinium chloride , 5 mM DTT . Denatured luciferase was diluted to a final concentration of 0 . 125 µM into a reaction mixture ( 50 µl final ) containing 100 mM MOPS , 500 mM KCl , 50 mM MgCl2 , 20 mM creatine phosphate , 0 . 1 mg . mL−1 creatine kinase , 5 mM ATP , 0 . 015% bovine serum albumin , 0 . 5 µM DnaK and 0 . 125 µM GrpE . All components were incubated on ice . Refolding was initiated by adding either DnaJ or DnaJ mutant protein ( 0 . 125 µM each ) . The luciferase activity was measured at different time points after incubation at 22°C by using 10 µL of the luciferase assay system from Promega ( E1500 ) and a Berthold Centro LB960 luminometer .
|
Bacteriophages are the most abundant biological entities on earth . As a consequence , they represent the largest reservoir of unexplored genetic information . They control bacterial growth , mediate horizontal gene transfer , and thus exert profound influence on microbial ecology and growth . One of the striking features of bacteriophages is that they code for many open reading frames of thus far unknown biological function ( called ORFans ) , which have been referred to as the dark matter of our biosphere . Here we have extensively characterized such a novel ORFan-encoded protein , Rki , encoded by the large , virulent enterobacteriaceae bacteriophage RB43 . We show that Rki functions to control the host stress-response during the early stages of bacteriophage infection , specifically by interacting with the host DnaK/Hsp70 chaperone to stabilize the major host heat-shock factor , σ32 .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbial",
"mutation",
"microbiology",
"gene",
"function",
"microbial",
"evolution",
"molecular",
"genetics",
"microbial",
"growth",
"and",
"development",
"microbial",
"physiology",
"proteins",
"biology",
"microbial",
"ecology",
"biochemistry",
"virology",
"gene",
"identification",
"and",
"analysis",
"genetics",
"microbial",
"control",
"genetics",
"and",
"genomics"
] |
2012
|
A Bacteriophage-Encoded J-Domain Protein Interacts with the DnaK/Hsp70 Chaperone and Stabilizes the Heat-Shock Factor σ32 of Escherichia coli
|
During retrovirus particle maturation , the assembled Gag polyprotein is cleaved by the viral protease into matrix ( MA ) , capsid ( CA ) , and nucleocapsid ( NC ) proteins . To form the mature viral capsid , CA rearranges , resulting in a lattice composed of hexameric and pentameric CA units . Recent structural studies of assembled HIV-1 CA revealed several inter-subunit interfaces in the capsid lattice , including a three-fold interhexamer interface that is critical for proper capsid stability . Although a general architecture of immature particles has been provided by cryo-electron tomographic studies , the structural details of the immature particle and the maturation pathway remain unknown . Here , we used cryo-electron microscopy ( cryoEM ) to determine the structure of tubular assemblies of the HIV-1 CA-SP1-NC protein . Relative to the mature assembled CA structure , we observed a marked conformational difference in the position of the CA-CTD relative to the NTD in the CA-SP1-NC assembly , involving the flexible hinge connecting the two domains . This difference was verified via engineered disulfide crosslinking , revealing that inter-hexamer contacts , in particular those at the pseudo three-fold axis , are altered in the CA-SP1-NC assemblies compared to the CA assemblies . Results from crosslinking analyses of mature and immature HIV-1 particles containing the same Cys substitutions in the Gag protein are consistent with these findings . We further show that cleavage of preassembled CA-SP1-NC by HIV-1 protease in vitro leads to release of SP1 and NC without disassembly of the lattice . Collectively , our results indicate that the proteolytic cleavage of Gag leads to a structural reorganization of the polypeptide and creates the three-fold interhexamer interface , important for the formation of infectious HIV-1 particles .
The Gag polyprotein encompasses the major structural elements responsible for assembly of retroviruses , including human immunodeficiency virus type 1 ( HIV-1 ) . Assembly and budding involve Gag self-association and interactions with the host cell plasma membrane , the viral genomic RNA , and host cell dependency factors , leading to the formation of immature , non-infectious , spherical virus particles [1] , [2] . The immature particles undergo maturation , resulting in a dramatic morphological rearrangement of viral components [3] , [4] . This process is initiated by proteolytic cleavage of Gag into the structural proteins , matrix ( MA ) , capsid ( CA ) , and nucleocapsid ( NC ) , as well as additional peptide sequences that vary among retroviruses ( p6 and spacer peptides , SP1 and SP2 , in the case of HIV-1 ) [5] . In the mature virion , MA ( N-terminal Gag ) remains associated with the viral membrane , and CA condenses into a distinct conical capsid shell ( core ) that encapsulates the viral enzymes reverse transcriptase and integrase along with the viral RNA genome , which is coated with NC [6] . The structures and functions of mature MA , CA , and NC proteins and of the mature capsid have been studied extensively through biochemical [7]–[12] , biophysical [13]–[17] and structural analyses [12] , [17]–[28] , while the structures of immature Gag and the maturation intermediates are less well known . The overall architecture of the immature HIV-1 Gag and Gag-cleavage mutants have been studied using cryo-electron tomography ( cryoET ) [1] , [2] , [29]–[32] , revealing partial coverage of the inner viral membrane by Gag , as a hexagonal lattice with ∼80 Å spacing [1] , [30] , [31] . The roles of specific HIV-1 Gag components in immature particle assembly [2] have been analyzed , and mutational analyses revealed that dimerization of the CA portion of Gag is critical for efficient assembly [11] . The NC component of Gag , which binds the viral RNA , aids in Gag-Gag interactions and particle assembly [29] , [33] . Further , in vitro assembly of Gag , and of the CA-SP1-NC Gag fragment , depends upon NC interactions with nucleic acid [34] , [35] . The precise mechanisms underlying transition from the “immature" Gag lattice to the mature capsid lattice , and the conformational changes that take place during maturation , are not well understood . Several models have been proposed , including de novo assembly of CA monomers or hexamers after proteolysis [22] and trigger-mediated conformational switch mechanisms [36] , [37] . Mutations and drugs that block cleavage at CA-SP1 and SP1-NC prevent core condensation and result in impaired infectivity [38] , [39] . Therefore , structural information on the C-terminal portion of Gag and the conformational changes that are associated with CA-SP1-NC cleavage and release of SP1 and NC will aid in our understanding of the maturation process . To study the intersubunit interfaces contributing to the immature HIV-1 lattice , we used cryoEM and real-space helical reconstruction of in vitro assembled HIV-1 CA-SP1-NC tubes and obtained density maps at 13 Å resolution; we compared these with those of HIV-1 CA tubes at 11 Å resolution . Molecular docking of atomic CA structures into both density maps revealed a distinct conformational difference in the CA-CTD: namely a 34° rotation of the CTD relative to the NTD via the connecting hinge . Our data support the model in which proteolytic cleavage of Gag results in a structural reorganization of the inter-hexamer ( trimer ) interface that is required for mature capsid formation .
Previous studies on the mature capsid structure revealed several intermolecular interfaces that are critical for capsid function , namely the NTD-NTD , NTD-CTD , CTD dimer and CTD trimer interfaces [12] , [17]–[28] . We sought to determine whether the equivalent interfaces exist during an intermediate stage of virus maturation and to delineate the structural changes that occur upon proteolytic release of CA from Gag . In particular , we assembled CA-SP1-NC tubes in the presence of nucleic acid [40] and compared the ‘immature’ CA structure in these assemblies with that of ‘mature’ CA tubes by CryoEM . The CA-SP1-NC tubes exhibited double-layer densities ( Fig . 1A & B ) , with an average diameter of 468±10 Å for the outer layer and 270±8 Å for the inner layer . Even though the diameter between the tubes varied , the distance between the outer and inner layer densities was invariant with a value of 100±2 Å . The CA-SP1-NC tubes displayed well-ordered helical symmetry and exhibited layer lines to at least 23 Å resolution ( Fig . 1C ) . Among many helical families , we selected six of the best quality tubes of ( −14 , 11 ) helicity and carried out real-space helical reconstruction [41] . A final 3D density map at 13 Å resolution was obtained ( Fig . S1A ) . For comparison , we also processed twelve CA tubes , each possessing ( −12 , 11 ) helical symmetry , to generate a density map at 11 Å resolution ( Fig . 1G–I and Fig . S1C ) . The CA-SP1-NC tubular structure exhibits two-fold symmetry , with an overall two-fold phase residual of 27 . 8° . The dimensions of the surface unit cell are a = 95 . 1 Å , b = 102 . 6 Å , γ = 109 . 7° ( measured at radius = 234 Å ) , slightly smaller than those obtained from the CA ( −13 , 11 ) tubes analyzed previously , at 16 Å resolution [20] , and the CA ( −12 , 11 ) tubes described here ( a = 99 Å , b = 102 Å , γ = 108° ( measured at radius = 213 Å ) ) , at 11 Å resolution . The CA-SP1-NC density map displays a 74 Å thick outer layer with a hexagonal surface lattice and a 53 Å thick , more diffuse , inner layer ( Fig . 1D–F ) . The outer layer consists of CA hexamers ( Fig . 1D ) , similar to CA assemblies , while the inner layer most likely comprises the NC protein and nucleic acid . The latter are required for CA-SP1-NC assembly . The poorly-defined densities in the inner layer suggest that the molecular structure in this region is flexible and/or poorly ordered , consistent with data from tomographic studies of immature particles [1] that revealed the absence of an ordered lattice in the NC region . There is a distinctive space ( ∼36 Å ) between the CA and NC density layers , suggesting that the SP1 peptide may span this distance . The CA reconstruction at 11 Å resolution from the assembly with ( −12 , 11 ) helical symmetry ( Fig . 1G–I ) , exhibits essentially the same CA structure as that described previously for the ( −13 , 11 ) helical assembly [20] . For comparison with CA-SP1-NC , the density map from ( −12 , 11 ) helical family tubes was used for subsequent structural analysis , owing to its higher resolution . For a detailed comparison of the CA structure in the CA and CA-SP1-NC assemblies , we docked atomic models of the CA-NTD ( PDB 3h47 ) [19] and the solution CA-CTD dimer ( PDB 2kod ) [20] , separately , into the CA-SP1-NC density map using a correlation-based automated rigid-body fitting method [20] . The pseudo-atomic model fits the CA-SP1-NC density envelope very well ( Fig . 2 ) , as measured by cross-correlation function ( CCF ) between the model and density map ( CCF = 0 . 95 for CA-NTD and 0 . 94 for CA-CTD , respectively ) . Three of the previously characterized CA intermolecular interfaces , NTD-NTD , NTD-CTD , and CTD-CTD dimer [19]–[21] , are also observed in the CA-SP1-NC tubular structure , although details of the contact residues may vary . Interactions between neighboring CA-SP1-NC hexamers are primarily mediated by the CTD dimers ( Fig . 2A & B ) ) ; however , in contrast to the previous CA structure [20] and the current 11 Å map , the intermolecular trimer contact at the pseudo three-fold axis is not observed ( Fig . 2C ) . Unlike CA , modeling of SP1 and NC in the density map was not straightforward . The distinctive pillar-like structures previously described in immature VLPs [1] , [22] , [30] are not observed , and only very weak electron density is present in the region between the CA layer and the inner NC/nucleic acid layer of the CA-SP1-NC assemblies ( Fig . 1E & F ) . Further , the diffuse density in the NC/nucleic acid region precludes the docking of a NC structural model with any confidence and suggests that , in these tubes , NC and the nucleic acid are not well-ordered , consistent with previous studies [1] . This notion is further supported by the lower resolution in this region ( 24 Å compared to 13 Å in the CA region ( Fig . S1A & B ) ) . With regard to the very weak electron density in the SP1 region , we considered several possible scenarios: 1 ) SP1 may form an α-helical bundle [42] , [43] that does not possess helical symmetry , thus the density would not be apparent with helical reconstruction; 2 ) SP1 has a flexible connection to the CA-CTD , thus the density for SP1 is smeared out after averaging; and 3 ) SP1 adopts a random coil structure with some nascent , fluctuating helical population , as suggested by the NMR analysis of the CA-CTD-SP1-NC protein in solution [44] . Based on the present structure , which was reconstructed using helical symmetry , we are unable to distinguish between these scenarios . As a first approximation , we constructed a model for CA-SP1 by connecting the SP1 NMR structure model ( PDB 1u57 ) , determined in the presence of trifluoroethanol [45] , to the CA-CTD by superimposing the overlap region ( LEEMMTACQG ) from the CA-CTD ( PDB 2kod ) and the SP1 structures ( Fig . 2D , inset ) . Interestingly , the resulting six α-helical SP1 segments point toward the interior diffuse NC/nucleic acid density ( Fig . 2D ) . Thus , it is plausible that SP1 adopts α-helical conformation in the assembled state , as recently suggested [46] . The pseudo-atomic models for assembled CA and CA-SP1-NC tubes permits delineation of the structural differences in CA when C-terminal Gag sequences are present . Within the CA monomer , a major conformational difference is observed in the relative orientation between the CTD and the NTD ( Fig . 3A ) . Specifically , the CTD domain is rotated approximately 34 degrees relative to the NTD through a flexible hinge ( Video S1 ) . Our current data suggest that this hinge plays a pivotal role in transmitting CA conformational changes upon protease cleavage , further underscoring the importance of the hinge region in the formation of mature capsid [47] . To evaluate whether and how this change in the monomer impacts the interfaces in the assembly , we carried out detailed comparative analyses of the intermolecular NTD-NTD and CTD-CTD trimer interfaces in the assembled ‘mature’ and ‘immature’ capsids [20] , [21] . While the first interface is involved in forming the CA hexamer or pentamer [18] , [19] , the latter connects CTD domains from adjacent hexamers and is important for forming the extended lattice [20] . The hexamer-forming NTD-NTD interactions present in the assembled CA are largely retained in the CA-SP1-NC assembly , although some minor variations exist . The P17/T19 pair [10] ( Fig . 3B ) , located at the center of the 18-helix barrel , is important in the hexamer arrangement [19]–[21] , [25] and displays similar average Cα-Cα distances , namely 6 . 3 and 8 . 0 Å in CA and CA-SP1-NC , respectively ( Table S1 ) . In contrast , the A14/E45 pair [10] , located half way into the barrel ( Fig . 3C ) , exhibits an average Cα-Cα distance difference of 3 . 9 Å between the two structures and noticeable variability among pairs within the CA-SP1-NC structure . Specifically , while the six A14/E45 pairs in the CA structure exhibit uniform Cα-Cα distances of 8 . 1±0 . 2 Å , in the CA-SP1-NC structure , four of six pairs display an average Cα-Cα distance of 13 . 0±0 . 7 Å , with the other two pairs being significantly closer ( ∼10 Å apart ) . The most dramatic difference in the CA-SP1-NC assembly compared to that of CA is found at the critical CTD trimer interface that we previously characterized [20] . The P207/T216 Cα-Cα distance at this interface is about 9 Å in the CA structure , while in the CA-SP1-NC structure these residues are separated by nearly 20 Å ( Fig . 3D , Table S1 ) . In fact , no electron density was observed at the pseudo three-fold axis in the CA-SP1-NC map ( Fig . 2C ) , in stark contrast to the CA density map [20] . Therefore , it appears that a major conformational change takes place after proteolytic cleavage at the CA-SP1 and/or SP1-NC junctions , leading to formation of the unique trimer interface in the mature capsid . To test our structural models and verify the predicted intermolecular contacts at interfaces in CA and CA-SP1-NC assemblies , double cysteine mutations were introduced at P17/T19 , A14/E45 , and P207/T216 for chemical crosslinking . The CA and CA-SP1-NC mutants were all competent for assembly ( Fig . S2 ) , and the crosslinking pattern of each mutant agreed very well with our structural model predictions ( Figs . 3E and S3 ) . After crosslinking at 17C/19C , the CA [10] and CA-SP1-NC assemblies displayed a similar ladder of oligomers , suggesting that the associated interface is unperturbed upon proteolytic cleavage . In contrast , crosslinking of 14C/45C resulted in predominant hexamers in the CA assembly [10] but was much less efficient in CA-SP1-NC , with the dimeric product representing the major crosslinked species . This pattern is consistent with our structural model in which two ( of the six ) pairs are close enough for disulfide crosslinking in the CA-SP1-NC assembly ( Table S1 ) . An even more pronounced difference between the two assemblies was observed after crosslinking at the CTD trimer interface ( Fig . 3E lanes 4 & 5 ) ; no significant accumulation of trimer was observed in CA-SP1-NC , consistent with the altered spatial arrangement at the trimer interface . To extend the above in vitro studies to HIV-1 viral particles , we examined the behavior of the identical cysteine mutants in mature virions and compared it with particles in which the specific cleavage sites between CA and NC were abolished ( CA6 ) [39] . To evaluate spontaneous disulfide crosslinking , particles were recovered from transfected cells and analyzed by non-reducing SDS-PAGE and immunoblotting with a CA-specific antiserum . The resulting data are in agreement with the in vitro analysis ( Fig . 3F ) . In particular , the CA protein in mature 14C/45C virions was readily crosslinked into hexamers ( lane 2 ) , while in the corresponding CA6 mutant particles , the protein accumulated predominantly in the dimer state ( lane 3 ) . Further , in mature particles , the 207C/216C spontaneous crosslink resulted in dimer and trimer forms of CA ( lane 4 ) that were not observed in CA6 particles ( lane 5 ) . Taken together , our crosslinking studies support the cryoEM-derived structural model and suggest that the trimer interface in the mature HIV-1 capsid is formed only after protease cleavage of Gag . To mimic the process of HIV-1 maturation in vitro , we performed HIV-1 protease digestion studies of preassembled CA-SP1-NC tubes and identified distinct patterns of digestion , compared to the unassembled protein . HIV-1 protease cleavage of unassembled CA-SP1-NC occurred primarily at the CA-SP1 site , yielding CA and SP1-NC as products , with very little NC ( Fig . 4A ) . However , in assembled CA-SP1-NC , the efficiency of cleavage at this site was greatly reduced , possibly because SP1 is less flexible in the assembled lattice [44] . Instead , cleavage between SP1 and NC was more efficient in assembled complexes , similar to Gag processing in immature particles [48] . At this juncture the question arose whether the mature CA-CTD trimer interface is formed upon protease processing of CA-SP1-NC tubes . Remarkably , the protease-cleaved CA-SP1-NC 207C/216C assemblies were able to form crosslinked CA dimers and trimers similar to the mature CA 207C/216C assemblies ( Fig . 4B ) , indicating that the trimer contacts form upon protease cleavage . In addition , the in vitro proteolysis process appears to involve concerted conformational changes , as we consistently observed a stretch of single-layered tube , apparently digested and of lighter intensity , flanked by the undigested , double-layered CA-SP1-NC tubes in the cryoEM images ( Fig . 4C & D ) . The linear densities ( Fig . 4C , white arrows ) likely correspond to the released NC/DNA fragments , which were only observed in protease-treated samples but not in untreated samples . The fact that we observed non-random and local proteolysis implies that the maturation process through the release of SP1-NC likely involves reorganization of CA interfaces , rather than disassembly and reassembly of CA subunits . This , does not exclude the possibility of partial or complete dissociation of immature lattice during early maturation steps , as suggested by the recent structure of an immature Gag assembly lattice of M-PMV [49] . Considering that there are two fractions of CA in HIV-1 particles , one of which assembles into the mature capsid [30] , [50] , and that fewer than one-half of Gag protein is expected to be bound to the viral genomic RNA [51] , we hypothesize that the fraction of RNA-bound Gag is selected for capsid assembly and remains a part of the lattice . By contrast , in our CA-SP1-NC assembly every protein molecule is bound to nucleic acid , and CA may remain associated with the complex following protease cleavage . Based on our findings , we propose a working model for the mechanism of HIV-1 capsid maturation with regard to the C-terminus of Gag ( Fig . 5 ) : in immature assemblies , initially only the SP1-NC cleavage site is readily accessible to the HIV-1 protease ( Site 1 ) . This results in NC and viral RNA release , as well as disorder in the SP1 segment . This , in turn , permits access of protease to the CA-SP1 site ( Site 2 ) , causing cleavage at that site . Removal of NC/RNA and SP1 not only destabilizes the immature lattice [52] , but also allows the CA-CTD to reorient relative to the NTD , creating new contacts along the trimer interface and forming the mature capsid contacts [20] ( Fig . 5B&C ) . Whether proteolysis between SP1-NC allows formation of the trimer interface or whether release of SP1 , by CA-SP1 cleavage , is also needed requires further investigation . The order of Gag cleavage by protease is known to follow the sequence SP1-NC>MA-CA≥SP2-p6>NC-SP2>CA-SP1 [48] . The question , therefore , arises: does the conformation of CA-CTD in the CA-SP1-NC structure represent a relevant structural intermediate , given that NC is released before MA and p6 ? We suggest the answer is yes , for the following reasons: 1 ) p6 release is most likely irrelevant to the CA-CTD conformation [53] , [54]; and 2 ) high-resolution structures show that the MA and CA-NTD domains are connected by a flexible linker and that MA cleavage does not appear to affect the CA-CTD structure , but results in formation of a beta-hairpin at the N-terminus of CA-NTD [55] , [56] . The importance of the MA-CA cleavage for the immature-to-mature lattice conversion has been implicated previously [36] , [55] , [57] , [58] , but role of the β-hairpin in HIV-1 maturation is not clearly established . The N-terminus of CA-NTD in the CA-SP1-NC construct may fold in a mature-like configuration , as indicated by the similarity of CA-NTD structures and crosslinking pattern of 17C/19C in both CA-SP1-NC and mature CA tubes . This notwithstanding , the CA-CTD in fact shows a major difference between CA-SP1-NC and CA tubes , and clearly is in an “immature-like" configuration , exemplified by the CTD trimer interface and supported by in vivo and in vitro disulfide crosslinking experiments . Therefore , the CA conformation in the CA-SP1-NC construct may represent a maturation intermediate , with only the CA-NTD on the path to maturation . Our data establish that release of SP1-NC is essential for formation of the trimer interface present in the mature viral capsid . This interface controls mature capsid structure: mutations that prevent cleavage of CA-SP1 result in unstable , incompletely formed capsids [39] . Furthermore , mutations in residues at the trimer interface , including Q219A , K203A , and E213A/Q , alter the intrinsic stability of the viral capsid and impair HIV-1 infectivity [7] , [20] with no apparent effect on capsid structure . Thus , the intersubunit trimer interface controls both capsid structure as well as stability . CA-SP1 is also the target of HIV-1 maturation inhibitors , including BVM and PF96 , which act by inhibiting cleavage of this site [59]–[61] . BVM , in particular , has been reported to stabilize the immature capsid lattice , suggesting that cleavage of SP1 results in conversion from “immature-intermediate" to the mature capsid structure [62] . It should be noted that CA-SP1-NC represents an intermediate conformation that is different from the initial immature state before any cleavage . Consistent with this , a Gag mutant defective for CA-SP1 cleavage fails to display a clear immature lattice [62] . While the present work indicates that the trimer contacts critically depend on cleavage of CA-SP1-NC , a detailed understanding of HIV-1 maturation awaits a detailed structural description of this region in the immature HIV-1 capsid lattice; structural knowledge on this interface will be important for developing small molecules that target the interface to inhibit maturation .
Recombinant A92E and double cysteine mutant HIV-1 CA and CA-SP1-NC proteins were expressed and purified as previously described [20] , [27] . CA tubes were assembled at 80 µM concentration in 1 M NaCl and 50 mM Tris-HCl ( pH 8 . 0 ) at 37°C for 1 hour . CA-SP1-NC tubes were assembled at 300 µM concentration with 60 µM TG50 ( IDT , Coralville , IA ) in 250 µM NaCl , 50 mM Tris-HCl ( pH 8 . 0 ) buffer at 4°C for 19 hours . CA and CA-SP1-NC assemblies ( 2 µl ) were applied to the carbon side of a glow discharged perforated Quantifoil grid ( Quantifoil Micro Tools , Jena , Germany ) . 2 . 5 µl dilution buffer ( 0 . 25 M NaCl , 50 mM Tris-HCl pH 8 . 0 ) was added to the back side of the grid , which was then blotted with a filter paper and plunge-frozen in liquid ethane using a home-made manual gravity plunger . Low dose ( 10∼15 e−/Å2 ) projection images were collected on Kodak SO-163 films with an FEI Tecnai TF20 electron microscope at a nominal magnification of 50 , 000 and underfocus values ranging from 1 . 0 to 2 . 5 µm . The best micrographs were digitized using a Nikon super coolscan 9000 ED scanner ( Nikon , Japan ) at a resolution of 4000 dpi . Well-ordered long tubes were Fourier transformed and indexed for helical symmetry . Six CA-SP1-NC tubes belonging to the helical family ( −14 , 11 ) and twelve CA tubes belonging to the helical family ( −12 , 11 ) were included in the final reconstruction of CA and CA-SP1-NC density maps respectively . Image processing and 3D reconstruction were carried out as previously described [41] . The structures of CA and NC were further refined separately using helical refinement programs [63] . During the refinement , helical symmetry and contrast transfer function correction were applied . The resulting density maps were visualized with Chimera [64] . The resolutions of the final 3D reconstructions were estimated from the Fourier shell correlation ( FSC ) curve using the FSC-0 . 5 cut-off criterion . Pseudo-atomic models of CA hexamers were constructed by docking the following NTD and CTD domain models ( PDB 3h47 for CA-NTD and PDB 2kod for CA-CTD ) into the density map separately . To obtain a model of HIV-1 CA hexamer , first , the fitting was performed with the tool “Fit in Map" implemented in Chimera [64] . Then the solution was refined with the program “colores" in Situs package [65] . The relative orientation of CA-CTD with respect to NTD in CA and CA-SP1-NC structures was measured in Chimera by structural comparison . A pseudo-atomic model for CA-SP1was constructed by aligning the overlapping segment ( LEEMMTACQG ) from both CA-CTD structure ( PDB 2kod ) and SP1 structure ( PDB 1u57 ) using the tool “MatchMaker" in Chimera . Crosslinking analysis of in vitro assembled CA and CA-SP1-NC mutants was carried out as previously described [12] . Briefly , 30 µl P207C/T216C , P17C/T19C and A14C/E45C CA and CA-SP1-NC mutants were preassembled in the presence of 50 µM DTT under the conditions described above . The assembled material was then subjected to centrifugation at 20 , 000 g at room temperature in an Eppendorf centrifuge 5417R for 15 minutes . The pellet was oxidized with oxidization mix ( 60 µM CuSO4 , 267 µM 1 , 10-Phenanthroline . Sigma ) and immediately quenched with 20 mM iodoacetamide and 3 . 7 mM Neocuproine ( Sigma ) . The reaction mix was electrophoresis on 4–20% polyacrylamide gradient gels ( Bio-Rad , Hercules , CA ) and stained with Coomassie-Blue . Crosslinking analysis of pelleted HIV-1 particles was performed as previously described [20] . Virus particles were derived by transfection of the full-length HIV-1 proviral construct R9 and mutant derivatives . The CA-SP1-NC cleavage site mutant was derived from the pNL4-3-based construct CA6 [39] by transfer of a BssHII-ApaI fragment into R9 . Particles were pelleted from the supernatants of transfected 293T cells , followed by lysis in non-reducing Laemmli buffer and electrophoresis on 4–20% polyacrylamide gradient Criterion gels ( Bio-Rad ) . Proteins were electrophoretically blotted to nitrocellulose membranes and detected by probing with a CA-specific polyclonal antibody . Bands were revealed with an Odyssey imaging system after probing with IR dye-conjugated anti-rabbit antibody . CA-SP1-NC assembly solution ( 300 uM ) was centrifuged at 20 , 000×g for 20 minutes . The pellet was then resuspended in protease digestion buffer ( 100 mM NaAc , 100 mM NaCl , 1 mM EDTA , 1 mM DTT , pH 5 . 5 ) with a final protein concentration of 80 µM . The soluble CA-SP1-NC protein without assembly was diluted directly to 80 µM with protease digestion buffer . For protease digestion experiment ( Fig . 4A ) , 0 . 09 µM and 0 . 45 µM ( 5× ) HIV-1 protease ( Sigma ) were incubated with CA-SP1-NC tubes for 5 hours and the reaction mixtures were analyzed by cryoEM . HIV-1 protease ( kind gift from Dr . Celia Schiffer at the University of Massachusetts ) at 0 . 45 µM concentration was used for the trimer interface crosslinking experiment with CA-SP1-NC 207C/216C mutant following protease cleavage ( Fig . 4B ) . The digestion reaction mixtures were incubated at 37°C for 5 hours and then subject to SDS-PAGE and cryoEM analysis . The reaction products were separated by NuPAGE Novex 4–12% Bis-Tris gel ( Invitrogen ) and visualized by Coomassie blue staining .
|
HIV-1 virions assemble as immature particles that must undergo proteolytic maturation to become infectious . During the maturation process , the Gag polyprotein is cleaved into matrix ( MA ) , capsid ( CA ) , nucleocapsid ( NC ) , and p6 proteins , and CA assembles to form a mature viral capsid . Here , we determined the structures of CA and CA-SP1-NC assemblies using cryo-electron microscopy , which revealed a marked conformational difference at the CA C-terminal domain in CA-SP1-NC compared to CA . We demonstrated that formation of mature interhexamer contacts critically depends on cleavage of the CA-SP1-NC and a resulting conformational change in CA . Our results provide new insights into the mechanism of HIV-1 maturation and are valuable for developing new inhibitors that target the interhexamer interface to block HIV-1 maturation .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"immunodeficiency",
"viruses",
"virology",
"biology",
"microbiology",
"viral",
"structure"
] |
2012
|
Protease Cleavage Leads to Formation of Mature Trimer Interface in HIV-1 Capsid
|
Caenorhabditis elegans ftn-1 and ftn-2 , which encode the iron-storage protein ferritin , are transcriptionally inhibited during iron deficiency in intestine . Intestinal specific transcription is dependent on binding of ELT-2 to GATA binding sites in an iron-dependent enhancer ( IDE ) located in ftn-1 and ftn-2 promoters , but the mechanism for iron regulation is unknown . Here , we identify HIF-1 ( hypoxia-inducible factor -1 ) as a negative regulator of ferritin transcription . HIF-1 binds to hypoxia-response elements ( HREs ) in the IDE in vitro and in vivo . Depletion of hif-1 by RNA interference blocks transcriptional inhibition of ftn-1 and ftn-2 reporters , and ftn-1 and ftn-2 mRNAs are not regulated in a hif-1 null strain during iron deficiency . An IDE is also present in smf-3 encoding a protein homologous to mammalian divalent metal transporter-1 . Unlike the ftn-1 IDE , the smf-3 IDE is required for HIF-1–dependent transcriptional activation of smf-3 during iron deficiency . We show that hif-1 null worms grown under iron limiting conditions are developmentally delayed and that depletion of FTN-1 and FTN-2 rescues this phenotype . These data show that HIF-1 regulates intestinal iron homeostasis during iron deficiency by activating and inhibiting genes involved in iron uptake and storage .
Iron is essential due to its presence in proteins involved in DNA synthesis , mitochondrial respiration and oxygen transport . Regulation of cellular iron content is crucial: excess cellular iron catalyzes the generation of reactive oxygen species that damage DNA and proteins , while cellular iron deficiency causes cell cycle arrest and cell death . Dysregulation of iron homeostasis caused by iron deficiency or iron excess leads to hematological , neurodegenerative and metabolic diseases in humans . Iron must therefore be maintained within a narrow range to avoid the adverse consequences of iron depletion or excess . Maintaining iron content within this physiological range requires precise mechanisms for regulating its uptake , storage and export ( for reviews , see [1] , [2] ) . In mammals , dietary non-heme Fe3+ is reduced by membrane bound ferric reductases ( e . g . duodenal cytochrome B or DCYTB ) before transport across the enterocyte apical membrane by divalent metal transporter-1 ( DMT1 , also known as NRAMP2 , SLC11a2 and DCT1 ) [3] . Cytosolic iron is either transported across the basolateral membrane into the circulation by ferroportin or sequestered in ferritin in a form unable to catalyze free radical formation [4] , [5] . Iron export by ferroportin is dependent on oxidation to Fe3+ by membrane and soluble multicopper oxidases where it is incorporated into transferrin for delivery to tissues . When body iron stores are high , cytosolic iron is not exported into blood , and is instead sequestered into ferritin [5] , . Iron in ferritin is lost by sloughing of enterocytes into the intestinal lumen . Mammalian intestinal iron transport increases during iron deficiency due to hypoxia-inducible factor-2α ( HIF-2α ) mediated expression of DMT1 and DCYTB [7] , [8] . HIFs ( HIF-1 and HIF-2 ) are key regulators of cellular and systemic oxygen homeostasis ( for reviews , see [9] , [10] ) . HIF transcription factors consist of an oxygen-regulated α subunit ( HIF-1α , HIF-2α and a constitutively expressed β subunit ( HIF-1β , also known as aryl hydrocarbon nuclear translocator or ARNT ) . In the presence of iron and oxygen , HIF-α subunits are hydroxylated by iron- and oxygen-dependent prolyl hydroxylases ( PHDs ) and are targeted for proteasomal degradation by the von Hippel-Lindau ( VHL ) E3 ubiquitin ligase . During hypoxia or iron deficiency , PHDs are inactivated , allowing HIF-1α /HIF-2β to accumulate . HIF-1α/HIF-2α dimerizes with HIF-β and binds to HREs in target genes to increase transcription . HIF regulates genes in diverse pathways including erythropoiesis , iron homeostasis , glucose metabolism , angiogenesis and cell survival ( for reviews , see [9]–[11] ) . Oxygen and iron homeostasis pathways are conserved in Caenorhabditis elegans . The HIF-1 pathway in C . elegans consists of hif-1 , aha-1 , vhl-1 and egl-9 , which are orthologous to genes encoding mammalian HIF-1α , HIF-1β , VHL and PHD [12]–[14] . C . elegans express a single hif gene , which encodes a protein homologous to vertebrate HIF-1α and HIF-2α [12] . C . elegans HIF-1 regulates target genes involved in metabolism , extracellular remodeling [15] , nervous system development [16] , oxygen-dependent behavior [17] and modulation of life span [18] . hif-1 mutant animals display increased embryonic and larval lethality in oxygen concentrations less than 1% , demonstrating the importance of HIF-1 for survival during hypoxia [13] , [19] . C . elegans express genes homologous to ferritin ( ftn-1 and ftn-2 ) , DMT1 ( smf-1 , smf-2 and smf-3 ) and ferroportin ( fpn-1 . 1 , fpn-1 . 2 and fpn-1 . 3 ) . Vertebrate ferritin is a mixture of 24 light- ( L ) and heavy- ( H ) subunits that form a shell that can accommodate up to 4500 iron atoms . The H-subunits exhibit ferroxidase activity and facilitate the oxidation of iron , whereas the L-subunits function with the H-subunits in iron nucleation [20] , [21] . C . elegans FTN-1 and FTN-2 display greater homology to the human H-subunit ( 55% and 60% ) than to the L-subunit ( 46% and 50% ) , and notably both proteins contain ferroxidase active-site residues . ftn-1 and ftn-2 genes are transcriptionally repressed during iron deficiency , which is dependent on an iron-dependent enhancer ( IDE ) located in the ftn-1 and ftn-2 promoters [22]–[24] . The IDE contains two GATA binding sites for the intestinal specific ELT2 transcription factor that regulates basal ftn-1 and ftn-2 transcription , but the mechanism regulating iron-dependent transcriptional repression is unknown . Unlike ftn-1 and ftn-2 , vertebrate ferritin-H and -L subunit mRNAs are translationally repressed by iron-regulatory proteins 1 and 2 ( IRP1 and IRP2 ) during iron deficiency ( for reviews , see [25]–[27] ) . SMF-1 , SMF-2 and SMF-3 display 55–58% amino acid identity with mammalian DMT1 and are involved in Mn2+ uptake and sensing , but the role of these transporters in iron uptake is not well understood [28]–[30] . The function of ferroportin homologs FPN1 . 1 , FPN-1 . 2 and FPN-1 . 3 in iron homeostasis has not been reported . Here , we show that HIF-1 activates smf-3 transcription and inhibits ftn-1 and ftn-2 transcription during iron deficiency . Transcriptional activation of smf-3 and repression of ftn-1 and ftn-2 is dependent on IDEs in their promoters that are similar but not identical . These studies show that HIF-1 is a key regulator of intestinal iron uptake and storage during iron deficiency in C . elegans .
Previous studies showed that ftn-1 and ftn-2 transcription is activated by iron and inhibited by iron chelators [22]–[24] . Transcriptional regulation is mediated by the IDE located in the promoters of ftn-1 and ftn-2 genes ( Figure 1A ) . The IDE contains two WGATAR sequences that are binding sites for the intestinal specific ELT2 GATA transcription factor . Mutation of either of the WGATAR sequences abolished expression of an ftn-1::GFP-his reporter showing that ELT-2 is required for ftn-1 transcription under iron sufficient conditions [24] . The IDE also contains three canonical HREs ( TACGTG ) in the reverse orientation that have been identified in hif-1 target genes [15] , [31] , suggesting a role for HIF-1 in iron-dependent ftn-1 and ftn-2 regulation . To test this model , hif-1 RNAi was used to deplete HIF-1 in worms carrying an ftn-1::GFP-his or an ftn-2::GFP-his reporter . GFP expression was quantified using the COPAS Biosort after growth in NGM or NGM supplemented with the membrane permeable Fe2+ chelator , 2 , 2′-dipyridyl ( NGM-BP ) [32] . These reporters contain 1 . 9 kb of ftn-1 or ftn-2 promoter sequences , including the IDE , fused to the initiator ATG of nuclear-localized GFP-histone [24] . BP reduces expression of ftn-1::GFP-his and ftn-2::GFP-his in worms fed control ( empty vector L4400 ) RNAi by 60% and 80% , respectively , compared to worms grown on NGM ( Figure 1B and 1C ) . By contrast , the BP- induced reduction in GFP expression is blocked by hif-1 RNAi . Furthermore , hif-1 RNAi increases GFP expression in worms grown on NGM , indicating that HIF-1 is expressed under normal growth conditions , and is capable of inhibiting ftn-1 and ftn-2 transcription . We next determined whether endogenous ftn-1 and ftn-2 mRNAs are regulated by HIF-1 . ftn-1 and ftn-2 mRNAs were measured in N2 wildtype animals cultured on NGM or NGM-BP and in strains carrying the loss-of function mutations in hif-1 ( ia04 ) and vhl-1 ( ok161 ) . vhl-1 ( ok161 ) mutant animals lack VHL required for HIF-1 ubiquitination and proteasomal degradation , leading to constitutive expression of HIF-1 [14] , [31] , [33] . Western blots confirm the absence of HIF-1 in hif-1 ( ia04 ) mutant animals and increased HIF-1 levels in vhl-1 ( ok161 ) mutant and in N2 wildtype animals cultured in NGM-BP ( Figure 2A ) . BP reduces ftn-1 and ftn-2 mRNA levels 75% and 20% , respectively , compared to untreated N2 wildtype animals . This is consistent with our previous studies showing that ftn-1 is more sensitive to iron chelators as compared to ftn-2 [22] , [24] . By contrast , ftn-1 and ftn-2 mRNA levels are not reduced by BP in hif-1 ( ia04 ) mutant animals , and notably hif-1 ( ia04 ) animals cultured in NGM express higher amounts of ftn-1 mRNA compared to N2 wildtype animals ( Figure 2B ) . In vhl-1 ( ok161 ) mutant animals , ftn-1 and ftn-2 mRNAs are reduced to levels found in N2 wildtype animals cultured in NGM-BP . Taken together , these data show that ftn-1 and ftn-2 are transcriptionally inhibited by HIF-1 during iron deficiency . Electrophoretic mobility shift assays were used to determine whether HIF-1 binds to the HREs in the IDE . Radiolabeled wildtype IDE or an IDE containing mutations in the three HRE sites ( HRE3m ) was incubated with reticulocyte lysate-synthesized HIF-1 and AHA-1 ( Figure 3A ) . Complex formation is only observed when HIF-1 and AHA-1 are present together in the reaction with wildtype IDE ( Figure 3A ) . Addition of HIF-1 antibody to the reaction led to the formation of a slower migrating HIF-1/AHA-IDE complex ( Figure 3A , lane 5 ) . Formation of HIF-1/AHA-1-IDE complexes is competed away by unlabeled wildtype IDE but not by unlabeled HRE3m IDE , showing that HIF-1 specifically binds to the HREs ( Figure 3B ) . To determine whether the IDE is a direct HIF-1 target in vivo , ChIP was performed on chromatin isolated from vhl-1 ( ok161 ) and hif-1 ( ia04 ) mutant animals . The binding of HIF-1 to the IDE or to the ftn-1 coding region used as a negative control was determined by ChIP using HIF-1 antibody . IDE DNA was enriched 4-fold in vhl-1 ( ok161 ) immunoprecipitates as compared to hif-1 ( ia04 ) immunoprecipitates ( Figure 3C ) . These studies indicate that HIF-1 binds to HREs in vitro and occupies the ftn-1 IDE in vivo . The activation of DMT1 by HIF-2α in iron-deficient mice increases intestinal iron uptake [7] , [8] . C . elegans express three DMT1 homologs , SMF-1 , SMF-2 and SMF-3 . SMF-1 and SMF-3 are expressed in the apical membrane in intestinal cells and are involved in Mn2+ uptake [28] , [30] , whereas SMF-2 is mainly expressed in pharyngeal epithelial cells [28]–[30] . To determine whether HIF-1 regulates smf-1 , smf-2 or smf-3 expression during iron deficiency , their mRNA levels were quantified in N2 wildtype and hif-1 ( ia04 ) mutant animals cultured in NGM or NGM-BP . BP increases smf-3 mRNA levels 2-fold as compared to untreated N2 wildtype animals , but has no effect on smf-1 or smf-2 mRNA levels ( Figure 4A and data not shown ) . In hif-1 ( ia04 ) mutant animals , smf-3 mRNA levels are reduced by 50% as compared to N2 wildtype animals , and are not increased by BP ( Figure 4A ) . Inspection of the 5′ upstream regulatory region of smf-3 reveals a 118-nt element harboring three tandem GATA binding sites flanked by two HREs ( Figure 4B ) . To determine whether this element functions as an iron enhancer , transgenic strains carrying a transcriptional reporter containing 1500 nt of smf-3 promoter sequences fused to GFP-his were generated . GFP expression was quantified in these strains after growth on NGM , NGM-ferric ammonium citrate ( NGM-FAC ) or NGM-BP . FAC reduces GFP expression , whereas BP increases GFP expression as compared to untreated worms ( Figure 4C ) . To show that the BP-induced increase in GFP expression is due to iron chelation , GFP expression was quantified after culture of worms on NGM-BP in the presence of an equimolar amount of FAC or MnCl2 . BP plus FAC , but not BP plus MnCl2 , reduces smf-3 ( -1500 ) ::GFP-his expression ( Figure S1 ) . hif-1 RNAi completely blocks BP-induced increased GFP expression ( Figure 4D ) . Similarly , expression of a smf-3 ( -1500 ) ::GFP-his reporter containing 250 nt of upstream sequences containing the IDE is increased by BP in control RNAi fed worms and is reduced by BP in hif-1 RNAi fed worms ( Figure S2 ) . Taken together , these data indicate that smf-3 is transcriptionally activated by HIF-1 during iron deficiency . The localization of SMF-3 to the apical membrane of intestinal cells [28] , [30] and its regulation by HIF-1 suggest a role for SMF-3 in intestinal iron uptake . If SMF-3 has a role in iron uptake , iron content might be expected to be reduced in smf-3 ( ok1035 ) mutant animals . We found that ftn-1 mRNA levels , which are positively correlated with cellular iron levels ( Figure 2 ) , are reduced in smf-3 ( ok1035 ) mutants as compared to N2 wildtype animals , but not in smf-1 ( ok1748 ) or smf-2 ( gk133 ) mutant animals ( Figure 5A ) . Quantification of metal content by inductively-coupled plasma spectroscopy ( ICP ) shows that total iron content in smf-3 ( ok1035 ) mutant animals is 45% of N2 wildtype animals consistent with reduced ftn-1 mRNA levels in these animals ( Figure 5B ) . The total iron content in smf-1 ( ok1748 ) and smf-2 ( gk133 ) mutant animals is not significantly different as compared to N2 wildtype animals . The total Mn content in smf-3 ( ok1035 ) mutant animals is 60% of N2 wildtype controls ( Figure 5B ) in agreement with SMF-3 as a regulator of Mn uptake [28] , [30] . The Mn content in the smf-1 ( ok1748 ) and smf-2 ( gk133 ) strains tended to be lower as compared to N2 wildtype controls , but did not reach significance . These results are consistent with a role for SMF-3 in intestinal iron transport . hif-1 ( ia04 ) mutant animals have no overt phenotype in normoxia , but display reduced viability in oxygen concentrations less than 1% [13] , [34] . Similarly , we find that hif-1 ( ia04 ) mutant animals develop normally under normoxic conditions , but are developmentally delayed when cultured under iron deficient normoxic conditions ( NGM plus 20 µM BP ) as compared to N2 wildtype animals ( Figure 6A ) . As total iron content is reduced in smf-3 ( ok1035 ) mutant animals and smf-3 expression is reduced in hif-1 ( ia04 ) animals , these data suggest that total iron content might also be reduced in hif-1 ( ia04 ) animals . ICP analyses show that the total iron content in hif-1 ( ia04 ) mutant animals is 60% of N2 wildtype animals ( Figure 6B ) . The total Mn content is also reduced in hif-1 ( ia04 ) mutant animals . We next questioned whether the developmental delay observed in hif-1 ( ia04 ) mutant animals cultured in BP can be rescued by reducing FTN-1 and FTN-2 expression , which would lead to an increase in the cellular labile iron pool . This pool contains chelatable redox-active iron that constitutes less than 5% of total cellular iron [32] , [35] . The modulation of ferritin levels is one mechanism for regulating the labile iron pool in mammalian cells: ferritin overexpression reduces the iron pool , while ferritin depletion increases this pool [36]–[38] . We depleted ftn-1 and ftn-2 by RNAi in N2 wildtype and in hif-1 ( ia04 ) mutant animals cultured on NGM or NGM plus 20 µM BP , and the number of worms reaching L4 stage was measured . ftn-1/ftn-2 RNAi increases the number of hif-1 ( ia04 ) mutant animals reaching L4 stage from 28% in untreated animals to 78% in ftn-1/ftn-2 RNAi-fed animals ( Figure 6C ) . These data indicate that the developmental delay observed in hif-1 ( ia04 ) mutant animals during iron deficiency can be partially rescued by reducing FTN-1 and FTN-2 levels .
Previous studies showed that ftn-1 and ftn-2 transcription in intestine is activated by iron and inhibited by iron deficiency [22]–[24] . Transcriptional regulation is dependent on an IDE containing HIF-1 and GATA binding sites . The GATA factor ELT2 regulates basal intestinal ftn-1 and ftn-2 transcription during iron sufficiency , but how transcription is repressed by iron deficiency was not understood . Here , we identify HIF-1 as a negative regulator of ftn-1 and ftn-2 transcription during iron deficiency . We also show that smf-3 is regulated by HIF-1 during iron deficiency , but unlike ftn-1 and ftn-2 , HIF-1 activates smf-3 transcription . The activation of smf-3 and inhibition of ftn-1 and ftn-2 by HIF-1 provides a mechanism to increase iron uptake and decrease iron storage during iron deficiency . In mice , increased iron uptake by DMT1 during iron deficiency is mediated by HIF-2α [7] , [8] . In contrast to the transcriptional regulation of ftn-1 and ftn-2 in C . elegans , vertebrate ferritin H- and -L subunit mRNAs are translationally repressed during iron deficiency by the binding of IRP1 and IRP2 to an iron-responsive element ( IRE ) in ferritin mRNAs [26] . When cellular iron levels increase , IRP1 is converted into a cytosolic aconitase concomitant with loss of RNA-binding activity and IRP2 is degraded , which leads to increased ferritin translation . Although C . elegans express an IRP1 homolog ( ACO-1 ) , it lacks RNA-binding activity and functions solely as a cytosolic aconitase [22] . The regulation of iron homeostasis by ftn-1and ftn-2 is essential as depletion of FTN-1 and FTN-2 rescues the growth delay observed in hif-1 null worms grown under iron limiting conditions . Recent studies show that constitutive expression of ferritin-H and -L subunits in mice with intestinal specific deletion of IRP1 and IRP2 have reduced survival rates [39] . Depletion of the intestinal ferritin-H gene in mice leads to reduced iron sequestration in intestine and increased body iron stores [40] . Taken together , these studies show that the precise regulation of intestinal ferritin expression is essential for appropriate control of iron absorption . The transcriptional inhibition of ftn-1and ftn-2 genes by HIF-1 during iron deficiency was unexpected . HIF-1 is a potent transcriptional activator of hundreds of HRE target genes [15] , [41] , [42] . HIF has also been reported to function as a repressor , but the mechanism of transcriptional repression is not fully understood [43]–[48] . For some HIF-negatively regulated genes , transcriptional repression may be an indirect effect due to HIF activation of a transcriptional repressor [41] , [42] . HIF-1 has also been shown to upregulate microRNA mir-120 , which represses gene expression [49] . For other genes , direct binding of HIF to HREs in the promoters of negatively-regulated genes has been demonstrated using ChIP analysis [45]–[47] . These studies led to models whereby HIF-1 negatively regulates transcription by the recruitment of corepressors and histone modifying complexes or by competing with transcriptional activators for HRE binding . One question is how HIF-1 mediates transcriptional activation and inhibition through the IDE . The ftn-1 , ftn-2 and smf-3 IDEs differ in number , spacing and orientation of the GATA and HIF-1 binding sites . It is likely that architecture of the IDE dictates physical interactions of ELT-2 , HIF-1 , coactivators and other transcription factors to activate or repress transcription . Further studies are needed to determine how the structure of the IDE affects HIF-1 transcriptional responses . HREs can be flanked by transcription factor binding sites , and it is the cooperation of HIF with these transcription factors that enhance transcription or direct cell specific expression [11] . The GATA binding sites flanking the HREs in ftn-1 , ftn-2 and smf-3 are essential for intestinal expression because mutations of these sites or depletion of ELT-2 reduces intestinal expression of ftn-1 and smf-3 GFP transcriptional reporters [24] ( preliminary data , SJR and EAL ) . Computational studies have shown that the majority of intestinal specific genes contain GATA binding sequences , leading to the notion that ELT2 is a global regulator of intestinal gene expression [50] , [51] . Several studies have shown that other transcription factors cooperate with ELT-2 to modulate its function in response to nutritional or physiological signals [52]–[56] . Based on our findings , a model for HIF-1 regulation of intestinal iron homeostasis is proposed ( Figure 7 ) . During iron sufficiency , ELT-2 binds to GATA binding sites in the IDE to activate intestinal expression of ftn-1 and ftn-2 . Both GATA binding sites are required for ftn-1 expression as deletion of either site abolished expression of an ftn-1 GFP transcriptional reporter [24] . In addition , mutation of all three HREs in the ftn-1 IDE abolished GFP reporter expression , suggesting that a transcriptional activator may bind to the HREs enhancing ELT-2 function [24] . This activator may be a member of the basic helix-loop-helix ( bHLH/PAS ) family or a bHLH transcriptional activator that binds to noncanonical E-box elements [57]–[59] . smf-3 transcription is reduced during iron sufficiency due to decreased HIF-1α levels . Our data also show that a small amount of HIF-1 is expressed during normal growth conditions that can interact with HREs in ftn-1 and smf-3 . During iron deficiency , HIF-1 is stabilized and transported to the nucleus where it dimerizes with AHA-1 . We propose that HIF-1/AHA-1 competes with a transcriptional activator for binding to the ftn-1 and ftn-2 HREs , inhibiting ftn-1 and ftn-2 transcription . HIF-1/AHA-1 binds to the smf-3 HREs , recruits coactivators and cooperates with ELT-2 to activate transcription . SMF-1 , SMF-2 and SMF-3 have been characterized with regard to their role in Mn2+ homeostasis and sensitivity [28] , [30] . SMF-1 and SMF-3 are localized to the apical intestinal epithelium consistent with a role in metal uptake [28] , [30] , whereas SMF-2 is primarily expressed in pharyngeal epithelium [28] , [29] . SMF-1 and SMF-2 are also expressed in dopaminergic neurons where they mediate sensitivity of neurons to Mn and neurotoxins [29] . The high homology of SMF-3 with mammalian DMT1 , its localization in the apical membrane of intestinal cells [28] , [30] , its regulation by iron and a reduction in total iron content in smf-3 ( ok1035 ) mutant animals indicate a role for SMF-3 is intestinal iron transport in C . elegans . The regulation of iron homeostasis by HIF-1 provides a mechanism to ensure that C . elegans maintain sufficient iron stores for growth and survival when iron is limiting .
Strains were cultivated on nematode growth medium ( NGM ) agar plates seeded with Escherichia coli OP50 at 20–22°C . For iron chelation experiments , synchronized larvae were grown for 24 h on NGM plates then transferred to NGM plates supplemented with 100 uM 2 , 2′-dipyridyl ( BP ) for 18 h unless indicated . For iron experiments , larvae were grown for 18 h on NGM plates supplemented with 6 . 6 mg/ml ferric ammonium citrate ( FAC ) . The pH of FAC-supplemented NGM agar was adjusted to pH 7 . 0 . The strains provided by C . elegans Genetics Center are: wild-type Bristol N2 , vhl-1 ( ok161 ) [13] , hif-1 ( ia04 ) [14] , RB1491 smf-1 ( ok1748 ) , VC171 smf-2 ( gk133 ) and RB1074 smf-3 ( ok1035 ) . XA6900 pha-1 ( e2123ts ) III; qaEx1 [ftn-1::Δpes-10::GFP-his , pha-1+] and XA6901 lin-15 ( n765ts ) X; qaEx2 [ftn-2::Δpes-10::GFP-his , lin-15+] were previously described ( Romney et al . , 2008 ) . Strains generated in this study are: XA6904 pha-1 ( e2123ts ) III; qaEx04 [smf-3 ( -1500 ) ::Δpes-10::GFP-his , pha-1+] and XA6905 pha-1 ( e2123ts ) III; qaEx05 [smf-3 ( -250 ) ::Δpes-10::GFP-his , pha-1+] . smf-3 ( -1500 ) ::GFP-his and smf-3 ( -250 ) ::GFP-his were generated by PCR amplification of sequences 1500 nt or 250 nt , respectively , upstream from the initiation ATG of smf-3 ( Y69A2AR . 4 ) using primers containing SalI and NheI restriction sites on the 5′ and 3′ termini , respectively . The PCR products were cloned into TOPO Zeroblunt ( Invitrogen ) followed by digestion and insertion into the SalI and NheI sites of pAP . 10 . Transgenic strains were made according to standard microinjection procedures . Plasmids B696 ( smf-3 ( -1500 ) ::GFP-his ) and B698 ( smf-3 ( -250 ) ::GFP-his ) were each co-injected ( 20 ng/ul ) with selection plasmid pBX-1 ( 100 ng/ul ) . Transgenic worms were recovered after growth at 20–22°C . RNAi clones against ftn-1 ( C54F6 . 14 ) and ftn-2 ( D1037 . 3 ) were from the ORFeome-based RNAi library [60] and hif-1 ( F38A6 . 3 ) was from the Ahringer feeding library [61] . Empty vector ( L4400 ) was used as a control . Worms were grown on RNAi plates ( NGM containing 1 mM IPTG and 50 ug/ml ampicillin ) seeded with bacteria expressing dsRNA corresponding to ftn-1and ftn-2 , hif-1 or L4400 . Mixed-stage populations of N2 wildtype and hif-1 ( ia04 ) animals containing gravid adults were transferred to RNAi plates seeded with bacteria expressing ftn-1 and ftn-2 dsRNA or empty vector control ( L4400 ) for 24 h at 20–22°C . Synchronized larval stage ( L1 ) worms were obtained by treating RNAi fed gravid adults with alkaline hypochlorite and allowing eggs to hatch overnight in sterile S-basal media . L1 larvae were spotted on ftn-1 and ftn-2 or L4400 RNAi plates supplemented with or without 20 µM BP and incubated at 20–22°C for 48 h prior to scoring for larval stage using a Leica MZ9 . 5 stereomicroscope . ftn-1::GFP-his , ftn-2::GFP-his , smf-3 ( -1500 ) ::GFP-his and smf-3 ( -250 ) ::GFP-his reporter lines were synchronized by treating gravid adults with alkaline hypochlorite followed by hatching eggs in S-basal medium ( 0 . 1 M NaCl , 0 . 05 M potassium phosphate , pH 6 . 0 , 5 ug/ml cholesterol ) overnight . Synchronized L1 worms were grown on control or hif-1 RNAi plates for 32 h . Worms were then rinsed from the plates and washed in M9 buffer ( 22 mM KH2PO4 , 42 mM Na2HPO4 , 86 mM NaCl , 1 mM MgSO4 ) and spotted onto fresh 10 cm control or hif-1 RNAi plates supplemented with 100 µM BP and grown for 18 h . Worms were rinsed from plates and washed with MT buffer ( M9 buffer containing 0 . 1% Triton X-100 ) by repeated rounds of centrifugation until free of debris . Worms were analyzed using the COPAS Biosort ( Union Biometrica , Somerville , MA ) as described [24] . Prior to data acquisition , gating parameters were established by visualizing a sorted population by microscopy . The same gating parameters were used for all experimental conditions during GFP fluorescence acquisition and subsequent analysis . Data were analyzed using FCS Express Version 3 . 0 lite ( De Novo Software , Ontario , Canada ) . Procedures for sorting non-RNAi-treated worms was the same as above except that synchronized L1 stage worms were grown on NGM plates seeded with OP50 for 32 h prior to being transferred to fresh NGM plates and NGM plates supplemented with either 100 uM BP , 100 uM FAC , 100 uM BP plus100 uM MnCl2 or 100 uM BP plus 100 uM FAC . Worms were grown for an additional 18 h prior to data acquisition as performed above . Images of GFP expression were captured using an Axio Imager ( Carl Zeiss MicroImaging , Inc , Thornwood NY ) outfitted with the Zeiss filter set 38HE ( BP 470/40HE , dichroic FT 495 HE , BP 525/50 HE ) and an AxioCam HRm camera ( Carl Zeiss MicroImaging , Inc , Thornwood NY ) using AxioVision software . Following acquisition , images were rotated , cropped and sized using Adobe Photoshop . Mixed-stage populations of N2 , hif-1 ( ia04 ) and vhl-1 ( ok161 ) animals were transferred from NGM plates to fresh NGM and 100 uM BP supplemented plates for 16 hr prior to harvesting . Worms were collected , washed with ddH2O and resuspended in 200 µl lysis buffer ( 20 mM HEPES pH 7 . 5 , 25 mM KCl , 0 . 5% NP-40 ) . Worms were sonicated twice using a Misonix 3000 ( 8 pulses , output 3 ) , centrifuged and the protein concentration of the clarified lysate was determined using Coomassie Plus protein assay reagent ( Thermo ) . Samples ( 20 ug ) were fractionated on a NuPAGE 4–12% Bis-Tris gel ( Invitrogen ) and western blotting was carried out using rabbit CeHIF-1 antibody at ( 1∶5 , 000 ) [14] ( a gift from Dr . Peter Ratcliffe , Oxford ) followed by incubation with horseradish peroxidase-conjugated secondary antibodies . Proteins were visualized using Western Lighting Chemiluminescence Reagent Plus ( PerkinElmer Life Sciences ) . Synchronized L1 larvae were grown on NGM plates seeded with OP50 for 48 h prior to harvest . For iron chelation experiments , synchronized worms were transferred to new NGM plates or NGM plates supplemented with 100 uM BP after 32 h and harvested at 48 h . At harvest , worms were washed from plates and cleaned by repeated rounds of centrifugation and resuspension in ddH2O . Pelleted worms were resuspended in TRIZOL ( Invitrogen ) and total RNA was purified according to manufacturer's protocol . cDNA was synthesized using 1 ug of purified total RNA using SuperscriptIII Supermix for qRT-PCR ( Invitrogen ) . Semiquantitative RT-PCR ( sqRT-PCR ) was performed using Recombinant Taq Polymerase ( Invitrogen ) . PCR products were run on ethidium bromide stained 1 . 2% agarose gels . Images were captured on a FluorChem IS-8900 ( Alpha Innotech ) and analyzed using ImageQuaNT ( Molecular Dynamics ) and ImageJ . Primer sequences are shown in Table S1 . ChIP assays were performed as previously described [62] . Mixed-stage vhl-1 ( ok161 ) and hif-1 ( ia04 ) worms were grown on two 150 mm NGM plates and harvested . Worm pellets were homogenized in crosslinking buffer ( 1% formaldehyde in PBS ) and incubated for 20 min at room temperature . The reactions were quenched with glycine for 20 min and snap frozen . The frozen pellets were resuspended in HLB buffer ( 50 mM HEPES-KOH , pH 7 . 5 , 150 mM NaCl , 1 mM EDTA , 0 . 1% sodium deoxycholate , 1% Triton-X100 , 0 . 1% SDS , 1 mM PMSF ) containing protease inhibitor cocktail ( Calbiochem ) , sonicated and the supernatants were precleared using 30 ul salmon sperm DNA/protein A agarose beads . After centrifugation , 10% of each supernatant was kept as input , while the remaining supernatants were incubated with CeHIF antibody ( 4 ul ) overnight at 4°C . DNA-protein antibody complexes were incubated with Protein A agarose ( 30 ul slurry ) for 2 h at 4°C , and the beads were then resuspended in proteinase K buffer ( 20 mg/ml proteinase K ) and incubated at 45°C for 2 h . The samples were further incubated at 65°C overnight to reverse crosslinks . DNA was purified using a QIAquick PCR purification kit ( Qiagen ) according to manufacturer's protocol . Quantitative ( q ) PCR was then performed using Sybr Green mix ( Invitrogen ) run on an ABI 7000 Sequence Detection System and additionally visualized by 2% ethidium bromide stained agarose gels . Primers flanking the ftn-1 IDE and control primers within the ftn-1 coding region are shown in Table S1 . Wildtype IDE and IDE containing mutations in the three HRE binding sites ( HRE3m ) ( CACGTAGC>ACATGCTA ) were excised from TopoZero blunt ( Invitrogen ) with EcoRI and gel purified . Wildtype IDE was radiolabeled with 50 µCi of 32P[α-dATP] using Klenow DNA polymerase . HIF-1 and AHA-1 were synthesized in TNT SP6 Quick Coupled Transcription/Translation system ( Promega ) using hif-1 ( pSP64-HIF-1 ) and aha-1 ( pJ343 ) [12] . pSP64-HIF-1 was generated by excision of hif-1 cDNA from pR33 [13] and insertion into pSP64 ( Promega ) . EMSA reactions ( 20 µl ) were performed in reaction buffer ( 10 mM Tris-HCl , pH 7 . 5 , 4% glycerol , 1 mM MgCl2 , 1 mM DTT ) containing 32P-labeled wildtype or HRE3m probes ( 0 . 4–1 ng ) , poly dI-dC ( 80 ng ) and HIF-1 and/or AHA-1 ( 1–4 µl ) at room temperature for 30 min . CeHIF-1 antibody ( 2 ul ) was added during the last 5 min of the binding reactions . For competition experiments , unlabeled IDE or HRE3m DNA ( 10–100× molar amounts ) was added to the reactions 5 min before addition of 32P-labeled probes . Samples were fractionated on a 5% non-denaturing polyacrylamide gel ( 37 . 5∶1 acrylamide∶bis ) . Synchronized L1 worms were obtained by treating gravid adults from each strain with alkaline hypochlorite followed by hatching eggs in S-basal medium overnight . L1 worms were grown on OP-50 seeded NGM plates . L4 worms were washed extensively with M9 buffer and incubated in M9 buffer for 30 min at room temperature to allow for purging of the gut followed by two rinses with ddH2O . Empty tubes were run in parallel to serve as controls . Samples were pelleted and frozen at −80C° . Samples and controls were brought up in 200 ul of metal free 40% nitric acid ( Optima ) and heated to 95°C for 2 min in a heating block . Solubilized samples were diluted to a final nitric acid concentration of 10% with ddH2O and measured on an Optima 3000 XL ICP-OES ( Perkin Elmer ) . Serial dilutions of commercially available mixed metal standards were used to calibrate the instrument . Results were normalized to the simultaneously acquired signal for sulfur for each sample [63] . The data are presented as a percentage of N2 wildtype animals . At least three independent biological replicates were performed . Data are presented as the means ± SEM . Two-tailed unpaired Student's t test were used for statistical analysis . Data are considered statistically significant at p<0 . 05 .
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Due to its presence in proteins involved in hemoglobin synthesis , DNA synthesis , and mitochondrial respiration , eukaryotic cells require iron for survival . Excess iron can lead to oxidative damage , while iron deficiency reduces cell growth and causes cell death . Dysregulation of iron homeostasis in humans caused by iron deficiency or excess leads to anemia , diabetes , and neurodegenerative disorders . All organisms have thus developed mechanisms to sense , acquire , and store iron . We use Caenorhabditis elegans as a model organism to study mechanisms of iron regulation . Our previous studies show that the iron-storage protein ferritin ( FTN-1 , FTN-2 ) is transcriptionally inhibited in intestine during iron deficiency , but the mechanisms regulating iron regulation are not known . Here , we find that hypoxia-inducible factor 1 ( HIF-1 ) transcriptionally inhibits ftn-1 and ftn-2 during iron deficiency . We also show that HIF-1 activates the iron uptake gene smf-3 . Transcriptional activation and inhibition by HIF-1 is dependent on an iron enhancer in the promoters of these genes . HIF-1 is a known transcriptional activator , but its role in transcriptional inhibition is not well understood . Our data show that HIF-1 regulates iron homeostasis by activating and inhibiting iron uptake and storage genes , and they provide insight into HIF-1 transcriptional inhibition .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology"
] |
2011
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HIF-1 Regulates Iron Homeostasis in Caenorhabditis elegans by Activation and Inhibition of Genes Involved in Iron Uptake and Storage
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Embryonic stem cells ( ESCs ) consist of a population of self-renewing cells displaying extensive phenotypic and functional heterogeneity . Research towards the understanding of the epigenetic mechanisms underlying the heterogeneity among ESCs is still in its initial stage . Key issues , such as how to identify cell-subset specifically methylated loci and how to interpret the biological meanings of methylation variations remain largely unexplored . To fill in the research gap , we implemented a computational pipeline to analyze single-cell methylome and to perform an integrative analysis with single-cell transcriptome data . According to the origins of variation in DNA methylation , we determined the genomic loci associated with allelic-specific methylation or asymmetric DNA methylation , and explored a beta mixture model to infer the genomic loci exhibiting cell-subset specific methylation ( CSM ) . We observed that the putative CSM loci in ESCs are significantly enriched in CpG island ( CGI ) shelves and regions with histone marks for promoter and enhancer , and the genes hosting putative CSM loci show wide-ranging expression among ESCs . More interestingly , the putative CSM loci may be clustered into co-methylated modules enriching the binding motifs of distinct sets of transcription factors . Taken together , our study provided a novel tool to explore single-cell methylome and transcriptome to reveal the underlying transcriptional regulatory networks associated with epigenetic heterogeneity of ESCs .
Embryonic stem cells ( ESCs ) have a wide range of applications in both basic research and pre-clinical drug screening . ESCs are characterized with the capacity to self-renew and to differentiate into multi-lineage cells [1 , 2] . While continuously proliferating , the undifferentiated ESCs are heterogeneous cellular populations corresponding to various differentiation potentials [3 , 4] . Growing evidence indicated that heterogeneous ESCs display substantial variations in gene expression [5] , transcription factor regulation patterns [6 , 7] , and epigenetic modifications including DNA methylation [8] . The heterogeneous expression of transcription factors ( TFs ) is responsible for lineage specific differentiation [9] and may underlie the mechanism that allows ESCs to exit self-renewal cycle and enter into various differentiation paths [7] . The recruitment of TFs to their binding sites may depend on DNA methylation and thus the binding activities of some TFs are methylation-dependent [10] . On the other hand , TF binding may modulate chromatin configuration and contribute to the regulation of DNA methylation [11 , 12] . Consequently , the interplays between TF binding and DNA methylation orchestrate gene expression . Despite these increased understandings , the connections among TF binding , DNA methylation , and gene expression in ESCs remain largely unexplored at the single-cell level . During cell differentiation , dynamic DNA methylation changes occur and have been recognized as needs for lineage-specific expression of developmentally regulated genes [8 , 13] . Regular bisulfite sequencing data sets derived from various tissues are informative to identify tissue specific DNA methylation . However , in tissues with a mixed cell population , each cell subset may have a distinct epigenetic landscape with a specific set of genomic loci differentially methylated . For experiments using bulk tissues , it remains challenging to determine the cell-to-cell methylation variation . With the advances in single-cell sequencing technologies , single-cell reduced representation bisulfite sequencing ( scRRBS ) [14] and single-cell bisulfite sequencing ( scBS-seq ) [15 , 16] have been exploited to profile genome-scale DNA methylation . Substantial heterogeneous DNA methylation patterns were observed in mouse ESCs [15] . Unfortunately , neither scRRBS nor scBS-seq could distinguish the methylation variations within a cell from the ones between cells . Within a cell , methylation variations may result from the differences between two alleles , i . e . allele-specific DNA methylation ( ASM ) , or between the two complementary strands within a DNA molecule , i . e . asymmetric methylation ( AM ) . Mouse ASM loci have been surveyed in a genome-wide study with brain methylomes generated from reciprocal crosses between two distantly related inbred strains [17] . AM can be assessed with the hairpin bisulfite sequencing technique , which generates methylation data for two complementary DNA strands simultaneously [18] . To compare the methylomes derived from single cells , it is necessary to consider ASM and AM , the two types of methylation variations within a cell . In this study , we implemented a pipeline to identify the epigenetic heterogeneity from scBS-seq datasets of mouse ESCs and explored the correlations among DNA methylation and gene expression . Using information from previous map of allele specific methylated loci [17] and the genome annotation of asymmetric methylation for mouse ESCs [18] , we were able to propose a statistical approach called the “beta mixture model” to infer the genomic regions exhibiting cell subset-specific methylation ( CSM ) pattern . Furthermore , we integrated the methylomes and transcriptomes at the single cell level as well as the profiles of TF bindings enriched in the putative CSM loci identified to decipher the epigenetic heterogeneity of mouse ESCs .
To assess DNA methylation variations within and across single cells , we started with the scBS-Seq data generated with the random priming method for nineteen mouse ESCs [15] . We first extracted genomic segments with four neighboring CpG dinucleotides in any given sequence read ( S1A Fig ) . From the nineteen methylomes , 2 , 875 , 509 distinct 4-CpG segments were obtained and the number of 4-CpG segments varied from 98 , 586 to 1 , 054 , 970 in the 19 cells ( S1A Fig & S1 Table ) . The average read depth of those 4-CpG segments in each cell varied from 1 . 1 for segments identified in only one cell to 35 for the segments identified in all 19 cells ( S1B Fig ) . Among the total 2 , 875 , 509 4-CpG segments , only 701 were present in all 19 cells and 917 , 687 were identified in at least five cells ( S1C Fig ) . 93 . 3% of the 701 4-CpG segments were with ≥5Xs read coverage in the 19 cells on average ( S1D Fig ) , and 79% of these 701 segments were distributed in 5’UTR compared to 13 . 3% for all 2 , 875 , 509 segments ( S1E Fig ) . This indicates the biased distribution of sequence reads on genome for single cell methylomes . We next examined methylation levels for allelic specific methylated loci in single cell methylomes . Within a cell , theoretically , the methylation levels of ASM loci should be around 50% . Due to loss of DNA content during library preparation , PCR bias , and low sequence depth , the two alleles from a single cell may not present equally in sequencing data . To assess the representation of methylation patterns for two alleles , we examined the methylation profiles of ASM loci reported in a previous study [17] . These ASM loci were identified with brain tissues derived from reciprocal crosses between two distantly related mouse strains . We focused on the parent-of-origin dependent ( imprinted ) ASM at 1 , 952 CG dinucleotides in 55 discrete genomic loci , including 21 germline ASM loci which acquire allelic methylation status during gametogenesis and maintain throughout development , and 34 somatic ASM loci of which the allelic methylation states arise late in development in a tissue-specific manner [17] . The methylation levels for 47 of these ASM loci could be determined in at least one single-cell methylome ( S2 Table and Fig 1 ) . We calculated the methylation levels of these 47 ASM loci for each methylome and obtained 546 data points . Surprisingly , only 32 out of the total 546 data points are with methylation level between 0 . 4 and 0 . 6 ( Fig 1A ) . In addition , the methylation levels of 47 ASM loci , including germline imprinted ones , are highly variable among single cells ( Figs 1B & S2A ) . Thus , the majority of ASM loci may be reported as cell subset-specific methylated: hyper-methylated in some cells while hypo-methylated in others . We next examined the methylation profiles of asymmetric methylated loci in single-cell methylomes . In a DNA molecule , the CpG dyads on the two complementary DNA strands usually show highly symmetric methylation pattern [18–20] . However , strand-to-strand methylation variation has been observed in mouse ESCs . Using the hairpin bisulfite sequencing strategy , our recent study showed that approximately 12% of CpG dyads are asymmetrically methylated in undifferentiated ESCs [18] . In particular , 65 . 2% of half-methylated ( methylation level at 50% ) cytosines are due to asymmetric methylation . Apparently , CpG sites with intermediate methylation level may pose a challenge to the identification of CSM in single-cell methylomes , in particular for those with low sequence depth . To explore CpG sites with asymmetrical methylation ( AM ) , we integrated the hairpin bisulfite sequencing data and single-cell methylomes generated for mouse E14TG2a ESCs . From the hairpin methylome , we identified a total of 12 , 042 4-CpG segments as AM loci which have at least a pair of hairpin sequence reads showing one strand as completely methylated and the other strand as completely unmethylated . We further analyzed the single cell methylomes and identified 7 , 209 4-CpG segments as AM loci with both completely methylated and completely unmethylated reads within a single cell . We obtained 19 , 162 AM loci in total by merging the results from the hairpin bisulfite sequencing data and single cell methylomes . Similar to the observation made for ASM loci , the methylation levels of these 19 , 162 AM loci vary substantially across cells ( S2B and S2C Fig ) . Since the two types of within-cell methylation variations , i . e . ASM and AM , may undermine the comparison of single-cell methylomes , we implemented a computational pipeline to assess the methylation heterogeneity among ESCs and infer putative CSM loci ( Fig 2 ) . The pipeline starts with the extraction of 4-CpG segments , excluding the known ASM and AM ones . We then defined CSM seeds as the 4-CpG segments that show complete methylated pattern in at least one methylome and complete unmethylated pattern in other methylomes . Overlapped CSM seeds were merged together to generate candidate CSM regions . Applying such a procedure to single cell methylomes , we obtained 7 , 161 candidate CSM regions covered by at least 5 cells and with at least 10 methylation counts within each candidate region in each cell . Suppose that there are two methylation states: hyper-methylated and hypo-methylated in a given candidate region . However , the composition of each state is unknown . To decompose states , a beta mixture model is developed . Here we assumed that the methylation probabilities of hyper-methylated state and hypo-methylated state , denoted by θ ( 1 ) and θ ( 2 ) , follow two distinct beta distributions . For each candidate region , the two probabilities were estimated by using the EM algorithms . One critical parameter is the methylation difference between two states for each candidate region , denoted by θ ( 1 ) —θ ( 2 ) . We conducted simulations to evaluate how the performance of our model is related to θ ( 1 ) —θ ( 2 ) ( S3A & S3B Fig ) . As shown in S3A Fig , the fraction of accurate prediction increased with the increasing of θ ( 1 ) —θ ( 2 ) and became stable until θ ( 1 ) —θ ( 2 ) reaching 0 . 3 . Thus , for the beta mixture model , we determined the threshold of methylation difference between two methylation states as 0 . 3 . We also checked the relationship between the estimated θ ( 1 ) —θ ( 2 ) and real θ ( 1 ) —θ ( 2 ) at different setting of λ which represented the proportion of the cells with hyper-methylated state in the given region , and found a high Pearson’s correlations , showing that the estimation of θ ( 1 ) —θ ( 2 ) was accurate enough ( S3B Fig ) . We further exploited the receiver operating characteristic ( ROC ) curve and the positive predictive value ( PPV ) to evaluate the model performance ( S3C & S3D Fig ) . In the beta mixture model , we used Deltamin to represent the observed minimum methylation difference of the two methylation states . From the ROC curve , we found that the beta mixture model had high sensitivity and high specificity for different settings of Deltamin as well as high PPV for different settings of θ ( 1 ) —θ ( 2 ) . The false discovery rate ( FDR ) and false positive rate ( FPR ) decreased dramatically with the increase of θ ( 1 ) —θ ( 2 ) until θ ( 1 ) —θ ( 2 ) reached 0 . 3 ( S3E Fig ) . In addition , to ensure the data quality , we required that a putative CSM loci should have data generated from at least 8 cells . With those parameters , 2 , 102 out of the total 7 , 142 candidate regions were inferred as putative CSM loci among ESCs . We next assessed the methylation profiles , genomic characteristics , and DNA-related features of the 2 , 102 putative CSM loci ( Figs 3 & S4 , S3 Tables ) . We also produced our control region set including 46 , 642 regions by merging the 2 , 813 , 756 ASM-freed segments . Putative CSM loci are intermediated methylated with methylation levels centered around 50% across single cells ( Fig 3A ) , while control regions tend to form two clusters , either hypermethylated or hypomethylated ( S4A Fig ) . Additionally , the methylation differences between the two methylation states , i . e . θ ( 1 ) —θ ( 2 ) , are centered at 0 . 54 for putative CSM loci and 0 . 25 for control regions ( S4B Fig ) . We calculated the methylation variance of putative CSM loci across cells and found that putative CSM loci exhibited significantly smaller methylation variance with average at 5 . 3e-04 compared to 5 . 7e-04 in control regions ( Wilcoxon test , p value = 5 . 94e-09 ) ( S4B Fig ) . By contrast , putative CSM loci exhibited higher methylation variance surrounding transcription start sites ( TSSs ) compared to control regions , especially in the downstream regions of TSSs ( Fig 3B ) . In addition , we found that putative CSM loci were enriched in CGI shelves with a 1 . 5-fold increase compared with control regions , and 1 . 2-fold and 1 . 1-fold increase in exons and CGI shores , respectively ( Fig 3C ) . We further examined the correlation between DNA methylation and histone modifications . As shown in the Fig 3C & 3D , putative CSM loci show enrichment in regions with H3K4me1 , H3K4me3 , H3K9ac , and H3K36me3 marks , except H3K27ac . Since H3K4me1[21 , 22] , H3K4me3 [22 , 23] , and H3K9ac [24] are the histone marks for enhancers or promoters , while H3K36me3 marks indicate active transcribed genes and induce the DNA methylation of the gene bodies [25] , this result suggests the regulation potential of the putative CSM loci on gene expression . Meanwhile , putative CSM loci are with higher GC content and CpG density ( S4C & S4D Fig ) , which are known to be related to open chromatin and active transcription [26 , 27] . In addition , compared to control regions , the sequences of putative CSM loci are more conservative among the placental mammals ( S4E Fig ) . To explore the association among the 2 , 102 putative CSM loci identified in mouse ESCs , we determined the methylation profiles of these loci in 17 mouse tissues spanning all three germ layers and extraembryonic placenta derived from trophectoderm [28] and performed co-methylation analysis to cluster these CSM loci into modules . For the 2 , 094 ( 99 . 7% of 2 , 102 ) putative CSM loci with data available in all 17 tissues , we calculated their pairwise Pearson's correlations in methylation level , and identified five major co-methylated modules ( Fig 4A ) which show distinct methylation profiles across different tissues ( Fig 4B ) . An early differentiation event during embryonic development is the segregation of trophectoderm and inner cell mass [29] . Intriguingly , compared to those in other tissues , the methylation levels in placenta are lower for the putative CSM loci in module I but higher for those in module IV . Putative CSM loci in module II are hypomethylated in cerebellum ( ectoderm-derived tissue ) and putative CSM loci in module III are hypomethylated in bone marrow , spleen and thymus ( blood-producing , mesoderm-derived tissues ) , while putative CSM loci in module V show higher methylation level in ectoderm-derived tissues . To characterize the function of genes associated with co-methylated CSM modules , we determined genes with putative CSM loci located within [-10k , 2k] from TSS and then performed GO analysis using DAVID annotation tool [30 , 31] to check the enrichment of GO terms for biological process ( Fig 4C ) . For the largest module I , GO terms including protein transport and autophagy were identified to be significant . Autophagy is recognized to promote cell survival and involved in the development of human placenta [32 , 33] . Genes in protein transport pathways are important for placenta function , since placenta plays an important role in the feto-maternal exchange processes via classic membranous transport mechanisms , i . e . the transportation capacity of the placenta . For module II and module III , the terms of neuron apoptotic process and positive regulation of protein kinase B signaling were identified , and were found to be related to the cell fate regulation during the development of cerebellum [34] and of hematopoietic lineages [35] , respectively . DNA methylation affects the bindings of transcription factors ( TFs ) to their targets [10] , while TFs binding may prevent or facilitate the methylation on their binding sites [11 , 12] . Hence , specific TFs could cooperate with DNA methylation to regulate gene expression . To examine whether co-methylated loci are under the control of the same set of TFs , we performed motif enrichment analysis with HOMER software [36] ( Fig 4D and S4 Table ) . Intriguingly , each co-methylated module is associated with a distinct set of transcription factors , whose functions have been linked to the tissues associated with modules . More specifically , transcription factor Dhcr24 was found to be the regulator for the putative CSM loci in both modules I and IV . The Dhcr24 gene is involved in cellular lipid metabolism and cholesterol biosynthesis [37] , and cholesterol is of vital importance for fetal development , thus the expression of Dhcr24 in placenta would provide a means to satisfy the high requirement for cholesterol in fetus [38] . Downregulation of this gene was detected in intrauterine growth restriction placentas compared to normal placentas [39] , which indicated that the decreased expression of this gene in the placenta influenced the cholesterol supply to the fetus , and contributed to the poor fetal growth . The enriched Hic1 [40] in module II , and Ets1 [41 , 42] in module III were essential for normal development of cerebellar and for the establishment of differentiation potentialities of hematopoietic tissues in mesoderm layers , respectively . To further investigate the role of DNA methylation in transcription regulation , we re-analyzed a single-cell RNAseq dataset derived from IB10 cell line [43] , a sub-clone of E14 ESCs we analyzed for the single cell methylomes in this study . Following the procedure described in the previous study [43] , we identified 2 , 266 highly variable genes ( HVGs ) , which were genes with over-dispersed abundance compared to those transcripts with non-fluctuating expression in all cells and showed much higher υ statistics than other genes ( S5A Fig ) [43] . To explore how the CSM contributes to the variation in gene expression , we examined the HVGs in genes overlapped with putative CSM loci ( S5B Fig ) . We determined genes with putative CSM loci localized in the distal upstream region ( [-10k , 2k] of TSS ) , proximal upstream region ( [-2k , 0 . 5k] of TSS ) , and gene body ( [-10k of TSS , TES] ) . A total of 927 genes with their distal upstream regions overlapped with putative CSM loci showed significant enrichment in the list of HVGs , with 134 of these 927 genes highly variably expressed among ES cells ( Chi square test , p value = 2 . 5e-02 ) . In contrast , no significant overlap was observed among HVGs and genes with putative CSM loci in their proximal upstream regions or gene bodies ( Chi square test , p value = 0 . 70 and 0 . 11 , respectively ) . This result indicates that the methylation heterogeneity in distal upstream region might underlie the variable gene expression in ESCs rather than proximal upstream region or gene body . We then examined the methylation differences of HVGs between two methylation states , i . e . θ ( 1 ) —θ ( 2 ) . Interestingly , for those genes with putative CSM loci in their gene bodies , we found that HVGs showed significantly higher θ ( 1 ) —θ ( 2 ) than non-HVGs ( Wilcoxon test , p value = 4 . 1e-02 ) , while for genes with non-CSM loci in their gene bodies , the θ ( 1 ) —θ ( 2 ) of HVGs were significantly lower than those of non-HVG ( Wilcoxon test , p value = 4 . 1e-06 ) ( S5C Fig ) . This indicates that other factors such as histone modifications may be involved in regulating genes lack of CSM , of which the expression variability showed independence to the methylation difference . Even for genes with putative CSM loci , the CSM are only partially responsible for the variable expression . This result is similar to a recent study which demonstrated that for genes with variably methylated promoters among single cells , about 26 . 1% of them are significantly correlated with gene transcription , while for genes with hypomethylated promoters , 51% of them exhibit dynamic expression across cells [44] . Altogether , these results suggest a complex regulating role of DNA methylation on gene expression , either in promoter or gene body .
Embryonic stem cells are characterized by high cellular heterogeneity and consist of various cell subsets that express different levels of specific markers ( such as Stella , Nanog and GATA-6 ) and differ in bias toward self-renewal or differentiation [4] . Single cell “omics” studies provide data in an unprecedented resolution to achieve understandings of the cellular complexity in multicellular organisms . Currently , a few single cell methylome datasets are available [14–16] but how to analyze and interpret methylation variation among single cells is far from clear . For cells in multicellular organisms , the genomic DNA contents are nearly identical , if not the same . However , at the epigenome level , dynamic DNA methylation is key to diverse cellular functions . In this study , we proposed a computational pipeline to infer CSM with scBS-seq data derived from mouse ES cells . To our knowledge , this study is the first attempt to explore single cell methylomes for CSM in heterogeneous embryonic stem cells . The pipeline implemented in this study may also be applied to other emerging single-cell methylation data sets . Single-cell methylomes are frequently with low read depth , which greatly limits the distinction of CSM from ASM and AM . Such a limitation has also been pointed out in a recent study . Hu et al . discovered a high rate of allele drop-out while applying single-cell techniques , resulting that the vast majority of assayed CpGs represent only one of two possible alleles [44] . To overcome such a limitation , the pipeline implemented in this study took the within-a-cell interference into account , and annotated ASM from previous knowledge and AM based on hairpin bisulfite sequencing data from our previous study and scBS-seq datasets . Current single-cell epigenetic studies primarily focused on measuring methylation heterogeneity by estimating the cell-to-cell methylation variance [44–46] . However , methylation variance may not reflect the heterogeneity attributed to different methylation states . For example , the higher methylation variance could be caused by methylation levels following continuous uniform distribution than bi-modal distributed ones , whereas the latter is more likely to be seen in a population of mixed cell subsets . In contrast to aforementioned studies [44–46] , we model the methylation data on putative CSM loci with a beta mixture model . Based on this model , we determined the difference of the estimated methylation probabilities between the two methylation states and provided statistical justification to infer putative CSM loci . As a side note , it was found that , when divided into hyper-and hypo-methylated clusters , such putative CSM loci exhibited higher methylation difference ( θ ( 1 ) —θ ( 2 ) ) but smaller methylation variance ( S4C Fig ) . Our analysis pipeline for CSM inference accepts single cell methylomes and excludes genomic loci associated with allele-specific and asymmetric methylation . It has several limitations on the requirements of prior knowledge and data inputs . 1 ) We assume a majority of allele-specific methylated loci have been identified in previous studies [17] . However , it remains challenging to determine the genome loci associated with stochastic allele-specific methylation and the parental origins of the conservative genomic loci lacking of SNPs across mouse strains . Thus , the existing list of ASM loci may not be comprehensive . 2 ) Our recent studies [18 , 47] on asymmetric DNA methylation suggest that fast replicating cells may have a large number of asymmetrically methylated CpG dyads while terminally differentiated cells have much fewer . Although asymmetric methylated CpG sites tend to be widely distributed [18] , some clusters of asymmetric methylated CpG sites in stem cells may end up as a source of cell specific methylated loci if the methylation statuses of two DNA strands segregating into two daughter cells are stable during cell duplication . 3 ) Apparently , the determination of putative CSM loci is highly dependent on the data quality of single cell methylomes , in particular the number of single cell sequenced , the genome coverage and read depth for each methylome . Currently , only very limited number of methylomes were determined at the single cell level and with low genome coverage . This greatly limits the downstream methylome comparisons and co-methylation analysis of CSM clusters . Despite all the aforementioned limitations , we were able to infer a number of putative CSM loci in mouse ESCs and made several interesting observations . The genome distribution analysis for putative CSM loci show that these loci are enriched in CGI shelves and genomic regions with histone marks for enhancer and promoter . We explored the methylation profiles of putative CSM loci in adult mouse tissues to perform co-methylation analysis . The co-methylation analysis provides valuable information for understanding on the biological readouts of epigenetic heterogeneity . Some putative CSM loci in co-methylated modules show placenta specific methylation profile . This suggests that , within a population of ESCs , some cells may be pre-marked at the epigenetic level and with the potential to differentiate into placenta tissue . In addition , TFs playing important roles in tissue specification were enriched in the co-methylation modules . More interestingly , the integration with single cell RNAseq data indicates that the putative CSM loci are associated with highly variable genes . The three-step procedure implemented in this study will provide lists of co-methylation modules , co-regulation of TFs , and underlying highly variable expression . Such a process paves the way to integrate “omics” data sets from multiple layers and to explore epigenetic regulation at a module-based level .
Methylomes of mouse ES cells ( E14TG2a ) were downloaded from Gene Expression Omnibus ( GEO ) database ( GSE56879 ) , including 19 scBS-seq datasets of cells cultured in serum/LIF [15] and one hairpin BS-seq dataset ( GSE48229 ) [18] . Our scBS-seq data analysis followed the processing steps provided in Smallwood et al . 2014 [15]: 1 ) perform adaptor trimming with Trim Galore ! ( v0 . 3 . 7 ) ; 2 ) map reads to human genome ( GRCh38/hg19 ) in pair-end mode to remove contaminated reads and then map the unmapped reads to mouse genome ( GRCm38/mm10 ) in single-end mode using Bismark [48] ( v0 . 7 . 7 ) ; 3 ) perform duplication removal using picard-tools ( v1 . 118 ) ; 4 ) perform methylation calling with Bismark [48] ( v0 . 7 . 7 ) . For hairpin BS-seq dataset , HBS analyzer [49] was employed . For both scBS-seq data and hairpin BS-seq data , all segments with four neighboring CpG sites in any sequence read were extracted from autosomes . In this study , the methylation level was determined as the ratio of the methylated cytosine counts to the total cytosine counts . The genomic coordinates of mouse ASM loci and the annotation of either ‘germline’ or ‘somatic’ ASM were retrieved from a previous study [17] , and were lifted to mm10 using liftOver . The AM loci were determined from hairpin BS-seq data [18] and scBS-seq data [15] . With hairpin BS-seq data , the AM loci were defined as 4-CpG segments with completely methylated pattern on one strand and completely unmethylated pattern on the other strand in a pair of hairpin sequence reads . For the scBS-seq dataset , the 4-CpG segments with at least one completely methylated read and one completely unmethylated read in one cell were defined as AM loci . Three steps were taken to infer candidate CSM regions . 1 ) The determination of seeds for CSM: The 4-CpG segments overlapped with known ASM loci were filtered from the total segments . Bipolar methylated segments were selected from the remaining segments , which were defined as the ones with completely methylation in one single-cell methylome and completely unmethylation in any other single-cell methylome . After filtering out AM loci , the remaining bipolar methylated segments were defined as CSM seeds . 2 ) The extension of CSM seeds: Each CSM seed as well as other ASM-filtered segments were extended to include upstream and downstream 100 bp regions . Extended CSM seeds overlapped with other extended segments or seeds were merged into one , which ensured that each merged region included at least one CSM seed . 3 ) The extraction of candidate CSM regions: The merged regions covered by at least 5 single-cell methylomes and with at least 10 cytosine counts in each single-cell methylome were defined as candidate CSM regions . To produce a control set for putative CSM loci , all ASM-filtered segments were extended to include upstream and downstream 100 bp regions , merged with overlapped ones , and filtered with the same cutoffs of number of cells and cytosine counts as the candidate CSM regions . Consider N single cells and R regions . For a given a region r from cell i ( r = 1 , 2 , … , R; i = 1 , 2 , … , N ) , there are cri CpG sites . For each CpG site , we assume that the methylated count follows binomial distribution with a common methylation probability . We further assume that there are a total of njri read counts for the jth CpG site ( j = 1 , 2 , … , cri ) . Then , on this CpG site , we have the methylated count mjri∼Binomial ( njri , θri ) . ( 1 ) Denote Mri′= ( m1ri , m2ri , … , mcriri ) T and , Nri′= ( n1ri , n2ri , … , ncriri ) T the joint probability function can be written as f ( Mri′|θri;Nri′ ) =∏j=1criCnjrimjriθrimjri ( 1−θri ) njri−mjri . ( 2 ) Since the true methylation probability θri is unknown , we treat θri as a random variable which follows beta distribution , θri∼Beta ( αri , βri ) . ( 3 ) By conjugacy , we have the posterior distribution of θri that is also beta distribution Pr ( θri|αri , βri;Mri′ , Nri′ ) =Beta ( ∑j=1crimjri+αri , ∑j=1crinjri−∑j=1crimjri+βri ) . ( 4 ) The parameters of the prior distribution αri and βri are unknown . In order to estimate them , first , the beta distribution may be reparameterized by its mean μri and precision Mri , that is μri=αriαri+βri , Mri=αri+βri . According to the previous assumptions of distributions , the marginal distribution of the methylated counts mjri is then given by beta-binomial distribution . Second , the parameters μri and Mri of the beta-binomial distribution are estimated using an empirical Bayesian method [50] . Consequently , we obtain an estimation based on the method of moments μ^ri=∑jnjriejri∑jnjri , ( 5 ) where μ^ri is the weighted mean of observed methylation level ejri , and ejri=mjrinjri , j=1 , 2 , … , cri . An estimation of precision Mri may be obtained as M^ri=μ^ri ( 1−μ^ri ) −sri2sri2−μ^ri ( 1−μ^ri ) N∑i=1N1∑j=1crinjri , ( 6 ) where sri2 is the total weighted sampled variance sri2=∑jnjri ( ejri−μ^ri ) 2∑jnjri . Based on ( 5 ) and ( 6 ) , αri and βri are estimated as follows α^ri=μ^riM^ri , ( 7 ) β^ri= ( 1−μ^ri ) M^ri . ( 8 ) In case that M^ri is negative [50] , we assign α^ri=β^ri=1 . In addition , for missing methylation data on some CpG sites for some cells , we set the two parameters of their methylated counts and total counts to zero . To understand the methylation heterogeneity driven by CSM , we evaluate the methylation variance of cell to cell . To this end , we employ a random effect model to describe the variances across single cells . According to the posterior estimations of methylation probabilities above , we have the expectations and variances of the methylation probabilities of θri: E ( θri ) =∑jmjri+αri∑jnjri+αri+βri , ( 9 ) var ( θri ) = ( ∑jmjri+αri ) ( ∑jnjri−∑jmjri+βri ) ( ∑jnjri+αri+βri ) 2 ( ∑jnjri+αri+βri+1 ) . ( 10 ) Also , we assume that μr is the abstract methylation probability across single cells . Furthermore , Δr2 is defined as the variance of population; δri is defined as the deviation from the average methylation probability across single cells; and εri is a random effect . The observed methylation probabilities θri with the corresponding variance Vri for region r from cell i are considered to be a function of the abstract methylation probability μr , δri and εri: θri=μrθ+δri+εri . ( 11 ) To resolve the random effect model , a non-iteration algorithm was employed [51] . As a result , μr is estimated as a weighted mean of the observed methylation probabilities θri: μ^r=∑i=1Nwri*θri∑i=1Nwri* , ( 12 ) where wri*= ( Vri+Δ^ri2 ) −1 . ( 13 ) Also , the estimator of the methylation variance V^r is V^r=1∑i=1Nwri* , ( 14 ) where the 95% confidence interval of V^r is obtained from 1000 Bootstrap samplings . Suppose that there are K methylation states in a given region . As the composition of methylation state is unknown , a mixture model is employed to decompose the mixture methylation states . To this end , we focus on some candidate regions with methylation variation across cells . For a given region r , we assume that the proportion of the kth subgroup over the cell population is λrk , where ∑k=1Kλrk=1 . As mentioned above , we assume that the number of methylated count for each CpG site in a given region follows binomial distribution and the methylation probability follows beta distribution . Then , we obtain the posterior distribution of methylation probability θri in region r from cell i: Pr ( θri|Mri′ , Nri′ ) =Beta ( ∑j=1crimjri+αri , ∑j=1crinjri−∑j=1crimjri+βri ) . Since cells are grouped in the region , the methylation probabilities of the cells from a subgroup are assumed to be the same . Let θr ( k ) denote the methylation probability of group k . Then , the probability for the observed methylation in cell i is: Pr ( i ) =∑k=1KPr ( k ) *Pr ( i|k ) =∑k=1KλrkPr ( i|θr ( k ) ) . According to the posterior distribution of methylation probability , the conditional probability of observing cell i from subgroup k is obtained: Pr ( i|θr ( k ) ) =Γ ( ∑j=1crimjri+α^ri ) Γ ( ∑j=1crinjri−∑j=1crimjri+β^ri ) Γ ( ∑j=1crinjri+α^ri+β^ri ) ( θr ( k ) ) ∑j=1crimjri+α^ri−1* ( 1−θr ( k ) ) ∑j=1crinjri−∑j=1crimjri+β^ri−1 , where Γ ( . ) is the Gamma function . Therefore , the joint likelihood function can be written as: L ( Θ ) =∏i=1NPr ( i ) , ( 15 ) where Θ= ( λr1 , λr2 , … , λrK;θr ( 1 ) , θr ( 2 ) , … , θr ( K ) ) T . The parameters Θ may be estimated by maximizing the log likelihood function: Θ^=argmaxΘlogL ( Θ ) =argmaxΘl ( Θ ) =argmaxΘ∑i=1NlogPr ( i ) . ( 16 ) The optimized problem ( 16 ) may be resolved by the Expectation-Maximization ( EM ) algorithm by introducing a latent random variable Yi which denotes the membership of cell i , that is Yi = k if cell i is from subgroup k . Let Pr ( Yi = k ) denote the probability of Yi = k . Finally , we iteratively estimate all parameters based on the EM algorithm: E-step: Pr ( Yi=k|i , Θ ) =λrkPr ( i|θr ( k ) ) ∑k=1KλrkPr ( i|θr ( k ) ) , ( 17 ) M-step: {λrk=∑i=1NPr ( Yi=k|i , Θ ) Nθr ( k ) =∑i=1NPr ( Yi=k|i , Θ ) ( ∑j=1crimjri+α^ri−1 ) ∑i=1NPr ( Yi=k|i , Θ ) ( ∑j=1crinjri+α^ri+β^ri−2 ) , ( 18 ) here k = 1 , 2 , …K , where Pr ( Yi = k|i , Θ ) is the posterior estimation of the probability of Yi = k given the observed cell i and parameters Θ . In this study , we only focused on the bimodal methylation states by assuming a two-state model , that is K = 2 . For each candidate region in a given cell , we considered two models: one is the beta mixture model; the other is a null model where only one cluster exists . We used likelihood ratio test to evaluate the goodness-of-fit of the two models to the data . The p-values are then adjusted by the Benjamini–Hochberg procedure [52] . In addition , we introduced a latent membership probability estimated by the beta mixture model to determine which cluster each single cell originates from in a given region , that is , the single cell i is from the first state if Pr ( Yi = 1 ) ≥ Pr ( Yi = 2 ) , and from the second state otherwise . Besides , larger θ ( 1 ) —θ ( 2 ) will lead to the more accurate estimation of the two states . We determined the cutoff of θ ( 1 ) —θ ( 2 ) to be 0 . 3 based on simulation data . In the study , the regions with significant adjusted p-values and with θ ( 1 ) —θ ( 2 ) ( that is tuning parameter ) greater than a given value were considered as putative CSM loci . Lastly , false discovery rate ( FDR ) , true positive rate ( TPR ) , false positive rate ( FPR ) and positive predictive value ( PPV ) are calculated for these putative CSM loci . A full description of the beta mixture model is provided in the S1 Text . The code and test data of the beta mixture model are available in the S1 Appendix and freely downloadable from https://github . com/Evan-Evans/Beta-Mixture-Model . In the simulation study , we consider two cell subpopulations with distinct methylation probabilities . To evaluate the robustness of parameters estimation in the statistical model , we simulate data by setting the number of reads for each CpG site , the number of cells , and the rate of missing data . More specifically , the parameter λ is randomly sampled from unif[0 , 1]; the read counts for each CpG site are sampled from a Poisson distribution with a prespecified mean that is considered as the read depth; and the methylated counts for each CpG site are sampled from binomial distribution with fixed methylation probabilities ( i . e . θr ( k ) , k=1 , 2 ) sampled from unif[0 , 1] . We consider the estimated parameter to be accurate if the difference between the estimated value and the real value we set is less than 1e-2 . All simulations are based on 10 , 000 independent samplings . Genomic features were obtained from the UCSC Genome database [53] , including annotations for gene structure ( Refseq genes ) , CpG islands ( cpgIslandExt ) , repetitive elements ( RepeatMasker ) , and placental mammal conservation scores ( phastCons60wayPlacental ) in mm10 . Promoters were defined as 1kb regions in the upstream of transcription starting sites ( TSSs ) . CGI shores ( 2kb regions directly upstream and downstream of CpG islands ) and CGI shelves ( neighboring regions outwards from a CpG island shore and up to 4kb away from the CpG islands ) were defined according to each CpG island . The information for DNA-related attributes including GC content , CpG density ( defined as CpG observed vs . expected ratio ) were extracted from the sequences of putative CSM loci . The histone modifications H3K27ac , H3K36me3 , H3K4me1 , H3K4me3 , and H3K9ac for E14 cell line were obtained from the ENCODE Project [54] and lifted to mm10 . Each histone peak was divided into 100 equal sized bins , and the frequency of putative CSM loci for each bin was calculated for plotting . We made use of 17 mouse tissue methylomes derived from a single pregnant female mouse ( GSE42836 ) , with an average depth of 8 . 2-fold genomic coverage per tissue , covering on average 79 . 7% of the CpG dinucleotides in the mouse genome [28] . The putative CSM loci with no methylation data available were filtered out . The methylation levels for the remaining 2 , 096 putative CSM loci ( account for 99 . 6% of the total ) were determined in each tissue . Pearson’s correlations were then calculated based on the methylation levels of each pair of putative CSM loci and further used for hierarchical clustering to determine co-methylation modules , with a correlation coefficient cut-off set as 0 . 75 . The motif enrichment analyses were performed for each co-methylated module using Hypergeometric Optimization of Motif Enrichment ( HOMER ) [36] . Single-cell RNAseq data for 933 cells derived from mouse IB10 cell line subcloned from E14 ESCs [43] were re-analyzed in this study . The expression profiles of these cells were downloaded from GEO ( GSE65525 ) . We referred to the filtering steps for genes in Zeisel et al . 2015 [55] to select genes with strong correlations with many others . First , genes with less than 10 UMI counts across the 933 mouse ESCs were removed ( resulted in 23943 genes ) . Second , we calculated the Pearson’s correlation between each two genes based on their expression profiles across single cells . Next , a threshold of correlation among genes was set according to the 90th percentile of all the Pearson’s correlations ( ρ = 0 . 166 ) . We removed the gene if among the correlations involving this gene , only 4 or fewer correlation values were found to be larger than the threshold ( resulted in 22660 genes ) . Lastly , the statistic score ( υ ) defined in Eq . ( S13 ) in Klein et al . 2015 [43] was calculated and the genes with the top 10% υ were determined as HVGs ( resulted in 2266 genes ) .
|
DNA methylation is an epigenetic mark with covalent modification that occurs directly on genetic material . In vertebrates , the most common form of DNA methylation is 5-methylcytosine ( 5-mC ) at which a methyl group ( CH3 ) is attached to the cytosine nucleotide , especially in the context of CpG dinucleotide . DNA methylation has important regulatory roles in a broad range of biological processes and diseases , such as embryonic stem cells ( ESCs ) differentiation and development . ESC populations can be strikingly heterogeneous in DNA methylation . Emerging single-cell methods for capturing DNA methylation are being developed with the exciting potential to investigate the DNA methylation feature within complex and heterogeneous tissues . In this study , we implemented a computational pipeline to infer cell-subset specific methylation of ESCs from single-cell methylome . Through integrative analyses with transcription factor binding and single-cell transcriptome , we explored the underlying regulatory mechanisms associated with methylation heterogeneity in ESCs to interpret the biological functional relevance of methylation variations .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"cell",
"differentiation",
"developmental",
"biology",
"probability",
"distribution",
"methylation",
"mathematics",
"epigenetics",
"dna",
"mammalian",
"genomics",
"dna",
"methylation",
"chromatin",
"chromosome",
"biology",
"gene",
"expression",
"chemistry",
"chromatin",
"modification",
"dna",
"modification",
"genetic",
"loci",
"animal",
"genomics",
"probability",
"theory",
"biochemistry",
"cell",
"biology",
"nucleic",
"acids",
"genetics",
"biology",
"and",
"life",
"sciences",
"chemical",
"reactions",
"physical",
"sciences",
"genomics"
] |
2018
|
Integrative single-cell omics analyses reveal epigenetic heterogeneity in mouse embryonic stem cells
|
The mechanisms involved in the persistence of activated CD4+ T lymphocytes following primary human T leukemia/lymphoma virus type 1 ( HTLV-1 ) infection remain unclear . Here , we demonstrate that the HTLV-1 Tax oncoprotein modulates phosphorylation and transcriptional activity of the FOXO3a transcription factor , via upstream activation of the AKT pathway . De novo HTLV-1 infection of CD4+ T cells or direct lentiviral-mediated introduction of Tax led to AKT activation and AKT-dependent inactivation of FOXO3a , via phosphorylation of residues Ser253 and Thr32 . Inhibition of FOXO3a signalling led to the long-term survival of a population of highly activated , terminally differentiated CD4+Tax+CD27negCCR7neg T cells that maintained the capacity to disseminate infectious HTLV-1 . CD4+ T cell persistence was reversed by chemical inhibition of AKT activity , lentiviral-mediated expression of a dominant-negative form of FOXO3a or by specific small interfering RNA ( siRNA ) -mediated silencing of FOXO3a . Overall this study provides new mechanistic insight into the strategies used by HTLV-1 to increase long-term maintenance of Tax+CD4+ T lymphocytes during the early stages of HTLV-1 pathogenesis .
Infection with the human T cell leukemia virus type I ( HTLV-1 ) affects more than 20 million people worldwide [1] and HTLV-1-associated diseases are a major cause of mortality and morbidity in endemic areas where infection rates range from 2 to 30% . Chronic infection with HTLV-1 can result in a number of severe pathologies , including the aggressive adult T cell leukemia ( ATL ) and the progressive neurological disorder termed myelopathy/tropical spastic paraperasis ( HAM/TSP ) [1] . The majority of HTLV-1-infected individuals remain asymptomatic carriers ( AC ) of the virus but a proportion of AC ( 1–5% ) will develop ATL or HAM/TSP . CD4+ T cells are the main targets for viral infection [1] , [2] , although HTLV-1 can also infect cells of the myeloid lineage including dendritic cells and monocytes [3] , [4] . HTLV-1-associated diseases are characterized by profound deregulation of CD4+ T cells in terms of activation , immune function and apoptosis [5] , [6] , all of which are facilitated by the pleiotropic functions of the viral oncoprotein Tax [7]–[10] . In addition to controlling viral gene expression and replication , Tax contributes to malignant transformation of CD4+ T cells by modulating host signalling pathways including NF-κB , PI3K-AKT , and JAK-STAT [7]–[10] . The chronic nature of retrovirus infection has been linked to the activity of the Forkhhead box ( FOXO ) transcription factor family , and particularly to FOXO3a , which can alter the activation , survival and proliferative capacity of CD4+ T cell compartment [11]–[15] . FOXO3a is constitutively expressed in most cell types including T lymphocytes , where it regulates apoptosis , tumorigenesis and inflammation [16]–[18] , processes that are also deregulated in HTLV-1-associated diseases [5] , [19] , [20] . Specifically , FOXO3a stimulates expression of pro-apoptotic and anti-proliferative target genes such as BIM , FASL and p130 [21] . The FOXO family is subject to numerous post-translational modifications [17] and FOXO phosphorylation can serve either an inhibitory or an activating role in FOXO functions; phosphorylation by JNK activates FOXO3a function [22] while phosphorylation of specific residues ( Ser 253 and Thr32 ) by the serine/threonine kinase AKT inactivates FOXO3a [23] . Previous studies demonstrated that FOXO3a activity contributes to the progressive depletion of central memory CD4+ T cells in HIV-1-infected patients [15] . Modulation of FOXO3a activity also occurs during de novo HIV-1 infection , where HIV Tat protein induces FOXO3a activity leading to HIV-specific apoptosis [24] , [25] . In the present study , we demonstrate that expression of HTLV-1 Tax in primary human CD4+ T cells , either by productive HTLV-1 infection or lentiviral-mediated transduction results in the phosphorylation-dependent inactivation of FOXO3a via the upstream kinase AKT . FOXO3a inhibition resulted in long-term survival of terminally differentiated , Tax+CD27negCCR7neg CD4+ T cells that were capable of disseminating infectious HTLV-1 . These results provide insight into the mechanisms used by HTLV-1 to increase the long-term maintenance of Tax+CD4+ T lymphocytes during the early stages of HTLV-1 pathogenesis .
Primary CD3/CD28 activated CD4+ T cells were infected with HTLV-1 in a dose dependent manner ( Fig . 1A ) using an in vitro trans-infection system in which CD4+ T cells were co-cultured with HTLV-1 shedding MT-2 cells [26] . Following multiple rounds of T cell receptor ( TCR ) triggering , HTLV-1 infected T cells [Tax+ cells; blue] persisted for 21–28 days without a significant reduction in cell number , ( P<0 . 05 ) ( Fig . 1B ) ; in contrast , T cells that were not infected [Taxneg cells; black] displayed a reduction in cell number by 14 days post-infection ( pi ) ( P<0 . 01 ) . The half-life of gated TaxnegCD4+ T cells was 18 . 1 days pi , whereas a half-life calculation could not be determined for Tax+ T cells before 28 days . Using a combination of CD3 , CD45RA , CCR7 and CD27 surface markers , we evaluated the generation and maintenance of terminally differentiated ( CD3+CD45RA+/−CCR7negCD27neg ) T cells during a 28-day cycle of HTLV-1 infection ( Fig . 1C ) [27] , [28] . Repeated TCR triggering reduced the proportion of viable terminally differentiated CD27negCCR7neg effector cells among gated CD3+Taxneg T cells , whereas the proportion and cell number of Tax+ T lymphocytes increased , and maintained activation status ( 55 . 7±4 . 6% and 36 . 2±1 . 3% of CD3+CCR7negCD27negcells , respectively for Tax+ and Taxneg T cell population at 28 days; P<0 . 01 ) ( Fig . 1D and S1A Fig . ) . In addition , terminally differentiated Tax+CD4+ T cells produced infectious HTLV-1 , even after four weeks in culture , based on their capacity to transmit virus to freshly isolated autologous CD4+ T lymphocytes ( Fig . 1E ) . Overall these results demonstrate that HTLV-1 infection promotes the in vitro maintenance of terminally differentiated , virus-producing CD4+ T cells ( CD3+CCR7negCD27neg ) . We hypothesized that the enhanced cellular survival observed in HTLV-1 infected CD4+ T cells may be associated with the deregulation of FOXO3a signalling , given its important role in regulating cell proliferation and apoptosis in other retroviral infections [14] , [15] , [24] , [29] . We first investigated at 2 days pi the activation status of AKT , one of the upstream kinases responsible for phosphorylation of FOXO3a [23] ( Fig . 2A ) . Based on phosphorylation of FOXO3a at Ser473 residue , as detected by PhosFlow and Western Blotting approaches [9] , we concluded that the upstream kinase AKT was significantly activated in Tax-expressing cells ( P = 0 . 0317 and P<0 . 001 , respectively ) ( Fig . 2B–D ) . HTLV-1 infection led to an increase in phosphorylation of FOXO3a at residues S253 ( P<0 . 01 ) and Thr32 residues ( P<0 . 001 ) at 2 days pi ( Fig . 2C , D ) , residues that inactivate FOXO3a function [23] . Consistent with this observation , productively infected cells displayed reduced expression of FOXO3a downstream target genes p130 and Bim [15] , [23] . The phosphorylation status of IKKα/β , another upstream kinase of FOXO3a , was however unchanged ( Fig . 2C , D ) . Overall these results demonstrate that productive HTLV-1 infection provides a survival and proliferative persistence advantage to infected CD4+ T cells , and is associated with AKT-mediated inactivation of FOXO3a transcriptional activity . Among the proteins encoded by HTLV-1 , the Tax oncoprotein exerts its essential role in viral transcription , as well as in T cell transformation [30]–[32] . To determine whether Tax expression alone was sufficient to drive FOXO3a inactivation , HTLV-1 Tax was introduced into activated CD4+ T cells using lentiviral particle ( LVP ) -mediated transduction . Tax was detected using intracellular staining by flow cytometry ( Fig . 3A ) and a concentration of 80 ng LVP/106cells resulted in ∼40% Tax+ cells . LVPTax-transduced CD4+ T cells displayed higher expression levels of HTLV-1 Tax when compared to infected cells ( S1B Fig . ; fold increase ∼2 . 07; P = 0 . 0091 ) . A BioMark transcriptional high throughput qPCR analysis of LVP-transduced T cells demonstrated that Tax expression modulated mRNA levels of several Tax-modulated genes [8] , [31] , including an increase in IL-2 and a decrease in type I IFN-associated genes . Tax expression led to higher mRNA expression levels of CXCR4 , SOCS1 and myc proto-oncogene , as previously shown [7] , [33]–[35] . This analysis also demonstrated the activated/differentiated status of Tax-transduced CD4+ T cells , based on the increased expression of CD40L , CTLA-4 , IFNγ and IL7R mRNA ( Fig . 3B ) . Interestingly , Tax expression not only inhibited p130 and Bim expression ( Fig . 3B , C ) , but also down-regulated several other FOXO3a target genes; BCL6 , p27 , BIM , FASL , NOXA and PUMA were all downregulated at the mRNA levels at 24 and 48 h post-transduction ( Fig . 3B , C ) . Tax transduction also induced AKT activation ( P<0 . 001 ) [9] , phosphorylation of FOXO3a ( P<0 . 05 ) and inhibition of p130 ( P<0 . 05 ) at the protein level , all of which were significantly reversed by the addition of an AKT inhibitor , AKT inhibitor IV ( AKTi ) ( Fig . 4A , B ) . Conversely , treatment of transduced CD4+ T cells with 100 µg/mL IKK inhibitor II ( Calbiochem ) did not significantly alter the expression levels of phosphorylated FOXO3a ( S2B–C Fig . ) . Tax expression in CD4+ T cells did not modulate FOXO3a stability , as we found no significant change in its expression in the presence or absence of Tax even after 6 days of transduction ( S3A–B Fig . ) . Nonetheless Tax transduction resulted in increased nuclear localization of inactive pFOXO3a forms ( Ser253 and Thr32 residues ) ( S3C–D Fig . ) [13] . Overall this data demonstrate that Tax expression is sufficient to transcriptionally inactivate FOXO3a signaling , via upstream activation of AKT . We further investigated whether Tax promoted the persistence of activated CD4+ T cells through AKT induction and subsequent FOXO3a inactivation . Tax transduction alone [blue] was sufficient to maintain T cell survival for 28 days , and maintenance of the differentiated T cell population was mediated through AKT signaling , since the addition of the AKTi reduced T cell viability to basal levels ( Fig . 4C ) ( half-lives of transduced T cells with LVPempty [black] and LVPTax+AKTi [green] were 20 . 5 and 25 . 7 days , respectively ) . Tax expression was also associated with the terminally differentiated phenotype , similar to that of HTLV-1 productively infected-T cells ( Fig . 4D ) . A majority of the Tax-transduced CD4+ T cells belonged to the CD3+CCR7negCD27negsubset at 28 days after Tax transduction ( 55 . 2±6 . 3% and 23 . 9±6 . 3% for LVPTax and LVPempty infected T cells , respectively; P<0 . 01 ) . In addition , a strong correlation was established between the number of viable primary CD4+ T cells at 28 days post-transduction ( Fig . 4C ) and the inhibition of FOXO3a signaling observed as early as 2 days pi ( Fig . 4A , B ) , and measured by phosphorylation of AKT ( P<0 . 0001 ) , pFOXO3a-S253 ( P = 0 . 0031 ) , pFOXO3a-Thr32 ( P = 0 . 0138 ) , and expression of p130 ( P = 0 . 0138 ) ( Fig . 4E ) . Altogether , these results demonstrate that long-term survival of activated CD4+ T lymphocytes is mediated by a Tax-dependent , AKT phosphorylation and inactivation FOXO3a transcriptional activity . Based on the above results , we rationalized that the T cell persistence observed during HTLV-1 infection or Tax transduction could be reproduced by introduction of a dominant negative form of FOXO3a , termed FOXO3a Nt [15] , that encompasses the N-terminal DNA binding domain of FOXO3a ( aa1–304 ) but lacks the C-terminal transactivation domain . FOXO3a Nt acts as a competitive DNA binding inhibitor of transcriptionally active FOXO3a [15] , [36] and interferes with FOXO3a activation of pro-apoptotic and anti-proliferative target genes . As shown in Fig . 5A , lentiviral-mediated transduction of FOXO3a Nt prevented primary T cells from undergoing apoptosis ( Fig . 5A ) and thus mimicked Tax function . Expression of FOXO3a Nt also inhibited endogenous FOXO3a activity , as determined by reduced expression of p130 and Bim ( Fig . 5B ) . FOXO3a Nt expression resulted in persistence of a highly activated , terminally differentiated CD4+ T cell population , similar to that observed with Tax expression ( Fig . 5C , D ) . In addition , we found an increased percentage of terminally differentiated CD4+ T cells in the presence of specific FOXO3a siRNA at 14 days of culture ( Fig . 5E , F and S4 Fig . ) . Finally , we sought to determine if Tax physically interacted with an inactivated FOXO3a; by co-immunoprecipitation from Tax-transduced primary T cells , we did not observe an interaction between Tax and FOXO3a , although the interaction between Tax and PI3K was detected ( S5 Fig . ) [9] . It is possible that Tax-PI3K association stimulates AKT activity and thus indirectly contributes to phosphorylation of FOXO3a by AKT . Collectively , these results demonstrate that Tax expression enhanced T cell longevity and activation , through the inhibition of FOXO3a transcriptional activity , mediated by AKT phosphorylation at S253 and Thr32 residues .
HTLV-1 infection is associated with the expansion and leukemic transformation of CD4+ T lymphocytes , driven in large part by the chronic disruption of host signaling networks by the HTLV-1 Tax oncoprotein [8] , [31] , [37] , [38] . In the present study , we demonstrate that HTLV-1 infection enhances the in vitro cellular persistence of activated CD4+ T cells , the expansion of terminally differentiated ( CD3+CCR7negCD27neg ) cells and the functional inactivation of the FOXO3a pathway ( illustrated by the increased localization of inactive FOXO3a in the nucleus and the inhibition of several targets such as Bim and p130 ) . Mechanistically , both de novo HTLV-1 infection and Tax transduction stimulated AKT activation and downstream phosphorylation of FOXO3a at residues S253 and Thr32 ( Fig . 2 and 4A , B ) . Mechanistically , we did not observe an interaction between Tax and FOXO3a ( S5 Fig . ) , although the interactions between Tax and PI3K was detected as previously reported [9] . It is possible that Tax-PI3K association stimulates AKT activity and thus indirectly contributes to phosphorylation of FOXO3a by AKT . Also , we cannot exclude the possibility that post-translational modifications other than phosphorylation ( such as acetylation , methylation , ubiquitination ) may impact FOXO3a activity [36] , [39] . In addition , since mRNA and protein levels of Tax are generally barely detectable in ATL cells displaying constitutively active AKT [40] , [41] , it is possible that other Tax-independent mechanisms of FOXO3a inactivation may be used by HTLV-1 . Nevertheless , Tax-transduced T cells displayed a global inhibition of FOXO3a activity , illustrated by reduced expression of many pro-apoptotic and anti-proliferative target genes such as BIM , FASL , NOXA , p27 and p130 at 24–48 h post-transduction ( Fig . 3B , C ) . Overall this study provides new mechanistic insights by which Tax potentiates the long-term maintenance of CD4+ T lymphocytes following HTLV-1 infection . FOXO3a activity is also targeted by another HTLV-1 accessory protein , HBZ , which was shown to inhibit FOXO3a by interfering with its localization and ability to bind DNA [13] . The mechanistically distinct , yet functionally redundant , inhibition of FOXO3a signaling may be explained by the distinct kinetics of expression of these two regulatory proteins . It has been reported that , in contrast to Tax , HBZ is transcribed at high levels in chronically infected patient samples [42] . Conversely , even though Tax mRNA expression is relatively moderate , it is at its highest during the early stages of infection , specifically within the first week [43] . Additionally , Tax controls FOXO4 activity through degradation by the proteasome during ATL development [11] . The inhibition of FOXO3a or FOXO4 activity by distinct HTLV-1 accessory mechanisms also highlights the importance of FOXO inactivation as a strategy to perpetuate HTLV-1 infected CD4+ T lymphocytes and to contribute in the ATL development . Using a BioMark high throughput qPCR analysis ( S1 Table ) , we demonstrated that Tax not only mediated CD4+ T cell persistence through the inactivation of the FOXO3a pathway , but also down regulated type I IFN responses ( S6A Fig . ) , in part mediated by the negative regulator of the JAK-STAT1 pathway SOCS1 [7] , [34] . Taken together with our findings , these data indicate an involvement of Tax oncoprotein in targeting FOXO3a to concomitantly modulate the cell survival , as well as the type I IFN antiviral responses in CD4+ T cells and thus facilitate HTLV-1 infection . The identification of a pivotal role for FOXO3a in de novo HTLV-1 infection of CD4+ T cells in terms of cellular differentiation and persistence survival may have important consequences for retroviral pathogenesis . For instance , alterations in the microenvironment mediated by HIV infection significantly increase FOXO3a activity , with a major impact on T and B cell immunity and survival [14] , [15] , [44] , [45] . Kino et al . reported that the HIV accessory protein Vpr inhibited the ability of insulin to induce FOXO3a phosphorylation via AKT , thus interfering with its exclusion from the nucleus [46] . The expression of HIV-1 regulatory molecule Tat in specific T cells and macrophages also induced FOXO3a-mediated apoptosis [24] , [47] . FOXO3a activity also impacts the pathogenesis and the outcome of Abelson murine leukemia virus [29] . Several gene networks/pathways that were deregulated in Tax expressing CD4+ T cells were similarly disrupted in transcriptome analyses of PBMC from HTLV-1 infected individuals [34] , [48] , [49] ( S5B Fig . ) . For instance , transcriptional analysis of differentially regulated pathways demonstrated that cytokines IL15 , IL17R , IL7R were down regulated , and chemokine CXCR4 was up regulated in ATL patients; in contrast TNFRSF17 was down regulated while granzyme B and IL-2 were up regulated , in HAM/TSP and AC individuals ( S5B Fig . ) . It is tempting to speculate that disruption of signalling mechanisms identified early after de novo HTLV-1 infection are also important in the development and maintenance of HTLV-1 associated pathologies and could be targeted for clinical treatment . Due to poor prognosis of patients diagnosed with ATL , coupled with limited therapeutic options , novel immunological approaches including recombinant IL-7 , IFN-α , and neutralizing anti-CD25 or anti-CXCR4 antibodies are currently being used to treat ATL and HAM/TSP patients [50]–[53] . The present study indicates that the PI3K-AKT-FOXO3a pathway may also represent a potential therapeutic target in ATL patients . Since AKT inhibitors are already in clinical development [54] , they may offer a valuable addition to current therapeutic approaches .
RPMI-1640 media , FBS and antibiotics were provided by Wisent Technologies ( CA , USA ) . Unconjugated anti-Tax mAbs ( clone LT4 ) was generously provided by Dr . Yuetsu Tanaka ( Kitasato University , Kanagawa , Japan ) . MT-2 cell lines were obtained from the ATCC ( VA , USA ) . All antibodies used for flow cytometry were purchased from BD Biosciences , except for the antibody to CD45RA-ECD , which was from Beckman Coulter . All primary antibodies used in Western Blots ( anti-phospho forms of FOXO3a , anti-Bim , anti-ERK , anti-AKT , anti-PI3K p85 , anti-IKK , and anti-phospho-IKK Abs ) were purchased from Cell Signaling Technology Inc . , whereas anti-p130 and anti-actin were purchased from Sigma Aldrich; anti-FOXO3a from Abcam . 7-Aminoactinomycin D ( 7-AAD ) came from Invitrogen . Anti-Tax antibody ( clone 1A3 ) was purchased from Santa Cruz Biotechnology . Leukaphereses from healthy donors were obtained from the Royal Victoria Hospital , Montreal ( QC , Canada ) . Written informed consent approved by the Royal Victoria Hospital and the Jewish General Hospital review boards was provided to study participants . Research was conformed to ethical guidelines established by the ethics committee of the Royal Victoria Hospital , the Jewish General Hospital , and McGill University ( # BMB-2001-028 ) . PBMCs were isolated using Ficoll-Hypaque gradient and CD4+ T cells were then purified using the untouched CD4 isolation kit ( EasySep Human CD4+ T cell Enrichment Kit; StemCell Technologies , Vancouver , BC , Canada ) , allowing for more than 94% purification without any cell stimulation and apoptosis . CD4+ T cells were then activated 72 hours in RPMI complete in the presence of 1 µg/mL anti-CD28 ( BD Biosciences ) in 6 well plates pre-coated 24 hours earlier with 0 . 5 µg/mL anti-CD3 ( clone: OKT-3 , BioLegend; 2 . 106 cells/well ) . Cell-cell transmission of HTLV-1 was performed essentially as previously described [26] . 20 . 106 HTLV-1 produced cell line MT-2 were first irradiated at 15 , 000 rads and then mixed at various ratios ( 2∶1 to 1∶8 ) of irradiated MT-2 to activated CD4+ T cells . At several time points post-infection ( pi ) , collected cells were treated with Cell Dissociation Solution non-enzymatic according to the Sigma manufacturer's protocol and finally filtered ( 70 µm ) , prior further analyses . Protein lysates ( 2–10 µg ) from highly purified CD4+ T cell subsets were subjected to Western blot analysis as previously described [4] . Densitometric quantifications of protein of interest ( normalized to β-actin whose expression level was used as loading control ) were calculated using ImageJ software . The lentiviral vector pWPI ( empty vector ) , packaging plasmid psPAX2 and envelope plasmid pMD2G were generously provided by VGTI-Florida , whereas pCLXSN-Tax vector was purchased from Addgene ( ref: 44038; MA , USA ) . The FOXO3a N-terminal ( Nt ) fragment was cloned into pWPI , and as previously described [15] , lentiviral particles were produced in 293T cells that harboured either pWPI or pCLXSN ( empty controls ) , pWPI-FOXO3a Nt , or pCLXSN-Tax expression vector . Titers ( ng/mL ) of lentiviral constructs were assessed using HIV p24 ELISA ( Zeptometrix Corporation , USA ) . CD4+ T cells ( 4 . 104 ) were co-cultured in the presence of irradiated MT-2 cells ( ratio = 1∶1 ) in complete RPMI . At 3 days pi , cells were washed to remove the maximum of dead MT-2i and cultured in the presence of 1 µg/mL anti-gp46 Abs to avoid any de novo infection . On days 7 , 14 and 21 pi , cells were re-stimulated by adding fresh anti-CD3 and anti-CD28 Ab in the presence of anti-gp46 Abs ( at 10 µg/mL; Abcam ) to avoid any de novo infection . The efficiency of neutralizing anti-gp46 Ab was confirmed by the absence of p19 staining on primary cells that were treated since the onset of co-culture . At days 3 , 7 , 14 , 21 and 28 pi , viable cultured cells were counted by trypan blue exclusion and stained with 7-AAD , anti-CD3-PE , anti-CD45RA-ECD , anti-CD27-APC H7 , anti-CCR7-PE Cy7 and anti-Tax-Alexa 647 Ab for flow cytometry analyses . A total of 107 activated CD4+ T cells were first electroporated in the presence of control or FOXO3a-specific siRNA ( Invitrogen; 3 µg ) using nucleofector II technology , according the manufacturer's protocol ( Amaxa human T cell nucleofector kit ) . Transfected cells were then washed , and cultured alone for 14 days as described above in Long-term persistence assays . Total RNA was isolated from cells using RNeasy Kit ( Qiagen , Valencia , USA ) as per manufacturer's instructions . RNA was reverse transcribed using the SuperScript VILO cDNA synthesis kit according to manufacturer's instructions ( Invitrogen , Carlsbad , USA ) . PCR primers were designed using Roche's Universal Probe Library Assay Design Center ( www . universalprobelibrary . com ) and ordered from the Integrated DNA Technology company ( IDT , USA ) ( S1 Table ) . cDNA along with the entire pool of primers were pre-amplified for 14 cycles using TaqMan PreAmp Master Mix as per manufacturer's protocol ( Applied Biosystems , Foster City , USA ) . cDNA were exonuclease treated to get rid of excess primers using Exonuclease I ( E . coli ) ( New England Biolabs , Ipswich , USA ) . cDNA samples were prepared with 2× FastStart TaqMan Probe Master ( Roche , Penzberg , Germany ) , GE sample loading buffer ( Fluidigm , San Francisco , USA ) and Taq Polymerase ( Invitrogen , NY , USA ) . Assays were prepared with 2× assay loading reagent ( Fluidigm , NY , USA ) , primers ( IDT ) and probes ( Roche , Penzberg , Germany ) . Samples and assays were loaded in their appropriate inlets on a 48 . 48 BioMark chip . Chip was run on the Biomark HD System ( Fluidigm , San Francisco USA ) and enabled quantitative measurement of up to 48 different mRNAs in 48 samples under identical reaction conditions . Raw Ct values were calculated after 40 cycles by the real time PCR analysis software ( Fluidigm , San Francisco , USA ) and software designated failed reactions were discarded from analysis . All data are presented as a relative quantification with efficiency correction based on the relative expression of target gene versus the mean of ( gapdh+actin+β2 microglobulin ) as the invariant control . The N-fold differential expression of mRNA gene samples was expressed as 2ΔΔCt . The heatmap was produced with the R package pheatmap ( http://CRAN . R-project . org/package=pheatmap ) and gene expression is shown as gene-wise standardized expression ( Z score ) . Statistical analyses were performed as previously described [4] . *** , P<0 . 001; ** , P<0 . 01 and * , P<0 . 05 .
|
HTLV- infection contributes to the development of Adult T cell Leukemia ( ATL ) or the neurological disorder HTLV-1-associated myelopathy/tropical spastic paraparesis ( HAM/TSP ) . HTLV-1 principally targets CD4+ T lymphocytes and causes profound changes in activation , immune function and cell death . The molecular mechanisms involved in the persistence of infected CD4+ T cells following primary HTLV-1 infection remain unclear . We demonstrate here that the Tax oncoprotein inactivates the FOXO3a transcription factor to facilitate the long-term survival of a population of highly activated and terminally differentiated T cells that maintain the capacity to spread infectious viral particles . Mechanistically , expression of Tax oncoprotein in primary human CD4+ T cells resulted in the phosphorylation-dependent inactivation of FOXO3a , via the AKT kinase . Tax-mediated CD4+ T cell persistence was also reversed by chemical inhibition of the AKT pathway , and reproduced by the expression of a dominant negative version of FOXO3a itself or by silencing its transcriptionally active form using specific siRNA . Overall this study provides new mechanistic insights used by Tax to potentiate the long-term maintenance of CD4+ T lymphocytes following HTLV-1 infection and suggests that modulation of FOXO3a activity , using a range of inhibitors targeting the PI3K-AKT-FOXO3a pathway , may offer a valuable addition to current therapeutic approaches .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology",
"and",
"life",
"sciences",
"medicine",
"and",
"health",
"sciences"
] |
2014
|
HTLV-1 Tax-Mediated Inhibition of FOXO3a Activity Is Critical for the Persistence of Terminally Differentiated CD4+ T Cells
|
MHC genes , which code for proteins responsible for presenting pathogen-derived antigens to the host immune system , show remarkable copy-number variation both between and within species . However , the evolutionary forces driving this variation are poorly understood . Here , we use computer simulations to investigate whether evolution of the number of MHC variants in the genome can be shaped by the number of pathogen species the host population encounters ( pathogen richness ) . Our model assumed that while increasing a range of pathogens recognised , expressing additional MHC variants also incurs costs such as an increased risk of autoimmunity . We found that pathogen richness selected for high MHC copy number only when the costs were low . Furthermore , the shape of the association was modified by the rate of pathogen evolution , with faster pathogen mutation rates selecting for increased host MHC copy number , but only when pathogen richness was low to moderate . Thus , taking into account factors other than pathogen richness may help explain wide variation between vertebrate species in the number of MHC genes . Within population , variation in the number of unique MHC variants carried by individuals ( INV ) was observed under most parameter combinations , except at low pathogen richness . This variance gave rise to positive correlations between INV and host immunocompetence ( proportion of pathogens recognised ) . However , within-population variation in host immunocompetence declined with pathogen richness . Thus , counterintuitively , pathogens can contribute more to genetic variance for host fitness in species exposed to fewer pathogen species , with consequences to predictions from “Hamilton-Zuk” theory of sexual selection .
Major histocompatibility complex ( MHC ) genes code for proteins that present pathogen-derived oligopeptides ( antigens ) to T-cells , thus initiating an adaptive immune response . MHC genes are highly polymorphic , with dozens to hundreds of variants typically segregating in natural populations ( reviewed in [1–3] ) . This extreme polymorphism is thought to result from balancing selection imposed by pathogenic organisms [4 , 5] , and broadly-reported associations between MHC variants and susceptibility to infection are consistent with the role of pathogens in driving MHC evolution ( reviewed in [3] ) . Correlative and comparative analyses reported positive associations between parasite community richness and the number of MHC alleles within a population and strength of positive selection on MHC [6–9] , providing further support for the role of parasites in driving MHC diversity . However , a meta-analysis based on 112 mammalian species showed that the signs , let alone the strength , of such associations may vary between taxa [10] . Interpretation of these differences is hindered by the scarcity of theoretical work exploring the impact of parasite richness on MHC diversity . The majority of MHC research has focused on amino acid sequence polymorphism . However , an aspect of MHC diversity that has received less attention is the number of MHC variants carried by individuals ( in this article , we use the term “variants” to describe individual MHC diversity , which is the number of distinct MHC molecules carried by an individual; we prefer this to the term “alleles” often used in MHC literature , as the variants are not alleles in a strict sense , being often distributed over several , functionally equivalent MHC loci ) . This number of variants carried by individuals is typically much lower than the number found in the population . For example , in humans , there are 6–7 classical MHC loci , allowing for up to 12–14 different variants in a fully heterozygous individual , while the number of currently identified MHC alleles summed across those loci in the human population exceeds 17 000 ( IPD-IMGT/HLA Database ( 8 ) , Release 3 . 30 . 0 ) . Given that most alleles segregating in a population are thought to be maintained by selection from pathogens [3] , such discrepancy suggests that any individual’s MHC diversity is unlikely to be sufficient to efficiently respond to the whole spectrum of pathogens a host may encounter . This implies there is some intrinsic cost of expressing too high MHC diversity . One possible mechanism constraining evolution of individual MHC diversity is the deletion of self-reacting T-cells , during negative selection in the thymus . This deletion is likely to intensify with an increased number of expressed MHC variants , leading to a sub-optimal T-cell repertoire[11 , 12 , but see 13 for criticism] . Recently , this mechanism has been supported by the study of Migalska et al . [14] , who reported a negative correlation between the number of expressed MHC class I variants and T-cell receptor repertoire in the bank vole . However , alternative mechanisms [reviewed in 13] , such as increased risk of autoimmunity or the necessity to reach a critical concentration of MHC–peptide ligands at the surface of antigen-presenting cells , can also play a role . However , there are huge differences among species in the number of MHC loci , ranging from a very few e . g . in chicken [15] or humans [16] to dozens in some rodents [17] or passerine birds [18] . This raises the question: why should stabilizing selection on individual MHC diversity lead to such different numbers of MHC loci in different species ? Answering this question may have broad implications beyond immunogenetics and host-parasite coevolution . For example , it has been suggested that the exceptional evolutionary success of passerines , a family comprising ca . 70% of all bird species , has been facilitated by their supreme immunity due to extremely high numbers of MHC genes they harbour [19] . Furthermore , evolution of individual MHC diversity may have implications for biological conservation [20] or speciation [21] . Similarly to population-level polymorphism , interspecific differences in MHC copy number could be due to differences in the richness of parasites the species is exposed to , although studies which have examined this association are rare . O’Connor et al [22] found that among passerines , the number of unique MHC variants carried by an individual ( which should correlate with the number expressed MHC loci ) is lower in the Palearctic compared to Africa , which they ascribed to higher parasite species richness in the latter region . Similarly , Minias et al . [23] showed that passerine MHC expansion is related to migratory behaviour , likely in response to larger diversity of pathogens encountered by migratory species . In a more direct approach , Eizaguirre et al . [24] compared two lakes and two river populations of three-spined sticklebacks Gasterosteus aculeatus and found that lake populations , which systematically harboured more parasite species , had more MHC variants per individual . Similarly , Radwan et al . [25] found a positive relationship between a proxy for parasite load and individual number of MHC variants in ornate dragon lizard Ctenophorus ornatus populations inhabiting isolated patches of natural habitat . Interestingly , the authors did not find a significant association of parasite load with population-level allelic MHC richness and speculated that evolution of high copy number may weaken the balancing selection that might otherwise maintain high polymorphism . Similarly , Dearborn et al . [26] argued that high individual MHC diversity which arose in Leach’s storm-petrels , Oceanodroma leucorhoa by duplication followed by diversification of MHC class II genes should weaken advantage of heterozygosity at MHC . However , there is a lack of theoretical work on how parasite richness simultaneously affects MHC allelic richness and the number of MHC loci . Here , we aim to fill this gap using computer simulations based on a framework that has previously been shown to be effective in recovering some of the most important features of MHC evolution , such as high polymorphism , frequency-dependent selection , heterozygote advantage and positive selection [27 , 28] . The model simulates interactions of MHC molecules and antigens produced by pathogens by matching strings of bits , which can mutate both in hosts and in parasites [27 , 28] . Here , we introduce a new feature to the framework to allow duplication and deletion of MHC genes . We then investigate how the number of pathogen species infecting a host affects the evolution of MHC allelic richness and the number of MHC loci .
Pathogen richness affected the number of unique MHC variants per individual ( individual number of variants , INV henceforth ) in a complex way , shaped by significant interactions with pathogen evolution rate and with the intrinsic cost of expressing more MHC variants ( described by cost parameter α ) ( Table 1 ) . Parasite species richness clearly increased INV at lower α , but at higher α there was little change in the INV across the levels of pathogen richness ( Fig 1 ) . There was also a significant pathogen richness × pathogen mutation rate interaction ( Table 1 ) , with the positive effect of higher pathogen mutation rate observed at low pathogen richness , but declining to zero as pathogen richness increased ( Fig 1 ) . The selection acting on host MHC genotypes , as measured by coefficient of variation ( CV ) in host fitness ( which in our simulation was determined solely by host immunocompetence , i . e . the proportion of pathogens recognized ) , was shaped by the significant interaction between pathogen richness and mutation rate ( Table 2 ) . CV in host fitness was much higher at higher pathogen mutation rate when pathogen species number was low ( Fig 2 ) . However , the differences between mutation rates declined , as did CV itself , with an increase in pathogen richness . We observed considerable within-population variation in the INV under most scenarios , except when the number of pathogens was very low ( S4 Fig ) . The slopes of the relationship between the number of pathogens presented to the immune system and INV increased with pathogen richness , but slopes were generally low at higher pathogen mutation rate ( Fig 3 ) . The number of MHC variants segregating in a host population ( PNV henceforth ) was driven by the significant three-way interaction between α , pathogen richness and mutation rate ( Table 3 ) . PNV generally increased with pathogen richness ( Fig 4 , Table 3 ) , but the increase was lower at α = 0 . 08 . High pathogen mutation rate increased PNV only at the combination of low α and high parasite richness ( Fig 4 ) . Interestingly , at low α , PNV largely reflected INV , whereas at high α PNV increased ( Fig 4 ) despite that INV did not ( Fig 1; see S5 Fig for correlation between INV and PNV ) .
Our model showed that under the Red Queen-like dynamics of MHC evolution , evolution of INV is shaped by a complex interaction of several factors , including pathogen richness , pathogen mutation rate , and the intrinsic cost of expressing many MHC molecules . Verbal arguments [e . g . 8 , 22 , 23] assumed that INV should generally increase with the number of pathogen species . In our simulations , this was the case only under some parameter combinations , and the form of the relationship depended both on the intrinsic costs of expressing additional MHC variants and on pathogen mutation rate . INV consistently increased across the investigated range of parasite species when the intrinsic cost of large MHC repertoire was small . However , with higher values for the cost factor ( α ) , we did not observe such an increase . This shows that high pathogen richness will not necessarily lead to the evolutionary expansion of MHC gene family . Little is known about the nature of the intrinsic costs of MHC expansion , and even less on how taxa differ in this respect , and therefore we have not modelled any particular mechanism underlying these costs in our simulations . The prevalent explanation is that high MHC diversity increases negative selection of self-reactive T-cell receptors [11 , 12] , impairing efficiency of immune response . This scenario has recently been supported in bank voles , where TCR repertoire has been demonstrated to decrease with the number of MHC class II variants [14] . Under such a scenario , intermediate numbers of MHC variants should result in the most efficient clearing of infections , as has been observed in some empirical studies , including bank voles [29–31] . However , several studies utilising extensive variation in INV present in passerine birds have observed either no such a relationship , or negative associations between INV and infection [e . g . 32 , 33–35] . This suggests that the nature of the intrinsic costs of expressing many MHC variants may differ between passerines and mammals . One possibility is that expressing too many MHC variants does not compromise passerine TCR repertoire in a way similar to that observed in bank voles [14] , allowing rapid expansion of MHC gene family ( compare Fig 1 ) . The study of TCR repertoires in birds , and the way they are shaped by MHC , emerges as an attractive target for future studies . More generally , understanding inter-specific difference in INV will require extensive study of intrinsic costs of expressing additional MHC variants across vertebrate taxa . Our model indicates that higher pathogen richness is unlikely to explain a spectacular expansions of MHC gene family , such as those observed among passerines . Ancestrally , birds have been characterised by a small number of MHC genes , which is still observed in non-passerines [23] . Our results suggest that expansion to dozens of MHC loci observed among some passerine superfamilies ( Sylvioidea , Passeroidea and Muscicapoidea [23] ) would require the number of pathogen in these lineages to be manifold higher compared to basal groups ( compare Fig 1 ) , which does not appear biologically feasible . Another factor which influenced the evolution of INV in our simulations was pathogen mutation rate , the effect of which was most pronounced at low pathogen species numbers ( Fig 1 ) . This pattern was mirrored by variance in host fitness ( measured as CV ) , which was the highest for high pathogen mutation rate combined with low pathogen richness ( Fig 2 ) . Host haplotypes with more MHC variants should be more likely to carry a variant conferring resistance to a parasite , but efficient evasion of MHC-recognition by fast-evolving pathogens could weaken association between INV and pathogen recognition , consistent with our results ( Fig 3 ) . Still , efficient parasite evasion should favour novel MHC variants [28] , and such variants are more likely to arise when the number of copies in the genome is high . When average number of MHC variants is already high , however , possessing an extra MCH copy provides relatively smaller advantage in terms of potential for beneficial mutation . This may explain why the effect of pathogen evolution rate on INV was observed only at low pathogen richness ( where INV was relatively low ) . Similarly , high CV in host fitness at low numbers of pathogen species likely results from the fact that a haplotype that is resistant to a prevalent pathogen genotype ( of any species ) will gain considerable advantage , whereas with many pathogen species resistance to any given pathogen contributes relatively less to fitness . This may explain why CV in host fitness declined with pathogen richness , which may have interesting implications for predictions stemming from Hamilton and Zuk’s ( 1982 ) theory of sexual selection . This theory poses that costly epigamic traits , such as long feathers or bright colouration , are subject to mating preferences because they reflect the genetic aspect of resistance to pathogens . At the interspecific level , the Hamilton-Zuk hypothesis predicts that higher risk of parasite infection should enhance sexual selection for extreme values of such epigamic traits , because of increasing contribution of pathogens to genetic variance in fitness ( Hamilton and Zuk 1982 , Berlanger and Zuk 2014 ) . Paradoxically , our results indicate that while host genetic diversity for resistance ( measured by the number of MHC variants segregating in populations ) increased , the variance in host fitness decreased . Our results thus indicate that if the number of pathogen species attacking the host is used as a measure of selective pressure from pathogens , the predicted relationship with an elaboration of epigamic traits might be counter-intuitive . INV was positively correlated with pathogen recognition ability ( Fig 3 ) , as assumed by models of copy-number evolution [11 , 12] . Nevertheless , our simulations suggest no such association should be expected when the number of MHC variants in the species is low ( Fig 3 ) . Indeed , in root voles Microtus oeconomus and guppy fish Poecilia reticulata , both characterised by a low to a moderate number of MHC loci ( 1–3 ) , possessing particular variants has been shown to be more important than the number of expressed MHC loci [36 , 37] . More interestingly , INV was not a good predictor of pathogen recognition efficiency when parasites evolved fast ( Fig 3 ) . As discussed above , fast-evolving parasites are more effective in evading recognition by MHC haplotypes prevalent in a population than slow-evolving ones . In consequence , when parasites evolve fast , possessing a rare-but-resistant MHC variant should have more of an effect on resistance than possessing many variants . Our simulations revealed tight associations between PNV and INV , but the slope of the associations depends on the intrinsic cost of expressing additional variants ( S5 Fig ) . At high α , where increase in pathogen richness does not result in a consistent increase in INV , PNV nevertheless increases , resulting in slope >1 . At low α , at which INV is more free to evolve , PNV largely reflects INV , which implies that when selection from many parasites favours gene duplication , per-locus polymorphism may change very little . Our results may explain the findings of comparative analyses showing that high pathogen richness is sometimes not found to be associated with MHC allelic richness ( a per-locus measure of variation ) , despite its effect on the rate of molecular evolution at MHC antigen binding sites [8 , 9] . Two recent comparative studies [22 , 23] demonstrated that among passerines , individual number of MHC variants decreases with such likely correlates of pathogen richness as latitude or migratory behaviour ( although we know of no work directly linking INV to parasite richness ) . It would be interesting to see if INV could explain PNV in this system , as predicted by our model . Concluding , our study showed that in general , pathogen richness selects for expansion of MHC gene family , but is unlikely to explain striking inter-specific differences in the number of MHC genes . The latter can be can be modulated both by the rate at which parasites evolve and , probably more critically , on the strength of mechanisms selecting against the high number of copies in the genome . These mechanisms are not well understood , but warrant investigation as potential causal factors underlying differences in MHC genes family sizes between species . In species which evolved high INV under selective pressure from many pathogen species , within population variation in INV can nevertheless be maintained . Despite high variation in INV , host variance in immunocompetence should , according to our model results , be lower in species experiencing selection pressure from higher diversity of parasites .
The model is based on an approach first used by Borghans et al . [27] , which simulated interactions between the peptide-binding grooves of MHC molecules and antigens derived from pathogens by aligning two strings of zeros and ones ( bitstrings ) . In our model , each MHC molecule was represented as a 16-bit-long string , which can be thought of as a representation of the amino acids that form pockets implicated in the specificity of antigen binding ( there are 12–23 polymorphic sites contacting antigens in human MHC molecules [38] ) . A pathogen was represented by a single 6000-bit long antigenic molecule , which was tested for a match with host MHC at all possible 16-bit epitopes which could be produced from the antigenic molecule . Antigen binding occurred when there was a match in all position of the bit strings representing the peptide bindig groove of MHC molecules and an epitope ( S1 Fig ) . Utilising 16 bits , we could simulate 65 , 536 ( 216 ) MHC epitopes . The probability of finding a random 16-bit sub-string ( epitope ) in a random 6000 bit antigen was approximately 0 . 084 , a number corresponding to the empirical estimates of an MHC molecule binding a random epitope produced by viral pathogens [39 , 40] . The way we simulated antigens differed from that in Borghans et al . [27] and earlier adaptations of their approach [e . g . 28 , 41] in which a single parasite was represented by a set of 20 independent , 16-bit-long antigens , and 7 matched bits were used as a threshold for pathogen recognition . The rationale for simulating a long antigenic molecule and a higher threshold number of matching bits was that it reduced the number of recognition motifs shared between pathogen species , and , additionally , it facilitated further diversification of species-specific motifs by conserving some of them in a species-specific manner ( see below ) . Nevertheless , the probability of binding a random antigen produced by a given pathogen remained broadly consistent with those earlier studies [27 , 28 , 41] . Hosts co-evolved with a variable number ( 2–64 ) of haploid pathogen species , which , to simplify simulations , had population sizes equal to that of their hosts [as in previous studies , e . g . 28] . Instead of simulating larger pathogen populations ( as would have been observed in nature ) , higher probability of a mutation in large populations was emulated by a higher pathogen mutation rate . There were 10 pathogen generations per one host generation to reflect the fact that pathogens typically have faster generation times than hosts . The fitness of pathogen haplotypes was proportional to the number of hosts a pathogen successfully infected , and host fitness was proportional to the number of pathogens recognized ( see below for details ) . The next generation of both hosts and pathogens was drawn in proportion to their fitness . The algorithm described above effectively simulates a host-parasite co-evolution system with Red Queen dynamics [see 28 for more details] . MHC genes ( i . e . 16 bit-long strings ) were located on one diploid pair of host chromosomes . The size of the host population was fixed at 1000 individuals . These individuals were exposed to one , randomly chosen individual of each pathogen species . If the infection was successful ( i . e . the pathogen was not recognized by any of the host’s MHC genes ) , the parasite clone could evolve in the host for 10 generations , ecologically excluding infections by other clones of the same species . If the infection was unsuccessful , a new , randomly selected individual attempted an infection in the next pathogen generation; if successful , this pathogen would be allowed to reproduce until 10 pathogen generations were completed . After 10 pathogen generation passed , host fitness was determined . The fitness was proportional to the number of pathogens presented by the host , but we additionally introduced a cost of having additional MHC variants ( see below ) . The cost was introduced to reflect various mechanisms thought to counteract unconstrained expansion of MHC region [11 , 13] . Our preliminary analyses indicated that the number of MHC loci rapidly increased and did not stabilise even after thousands of generations if no cost was introduced . The host fitness function was calculated according to the equation: fhost=P⋅e− ( αN ) 2 ( 1 ) where P is the number of pathogen species a host recognized ( thus avoiding infection ) , N is the number of unique MHC variants in the host’s genome and α is the cost factor . The cost factor α was selected to achieve a realistic number of unique MHC types in an individual ( i . e . from a few to few dozens ) . After interactions with pathogens ( across 10 pathogen generation cycles ) , hosts reproduced with probability proportional to their fitness . We have not modelled separate sexes ( i . e . our hosts were equivalent to out-crossing hermaphrodites ) . During reproduction , each of the diploid mates provided one chromosome ( selected randomly ) to the resulting progeny . Each mating resulted in one offspring , but individuals could be selected for mating more than once ( which was more likely for high fitness hosts ) , and random mating pair selection was repeated until the size of the host population NH was restored . Host chromosomes could undergo two types of mutations: micromutations within the 16-bit string , and copy number mutations . Micromutations were represented by a flip of a single bit with a given probability . This can be thought of as a non-synonymous substitution in an antigen binding site of MHC molecule , which could occur as a non-synonymous mutation , or micro-recombination ( the latter may be the predominant mode of mutation at human MHC [42] ) . For the sake of consistency with previous simulation studies , in which mutation rates were given as the probability of change in MHC molecule as a whole ( replacement of old MHC with a new one ) , we report the mutation rate per MHC molecule ( i . e . 16 bit string ) , which translates into per bit rate according to the equation: μbit=1− ( 1−μMHC ) 1/16 ( 2 ) where μMHC is the mutation rate per MHC peptide , μbit is the mutation rate per single bit in the MHC PBR ( see also S1 Appendix in [28] . We used a host mutation rate of 10−4 per MHC molecule ( or 6 . 25 × 10−6 per PBR ) , which appears realistic based on published literature [42] . We also simulated “macromutations” in MHC , which could be thought of as recombination or gene conversion of large fragments of an exon coding for peptide binding groove . Following earlier work [27] , we simulated macromutations by producing random strings of bits . However , mutation mode have not qualitatively affect our results ( S6 Fig ) , therefore in the main text we only present results for micromuations . Copy number of MHC genes could change via duplication or deletion . Duplication was modelled by adding a new copy of the original sequence on the same chromosome , and during deletion , a gene disappeared from the chromosome . However , the algorithm did not allow the number of MHC loci to go below 1 per chromosome . Each gene could be duplicated with probability 10−3 and deleted with probability 10−3 , which is higher than direct empirical estimates for large structural variant indels in human genomes [43] , but was the minimum necessary for the number of copies to stabilise within realistic computing time . Neo- or sub- functionalization of duplicated loci could occur by mutations described above . We simulated a variable number of haploid pathogen species , with the population size of each species equal to that of the host . A species was initiated as a single antigen , and thus individuals were sharing the evolutionary origin and history within species , but separate species were initialized independently . Because the possible number of distinct 6000 bit antigens is very large ( ~1 . 5 × 101806 ) , pathogen species showed little overlap in their antigenic profiles ( S2 Fig; the probability that a random 16-bit-long sub-string will be present in both of two random and independent 6000-bit-long strings equals to ~0 . 0842 ) . We trialled a variant of the simulations in which each pathogen species had a randomly-assigned , species-specific 33% of bits conserved , but this did not result in a different interpretation , and we do not report results from this version . Pathogen haplotypes were selected for reproduction with probability proportional to the number of hosts they had infected . During each of 10 pathogen generations , every host was matched with a randomly selected individual of each pathogen species and the outcome of the infection was evaluated according to the bit-matching rules described above . A pathogen species could infect an individual host only once per host generation . The successful pathogens reproduced parthenogenetically by producing 'clonal' progeny . The progeny could mutate by changing a single bit to the opposite before advancing to the next round of infections . To examine the role of pathogen evolution rate on our results , we simulated two pathogen mutation rates: 10−5 and 5 × 10−5 . These values resulted in the host-parasite coevolution we sought to produce in our simulations . Exploratory analysis showed that at lower pathogen mutation rates than reported above , pathogens were unable to adapt to host genotypes fast enough , whereas at higher mutation rate fitness differences between host genotypes were small , precluding effective co-evolution [see 44] . For comparison , the influenza virus NS gene mutates at a rate of 1 . 5 × 10−5 [45] . The model’s program was written in C++14 language , which generates a number of text files of simulation results that were then analysed and plotted using Python scripts . The general scheme of the algorithm is shown in S3 Fig . The source code and its documentation can be obtained from https://github . com/pbentkowski/MHC_Evolution . Summaries of the model’s parameters and their values are given in Table 4 . Each combination of parameters was run 20 times , except for the most computationally demanding simulations with 64 pathogens , which were run 10 times . For evaluation purposes , we considered the last 1250 host generation when the dynamics of the host-parasite co-evolution stabilised in term of the numbers of MHC variants in both populations and individuals . For that period and for each run , we calculated mean PNV and mean CV in host fitness ( pathogen presentation ability ) by averaging it over 1250 latest host generations . To calculate mean INV , we first averaged across individuals at a given time step , and then took the averaged simulated values across 1250 latest host generations . Coefficients of regression of INV on pathogen presentation ability ( Fig 3 ) was based on a population 'snapshot' at host generation #5000 ( the last one ) , when we recorded detailed information on each host ( what genes they had , what pathogen species they presented ) . These data are available in Supplementary File 1 . Results were analysed with linear models , with an average INV , PNV or CV in host fitness as a response variable , and α , pathogen mutation rate and pathogen richness , and their interactions , as fixed factors . Statistical analyses were done in R 3 . 4 . 2 . [46] .
|
Highly polymorphic genes of the Major Histocompatibility Complex ( MHC ) code for proteins responsible for presenting antigens to lymphocytes , thus initiating adaptive immune response . The polymorphism is driven by coevolution with parasites which are selected to evade recognition by MHC proteins . Expressing many MHC molecules could ensure that an individual could present antigens of most pathogen species encountered , but this comes at a cost , such as enhanced negative selection on lymphocytes leading to holes in T-cell receptor repertoire . Our simulations showed that evolution of the number of MHC genes in the genome is driven by a complex interaction between three factors we explored: pathogen richness , the intrinsic cost of expressing additional MHC variants , and pathogen mutation rate . In contrast to verbal arguments , our results indicate that pathogen richness does not always selects for MHC gene family expansion . Taking into account factors other than pathogen richness , in particular costs of expressing additional MHC variants which are still poorly understood , may help explain striking interspecific variation in the number of MHC genes . Counterintuitively , our results also demonstrated that opportunity for selection on immunocompetence should decrease with MHC gene family expansion .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
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"proteins",
"passerines",
"eukaryota",
"cell",
"biology",
"clinical",
"immunology",
"host-pathogen",
"interactions",
"myosins",
"biology",
"and",
"life",
"sciences",
"evolutionary",
"biology",
"amniotes",
"organisms"
] |
2019
|
Evolution of major histocompatibility complex gene copy number
|
Replicative DNA polymerases cannot insert efficiently nucleotides at sites of base lesions . This function is taken over by specialized translesion DNA synthesis ( TLS ) polymerases to allow DNA replication completion in the presence of DNA damage . In eukaryotes , Rad6- and Rad18-mediated PCNA ubiquitination at lysine 164 promotes recruitment of TLS polymerases , allowing cells to efficiently cope with DNA damage . However , several studies showed that TLS polymerases can be recruited also in the absence of PCNA ubiquitination . We hypothesized that the stability of the interactions between DNA polymerase δ ( Pol δ ) subunits and/or between Pol δ and PCNA at the primer/template junction is a crucial factor to determine the requirement of PCNA ubiquitination . To test this hypothesis , we used a structural mutant of Pol δ in which the interaction between Pol3 and Pol31 is inhibited . We found that in yeast , rad18Δ-associated UV hypersensitivity is suppressed by pol3-ct , a mutant allele of the POL3 gene that encodes the catalytic subunit of replicative Pol δ . pol3-ct suppressor effect was specifically dependent on the Rev1 and Pol ζ TLS polymerases . This result strongly suggests that TLS polymerases could rely much less on PCNA ubiquitination when Pol δ interaction with PCNA is partially compromised by mutations . In agreement with this model , we found that the pol3-FI allele suppressed rad18Δ-associated UV sensitivity as observed for pol3-ct . This POL3 allele carries mutations within a putative PCNA Interacting Peptide ( PIP ) motif . We then provided molecular and genetic evidence that this motif could contribute to Pol δ-PCNA interaction indirectly , although it is not a bona fide PIP . Overall , our results suggest that the primary role of PCNA ubiquitination is to allow TLS polymerases to outcompete Pol δ for PCNA access upon DNA damage .
Despite the remarkable catalytic activities of replicative DNA polymerases , these enzymes cannot efficiently incorporate nucleotides opposite damaged template DNA . Therefore , in eukaryotes , translesion DNA synthesis ( TLS ) is carried out by specialized , low stringency damage-tolerant polymerases belonging to the Y-family ( Pol η , Pol ι , Pol κ , and Rev1 ) and the B family ( Pol ζ ) [1] . The inevitable consequence of the TLS polymerases feature to synthesize across DNA lesions with no associated proofreading activity , is their overall reduced fidelity , even at undamaged templates . This could lead to accumulation of unwanted mutations and therefore , their activity needs to be tightly regulated [2 , 3] . The main mechanism of damage-induced activation of TLS polymerases involves covalent modifications of the sliding clamp PCNA by ubiquitin or SUMO peptides [4–7] . PCNA mono-ubiquitination at the highly conserved lysine ( K ) 164 by the ubiquitin-conjugating enzyme ( E2 ) Rad6 and the ubiquitin ligase ( E3 ) Rad18 is a prerequisite for the activation of TLS polymerases [4 , 8 , 9] . Subsequently , K164 is poly-ubiquitinated via a K63-linked poly-ubiquitin chain , for which Rad5 and the Mms2-Ubc13 complex are additionally required . PCNA poly-ubiquitination then triggers a template switch mechanism [4 , 10] . The recruitment of DNA replication and repair proteins to DNA by PCNA is often dependent on the presence of a conserved protein-protein interaction motif , the "PCNA-interacting protein" or PIP-box [11] . The PIP-box consensus sequence , Qxx ( M/L/I ) xxF ( Y/F ) , is well conserved [12–14] . All Y family DNA polymerases interact with PCNA . PIP domains are found in Pol η , Pol ι and Pol κ [15–21] , whereas Rev1 interacts with PCNA through an additional motif [22] . In addition , one or two ubiquitin-binding domains ( UBDs ) were identified in all eukaryotic members of the Y family [23 , 24] . They are the prototypes of two distinct classes: the ubiquitin-binding zinc finger ( UBZ ) and the helical ubiquitin-binding motif ( UBM ) . Mutational inactivation of these motifs abolishes TLS in yeast and prevents damage-induced association of the mutated polymerases with PCNA in mammalian cells [22–29] . In vitro biochemical assays showed that ubiquitinated PCNA activates the replicative Pol δ similarly to unmodified PCNA [30 , 31] . Pol η takes the place of Pol δ at the 3’ extending end only when DNA synthesis by Pol δ is stalled and PCNA is ubiquitinated [32 , 33] . These observations lend support to an expanded "tool-belt" model [2]: ubiquitin primarily acts as a supplementary interaction module to which TLS polymerases first bind before the switch between polymerases . Support for this model comes from structural studies on ubiquitinated PCNA , the catalytic core of Pol η , its PIP-box bound to PCNA and its UBZ domain in complex with ubiquitin [34–38] . Particularly , it was observed that ubiquitin attachment to PCNA does not alter its conformation . Moreover , the ubiquitin moiety is positioned on the back side of the PCNA ring , presumably far away from its front side where PIP binding sites are localized and where polymerases position themselves and perform DNA synthesis [37 , 38] . Although the role of PCNA ubiquitination is firmly established , a number of observations indicate that TLS polymerases can be recruited also in the absence of PCNA modification . In yeast , early genetic studies showed that spontaneous mutagenesis in wild type ( WT ) and in the rad18Δ mutant , in which PCNA cannot be ubiquitinated , depends on Pol ζ and Rev1 [39–41] . More recently , studies using human cell extracts [42 , 43] , mouse embryo fibroblasts [44–46] , mouse pre-B cells [45] or DT40 chicken cells [47 , 48] reported activation of TLS polymerases with unmodified PCNA in various contexts: bypass of site-specific DNA lesions on plasmids , somatic hypermutation on immunoglobulin genes , and UV radiation- or methyl methanesulfonate-induced DNA damage . These results are puzzling because the conditions that allow the recruitment of TLS polymerases independently of PCNA ubiquitination are currently unknown . The finding that Pol δ and TLS polymerases share common structural features is another challenging issue to understand the preferential recruitment of Pol δ over TLS polymerases . Pol δ from S . cerevisiae has three subunits: Pol3 , Pol31 and Pol32 . Pol3 is the catalytic subunit that contains the polymerase and the 3’ to 5’ exonuclease active site domains . In addition , Pol3 carries a C-terminal domain ( CTD ) with eight conserved cysteine residues that is folded distinctly from the catalytic domain . The first set of four cysteines ( CysA ) resembles a zinc ribbon motif [49] and is crucial for mediating DNA-dependent interactions between PCNA and Pol δ [50] . The second C-terminal set of cysteines ( CysB ) is an essential Fe-S cluster [50] . Pol31 is the essential structural B subunit of 55 kDa with which Pol3 CTD interacts . Pol32 is a non-essential subunit of 40 kDa ( or C subunit ) that is tethered solely via interactions with Pol31 [51] . Moreover , similarly to some TLS polymerases , Pol δ carries PIP motifs . A canonical PIP motif lies in the C-terminal end of Pol32 and has been shown to interact with PCNA by two-hybrid analyses [52] . Non-canonical PIP motifs are present in Pol3 and Pol31 and they contribute to PCNA-stimulated DNA synthesis [53] . Thus , the presence of multiple distant PIP motifs on the different Pol δ subunits could provide a positive advantage for the access to PCNA compared with monomeric TLS polymerases that carry one or several adjacent PIP motifs [20 , 21] . More surprisingly , Pol δ and Pol ζ share the same B and C subunits ( Pol31 and Pol32 in yeast; P50 and P66 in mammals ) [54–56] . This raises the possibility that Pol δ preferential access to unmodified PCNA is determined mostly via its catalytic subunit . It has been proposed that in yeast , the Rev3/Rev7 catalytic complex of Pol ζ replaces Pol3 on the Pol31/Pol32 platform to allow the polymerase switch from Pol δ to Pol ζ upon DNA damage [54] . In this scenario , PCNA ubiquitination could trigger the specific poly-ubiquitination of Pol3 by Def1 and its subsequent proteosomal degradation [57] . Given these structural similarities between Pol δ and TLS polymerases , we hypothesized that destabilization of the interaction between Pol δ subunits and/or between Pol δ and PCNA could modify the regulation of replicative and TLS polymerase loading on PCNA . To this aim , we used a mutant allele of POL3 ( pol3-ct ) . First we showed that in budding yeast , this mutant leads to an increase of UV resistance in rad18Δ cells . We then demonstrated that the suppression of the rad18Δ phenotype by pol3-ct occurs via Pol ζ and Rev1 , although PCNA is not ubiquitinated . Moreover , mutational inactivation of Pol3 non-canonical PIP motif in the rad18Δ mutant led also to a robust increase in UV resistance . This suggests that a partial loss of the Pol δ-PCNA interaction is responsible for the increased UV resistance , when PCNA is not ubiquitinated . Using isothermal titration calorimetry ( ITC ) , we found that Pol3 non-canonical PIP motif is probably not a bona fide PIP domain and might participate only indirectly in the PCNA-Pol δ interaction . Overall , our results suggest that the stability of the interaction between PCNA and Pol δ a the primer/template junction is a crucial factor to determine the requirement of PCNA ubiquitination .
In rad18Δ yeast mutant cells , UV-induced PCNA ubiquitination is abolished and the damage avoidance pathways are inhibited . Indeed , rad18Δ cells displayed UV hypersensitivity compared with WT cells ( Fig 1A ) . Conversely , UV resistance was significantly increased in rad18Δ cells that carried also the pol3-ct allele of POL3 ( Fig 1A ) in which the substitution of a Leu codon with a stop codon resulted in the loss of the four last C-terminal amino acids ( LSKW ) of Pol3 [58] . This mutation destabilizes the interaction between Pol3 C-terminal domain and Pol31 [59] . This result suggested that WT Pol δ could contribute to the UV sensitivity associated with RAD18 deletion . To test this hypothesis , we performed a detailed genetic analysis . It has been already reported that rad18Δ-associated UV sensitivity is suppressed in the absence of the Srs2 helicase [60] or of the Siz1 SUMO ligase [61] . This suppression requires the homologous recombination ( HR ) genes RAD51 and RAD52 . However , in rad18Δ cells in which RAD51 or RAD52 was also deleted , UV resistance was increased in the presence of pol3-ct ( Fig 1B and 1C ) . Therefore , we concluded that rad18Δ suppression by pol3-ct is mechanistically not related to HR . Moreover , pol3-ct did not suppress UV sensitivity associated with rad51Δ at high UV doses ( S1A Fig ) . These findings suggested that pol3-ct effect could be specific to the DNA damage tolerance ( DDT ) pathways controlled by PCNA ubiquitination . To determine whether pol3-ct suppressor effect was related to PCNA ubiquitination , we tested also the impact of pol3-ct in the pol30-K164R mutant . In this mutant , PCNA K164 is mutated , thereby preventing its ubiquitination by Rad6/Rad18 and sumoylation by Siz1 . The pol30-K164R mutant was less sensitive to UV than the rad18Δ single mutant ( Fig 1D ) . This phenotype can be explained by the lack of PCNA sumoylation in the pol30-K164R mutant that could lead to inefficient Srs2 recruitment [61 , 62] and consequently , to frequent channeling of UV-induced DNA lesions towards HR . Moreover , pol30-K164R UV sensitivity was not affected by pol3-ct ( Fig 1D ) . Yet , in the absence of HR , pol3-ct had a clear suppressor effect ( Fig 1D ) , thereby showing that pol3-ct restores UV resistance to both pol30-K164R and rad18Δ cells . Overall , our observations support the hypothesis that pol3-ct relieves partially the requirement of PCNA ubiquitination for UV resistance . Several DDT pathways are regulated by Rad18 ( i . e . , TLS activation and template switching ) . We noticed that pol3-ct suppressed the rad18Δ phenotype only partially and that rad18Δ pol3-ct cells remained sensitive to UV compared with WT cells ( Fig 1A ) . This suggested that pol3-ct suppressor effect could involve mainly one of the Rad18-dependent pathways . To test this hypothesis , we first evaluated pol3-ct effect within the template switching pathway that is triggered by PCNA poly-ubiquitination catalyzed by Rad5 and Mms2-Ubc13 . A rad5Δ mutant and , to a lesser extent , an mms2Δ mutant ( both defective in PCNA poly-ubiquitination ) regained some UV resistance in the presence of pol3-ct ( Fig 2A and 2B ) . Moreover , both rad5Δ and mms2Δ strains showed a negative interaction with rad51Δ upon UV radiation , and the UV sensitivity of the rad5Δ rad51Δ and mms2Δ rad51Δ double mutants was similarly reduced by pol3-ct ( Fig 2C and 2D ) . Thus , some of the UV-induced DNA lesions handled via template switching are bypassed in the rad5Δ and mms2Δ mutants thanks to pol3-ct . To bypass UV-induced lesions during DNA replication , Rad18 also controls the Pol η-dependent error-free and the Pol ζ- and Rev1-dependent error-prone TLS pathways . Concerning Pol η ( encoded by RAD30 ) , pol3-ct partially suppressed the UV sensitivity associated with the rad30Δ allele ( Fig 3A ) . However , this effect was abolished in the absence of Rad51 , suggesting a complex relationship between Pol δ-ct and Pol η ( S7B Fig ) . pol3-ct had little effect on UV resistance in the Pol ζ and Rev1 mutants , even at higher UV doses ( Fig 3B and 3C; S1B and S1C Fig ) . We noticed that in the rev3Δ rad51Δ and rev1Δ rad51Δ double mutants , pol3-ct had a minor suppressive effect , suggesting a modest Pol η recruitment ( Fig 3B and 3C; S7C Fig ) . These observations imply that Pol ζ and Rev1 are still required for UV resistance in the pol3-ct mutant . As pol3-ct did not display a pervasive suppressor effect in TLS polymerase-defective mutants , we conclude that Pol δ-ct cannot take the place of TLS polymerases . Conversely , the pol3-ct suppressor effect clearly acts on the RAD18-dependent poly-ubiquitination sub-pathway . To explain these results , we hypothesized that Pol δ-ct reduces the PCNA ubiquitination requirement for TLS polymerase recruitment . In this model , suppression of the rad18Δ phenotype by pol3-ct should require the TLS polymerases . The suppression of rad18Δ UV sensitivity by pol3-ct was still observed in the rad30Δ mutant ( Fig 4A ) , which suggests a minor role for Pol η in the bypass of UV-induced DNA lesions in the pol3-ct rad18Δ double mutant . On the contrary , the rev3Δ rad18Δ pol3-ct and rev1Δ rad18Δ pol3-ct strains were UV hypersensitive , like the rev3Δ rad18Δ and rev1Δ rad18Δ double mutants ( Fig 4B and 4C ) . Thus , suppression of rad18Δ UV sensitivity by pol3-ct occurs only when Pol ζ and Rev1 are present . Interestingly , we observed that suppression of rad5Δ-associated UV sensitivity by pol3-ct was dependent on both Pol ζ and Pol η ( S2 Fig ) , showing that Pol η can play a role in pol3-ct strains when PCNA is ubiquitinated . Rev1 carries a conserved UBM motif in its C-terminus . As pol3-ct relieves partially the requirement for PCNA ubiquitination , the Rev1 UBM should be dispensable in the pol3-ct mutant . Point mutations within this motif ( L821A , P822A , I825A ) abolish its functional interaction with ubiquitinated PCNA in vitro and strongly lower cell resistance to UV radiation in vivo [29] . In the pol3-ct background , UV sensitivity was not reduced in the rev1-12 mutant that carries the L821A , P822A , I825A mutations , ( Fig 4D ) . However , the rad18Δ phenotype was suppressed by pol3-ct in the rev1-12 mutant ( Fig 4E ) . Thus , we conclude that in the pol3-ct mutant , Pol ζ and Rev1 bypass UV-induced DNA lesions in the absence of PCNA ubiquitination independently of Rev1 UBM . UV-induced mutagenesis mostly depends on Pol ζ and Rev1 and on PCNA ubiquitination [8 , 63–65] . In the pol3-ct mutant , the role of PCNA ubiquitination in UV-induced mutagenesis could be less important . To test this hypothesis , we monitored UV-induced mutagenesis with the CAN1 forward mutation assay after exposure to a UV dose of 15 J/m2 . At this dose , only about 1% of rad18Δ cells survived and pol3-ct strongly suppressed rad18Δ-associated UV sensitivity ( Fig 1A ) . Interestingly , we observed that the frequency of UV-induced canavanine resistant ( CanR ) cells was higher in the rad18Δ pol3-ct double mutant compared with rad18Δ cells ( Fig 4F ) . This result was obtained with strains coming from two different progenies and is no longer observed in absence of Rev1 ( Fig 4F ) . Thus , these observations further support the hypothesis that upon UV irradiation , Pol ζ and Rev1 are recruited independently of PCNA ubiquitination in the pol3-ct mutant . Pol3-ct interacts weakly with Pol31 [59] . To determine whether this interaction plays a role in PCNA ubiquitination requirement , we wanted to identify mutations that affect this interaction and then test them genetically in the rad18Δ mutant . Based on our previous three-dimensional model of the Pol3-CTD and Pol31 complex from the published structures of human p50 and of Pol α [59 , 66 , 67] ( Fig 5A ) , we focused our analysis on Arg1043 of Pol3 and Asp304 of Pol31 , which is opposite to Pol3 Arg1043 ( Fig 5A ) . Two-hybrid analyses [59] indicated that co-transformants carrying pBTM116-Pol31 and pACT2-Pol3-R1043G displayed temperature-sensitive β-galactosidase activity after incubation for two days . Compared with the activity of pBTM116-Pol31 and pACT2-Pol3-CTD co-transformants , their activity was low at 22°C and even lower at 30°C , showing that Pol3-R1043G gives similar results than Pol3-ct ( Fig 5B; [59] ) . Co-transformants carrying pBTM116-Pol31-D304N and pACT2-Pol3-CTD did not show any measurable β-galactosidase activity at either temperature ( Fig 5B ) . pol3-R1043G did not confer sensitivity to the genotoxic agent hydroxyurea ( HU ) differently from pol3-ct ( S3A Fig ) . Yet , we observed synthetic lethality between pol3-R1043G and pol32Δ , a phenotype shared with pol3-ct ( Material & Methods; S4 Fig ) . The pol31-D304N allele ( originally named hys2-2; [68] ) conferred temperature and HU sensitivities ( S3A Fig ) and was synthetic lethal with pol32Δ ( S4 Fig ) . In summary , the Pol3-R1043G mutation affected the structure of the Pol δ holoenzyme although to a lesser extent than the Pol3-ct and the Pol31-D304N mutations . To determine the role of the interaction between Pol3 CTD and Pol31 in bypassing PCNA ubiquitination , we first evaluated UV sensitivity in the pol3-ct , pol3-R1043G and pol31-D304N strains . The pol3-ct and pol3-R1043G mutants were not UV sensitive and showed UV-induced mutagenesis frequencies similar to those of WT cells ( Fig 5C; S5 Fig ) . Conversely , the pol31-D304N allele increased UV sensitivity ( Fig 5C ) . As Pol31 is a member of the Pol ζ complex , we hypothesized that this phenotype could be caused by a partial impairment of the interaction between Pol31 and Rev3 CTD . Interestingly , UV-induced mutagenesis in the pol31-D304N mutant was significantly decreased , but not abolished ( S5 Fig ) . Based on the UV phenotypes of Pol δ mutants , we hypothesized that rad18Δ UV hypersensitivity could be suppressed by pol3-R1043G , but not by pol31-D304N due to its possible defect in the Pol ζ-dependent pathway . However , neither pol3-R1043G nor pol31-D304N suppressed the rad18Δ phenotype ( Fig 5D ) . Thus , in disagreement with our initial prediction , suppression of rad18Δ UV sensitivity by pol3-ct might not be related to a defective interaction between Pol3 CTD and Pol31 . To test genetically this hypothesis , we used the pol31-K358I allele that suppresses pol3-ct effect [59] . K358 is accessible for interaction with Pol3 CTD residues ( Fig 5A ) . The pol31-K358I allele did not modify the suppression of rad18Δ UV hypersensitivity by pol3-ct , reinforcing the conclusion that pol3-ct effect on rad18Δ is not related to the interaction between Pol3 CTD and Pol31 ( Fig 5E ) . As an alternative hypothesis , TLS polymerase recruitment could be facilitated by Pol δ mutations that weaken its interaction with PCNA . Our strategy was again to find these mutations and to test them subsequently in rad18Δ strains . However , this search was hampered by the lack of a ternary structure of PCNA complexed with Pol δ on DNA . Hence , we focused on Pol δ sites that were described as PIP motifs [52 , 53] . Pol32 PIP motif ( QxxLxxFF ) contains the PIP consensus sequence , is highly conserved in eukaryotes [52] ( S6C Fig ) and has been implicated in PCNA interaction by two-hybrid screens [52] . The Pol31 motif LxxYF lacks the conserved Gln residue , is not conserved and is located in the Pol31 PDE domain [53 , 67] ( S6B Fig ) . In our Pol31 model , the aromatic dyad is exposed and the preceding L324 could be buried ( Fig 5A ) . The Pol3 motif QxxxLxxFI differs from the consensus PIP motif by the presence of an extra residue between the conserved Gln and Leu residues and by the lack of the second aromatic residue at the end of the motif . Moreover , this motif is located just upstream of the highly conserved CysA cysteine module ( Fig 5A ) , and only the Leu and Phe residues are conserved in eukaryotes ( S6A Fig ) . To test the functionality of these three motifs , we characterized by microcalorimetry the affinity and stoichiometry of the interaction between purified PCNA and synthetic peptides that contain the putative PIP-boxes found in Pol δ . The Pol3 and Pol31 peptides were of equal length ( 21 amino acids ) , whereas the Pol32 PIP motif , which is located in the extreme C-terminus of Pol32 , was three amino acids shorter . In parallel , we tested the canonical PIP motif of Msh6 that mediates the interaction of MutSα with PCNA [69] . The binding reactions between Msh6 and Pol32 peptides with PCNA gave large exothermic signals and the interactions could be fitted with a one-site binding model after integration . The dissociation constant ( Kd ) of the Msh6 and Pol32 PIP motifs were 0 . 31 μM and 0 . 46 μM at 30°C , respectively ( Table 1 , Fig 6C and 6D ) . Both interactions presented favorable enthalpy and entropy , as previously observed for other canonical PIP motifs [14 , 70 , 71] . In the same experimental condition , the non-canonical Pol3 and Pol31 PIP motifs showed no interaction or very weak interaction , respectively ( Fig 6A and 6B ) . In summary , while the Pol32 PIP motif has the characteristics of a functional PIP motif , the proposed Pol3 and Pol31 non-canonical motifs may have a role in Pol δ function or in Pol δ interaction with PCNA , but possibly not as bona fide PIP domains . Although they do not interact with PCNA , the Pol3 and Pol31 non-canonical PIP motifs contribute to PCNA-stimulated DNA synthesis in vitro [53] . To study their role in vivo , we mutated the Pol3 QxxxLxxFI and Pol31 LxxYF motifs and generated strains that carry either the pol3-FI1002-1003AA allele ( thereafter , named pol3-FI ) or the pol31-YF327-328AA allele ( thereafter , named pol31-YF ) . We also produced the pol32-FF344-345LL allele ( thereafter , named pol32-pip ) by directed mutagenesis of the Pol32 PIP motif . Mutants carrying these alleles did show neither slow growth , nor temperature or HU sensitivity ( S3 Fig ) . In addition , all double mutants were viable and thermo-resistant . Only the pol3-FI pol32-pip double mutant was sensitive to HU ( S3B Fig ) . Importantly , the pol3-FI pol31-YF pol32-pip triple mutant was viable , strongly suggesting that in this mutant , PCNA is still a processivity factor for Pol δ ( S3B Fig ) . Moreover , the triple mutant was more sensitive to HU than the pol3-FI pol32-pip double mutant . This suggests that pol31-YF has some effect on Pol δ structure stability . Accordingly , pol31-YF showed synthetic lethality with pol32Δ ( S4 Fig ) and an additive effect with pol3-ct upon HU treatment ( S3A Fig ) . Finally , the Pol31 LxxYF motif is close to the Pol31-D304 residue involved in the interaction with Pol3 CTD ( Fig 5A ) . By two-hybrid assay , we found that the Pol31 YF residues were as important for this interaction as the D304 residue ( Fig 5B ) . This also suggests that these residues contribute to the overall stability of the Pol δ holoenzyme . UV resistance ( Fig 7A ) and UV-induced mutagenesis ( S5 Fig ) were comparable in the three pol3-FI , pol31-YF and pol32-pip single Pol δ mutants and in WT cells . Thus , these mutants carry a functional Pol ζ . Therefore , we could test the role of the Pol δ mutated motifs in the absence of PCNA ubiquitination . UV sensitivity was comparable in the pol32-pip rad18Δ double mutant and in the rad18Δ single mutant ( Fig 7B ) . Thus , the Pol32-pip mutation did not affect the competition for PCNA access between Pol δ and Pol ζ . We obtained similar results with the pol31-YF rad18Δ mutant ( Fig 7B ) . Conversely , pol3-FI suppressed rad18Δ-associated UV hypersensitivity and this effect was REV3 dependent ( Fig 7C ) . In agreement with these observations , UV-induced mutagenesis was significantly increased in rad18Δ pol3-FI cells compared with rad18Δ cells ( Fig 7D ) . Thus , only pol3-FI recapitulates the phenotypes of the pol3-ct allele in the rad18Δ background . The Pol3 FI residues ( mutated in the pol3-FI strain ) and Pol3 LSKW residues ( lost in the pol3-ct strain ) are close to the CysA module of Pol3-CTD in our structural model ( Fig 5A ) . Therefore , the phenotypes shared by pol3-ct and pol3-FI could be due to destabilization of the CysA module that has been proposed to be essential for the Pol δ-PCNA interaction ( [50] , Discussion ) .
The pol3-ct and pol3-FI alleles do not confer UV sensitivity to WT cells or to cells with defects in one or several UV-induced DNA lesion tolerance pathways ( [59] , Figs 5C and 7A , S1 Fig ) . Moreover , these alleles are not associated with a defect in UV-induced mutagenesis ( S5 Fig ) . These key features allowed us to detect the partial rescue of the rad18Δ mutant by pol3-ct and pol3-FI following UV radiation . Although rad18Δ still confers high UV sensitivity in the presence of the POL3 alleles ( Figs 1A and 7B ) , we considered the phenotypic suppression robust for the following reasons . At higher UV doses , rad18Δ cell survival is increased at least ten-fold in the presence of the pol3-ct and pol3-FI alleles . pol3-ct suppresses the rad18Δ phenotype in the W303 and the FF genetic backgrounds and in several genetic contexts ( pol30-K164R , rad5Δ and mms2Δ ) . Finally , this suppression seems to occur only through the error-prone repair pathway , which explains why rad18Δ cells still retain high UV sensitivity . In addition , pol3-ct suppression of rad18Δ UV sensitivity is novel . It does not require functional HR , differently from the srs2Δ- and siz1Δ-dependent suppressions [60 , 61] . Moreover , studies based on the inactivation of the Pol δ proofreading domain in yeast and DT40 cells indicated that Pol δ contributes to TLS in vivo [72 , 73] . This propensity of the exonuclease-dead Pol δ to perform TLS in yeast is independent of Pol ζ and remarkably suppresses also rad18Δ-associated hypersensitivity to DNA damaging agents [72] . On the other hand , rad18Δ suppression by Pol3-ct and pol3-FI depends on Pol ζ and Rev1 . Our results allow us to revisit the role of PCNA ubiquitination and of polymerase switch upon UV radiation . How to explain that Pol δ-ct and Pol δ-FI allow the recruitment of Rev1 and Pol ζ independently of PCNA ubiquitination ? The finding that Pol ζ may function as a four-subunit enzyme ( Pol ζ4 ) has led to the suggestion that the polymerase switch involves dissociation of the Pol δ catalytic subunit ( Pol3 in yeast ) from its structural subunits ( Pol31 and Pol32 in yeast ) , which will become part of Pol ζ [54–56] . In addition , DNA damage and PCNA ubiquitination trigger Def1-dependent degradation of the Pol3 catalytic subunit of yeast Pol δ [57] . Def1-dependent Pol3 degradation could be the initial event leading to polymerase switching on the Pol31/Pol32 platform [57] . The genetic suppression of rad18Δ by pol3-ct and pol3-FI described here depends on Pol ζ . In addition , pol3-ct partially impairs the interaction between Pol3 and Pol31 [59] . These observations fit well with a model in which in our pol3 mutants , the switch between Pol3 and Rev3/Rev7 on the Pol31/Pol32 platform occurs spontaneously without the need of PCNA ubiquitination and the subsequent Pol3 poly-ubiquitination by Def1 . Yet , and rather unexpectedly , the results of our genetic analyses imply that the impaired interaction between Pol3 and Pol31 is not involved in the suppression of rad18Δ . The Pol3-R1043G mutant protein displays the same defect as the pol3-ct mutant in the two-hybrid interaction with Pol31 , and both pol3-R1043G and pol3-ct are synthetic lethal with pol32Δ . However , pol3-R1043G does not suppress rad18Δ ( Fig 5D ) . Similarly , the simultaneous mutational inactivation of Pol31 Y327 and F328 impairs the interaction between Pol31 and Pol3-CTD ( Fig 5B ) and leads to synthetic lethality with pol32Δ ( S4 Fig ) . However , the pol31-YF mutant allele does not suppress rad18Δ ( Fig 7B ) . The Pol31-K358I mutation restores stable Pol3-Pol31 interactions in the pol3-ct mutant and pol31-K358I suppresses pol3-ct-associated HU sensitivity [59] . On the contrary , pol31-K358I does not affect rad18Δ suppression by pol3-ct ( Fig 5E ) . Finally , the pol3-FI allele suppresses rad18Δ , although the Pol3 F1002 and I1003 residues are upstream of the C-terminal Pol3 domain that is sufficient for interaction with Pol31 [74] ( Fig 7C ) . Thus , the model implying a switch between Pol3 and Rev3/Rev7 on a Pol31/Pol32 platform does not fully account for the bypass of PCNA ubiquitination observed in the pol3 mutants . These observations suggest that the effect of the Pol3-ct mutation on Pol δ structure does not impair only the interaction with Pol31 . Therefore , we hypothesized that pol3-ct destabilizes the interaction between Pol δ and PCNA . Hence , we expected to find Pol δ mutations that affect this interaction and that would share the pol3-ct phenotypes . However , the lack of a ternary structure that includes Pol δ bound to PCNA at primer ends made our search uncertain . Moreover , Pol δ interacts with PCNA through multiple sites and a possible redundancy in binding interactions could allow Pol δ to adopt flexible configurations with PCNA [75 , 76] . Our understanding of PCNA-Pol δ interactions is even more challenged by our finding that among the three proposed PIP motifs of Pol δ , only the Pol32 motif is a bona fide PIP motif ( Table 1 , Fig 6A ) [53] . The observation that the pol3-FI pol31-YF pol32-pip triple mutant is viable in our strain backgrounds ( W303 and FF18733; S4 Fig and S1 Table ) clearly indicates that Pol δ interacts with PCNA in this triple mutant . Despite the uncertainties surrounding PCNA-Pol δ interaction , the Pol3 F1002 and I1003 residues are separated by only five amino-acids from Pol3 C1009 , the first cysteine of the CysA zinc-binding segment of Pol3 CTD ( Fig 5A ) . This CysA motif is likely to be crucial for the interaction with PCNA [50] . Thus , Pol3 F1002 and I1003 , while not directly required for the interaction with PCNA , might contribute to the optimum structural conformation of Pol3 CysA . Destabilization of this CysA module could affect the interaction between Pol δ and PCNA and consequently facilitate the recruitment of TLS polymerases to PCNA . To substantiate this hypothesis , we wanted to mutate the CysA cysteines ( C1009 , C1012 or C1024 ) , but failed . This suggests that these cysteines are essential and that the CysA module is crucial for PCNA-Pol δ complex stability [50 , 77] . The last Pol3 C-terminal W1097 residue is close to the CysA module and therefore , could play a role in its stabilization as well ( Fig 5A ) . Thus , the loss of the last four LSKW residues in the pol3-ct mutant might affect the interaction with Pol31 and also with PCNA . Our genetic observations support a role for Pol3 F1002 and I1003 and for Pol3 W1097 in promoting stable interactions between Pol3 and PCNA . Only pol3-ct and pol3-FI suppress the UV hypersensitivity associated with rad18Δ and remarkably , only these two POL3 alleles display an additive negative effect with the pol32-pip allele upon HU treatment ( S3 Fig ) . Similarly , when both Pol3 CysA and Pol32 PIP motifs are mutated , the PCNA-dependent replication activity of Pol δ is almost abolished , showing an additive negative effect between these sites in vitro [50] . Therefore , we propose that the impaired interaction between a Pol3 CTD mutant and PCNA is the origin of the suppression of rad18Δ-dependent UV sensitivity . The observation that pol3-ct and pol3-FI suppress rad18Δ-associated UV hypersensitivity leads to the conclusion that WT Pol δ is in part responsible for this sensitivity . In addition , our data suggest that Pol δ competes with TLS polymerases for the access to primer/template junctions in the front side of PCNA ( Fig 8A ) . Therefore , PCNA ubiquitination might provide a docking site on the back side of PCNA for recruiting TLS polymerases , thereby increasing their local accumulation near a stalled 3’ end ( Fig 8B ) . Spontaneous or active Pol δ displacement from its interaction domains with PCNA at sites of DNA damage would be accompanied by the concomitant binding of a TLS polymerase to the front side of PCNA and its access to the primer end . In the absence of PCNA ubiquitination , preferential binding of Pol δ to the front side of PCNA due to stronger affinity or mass action would inhibit the polymerase switch at blocking DNA lesions . Our model is based on the activation of Pol ζ and Rev1 independently of PCNA ubiquitination observed in the pol3-ct and pol3-FI mutants . A noticeable issue in our model is the absence of a similar activation of Pol η in rad18Δ cells . From this unexpected result , we hypothesized that the key factor of rad18Δ suppression might be the specific interaction between Pol η or Pol ζ with PCNA ( Fig 8B ) . Given the structurally conserved organization of the catalytic Pol3 and Rev3 subunits [50] , the CysA metal-binding motif in Rev3 CTD and the CysA motif of Pol3 might interact with the same PCNA region . Thus , upon destabilization of Pol3 CTD , PCNA ubiquitination could be bypassed only through the binding of Rev1 and Rev3 CTD to PCNA ( Fig 8C ) . Differently from Pol ζ , Pol η relies on a PIP motif for its interaction with PCNA and does not carry a metal-binding motif in its CTD . If the PCNA domain for interaction with CysA modules were different from the domain that interacts with the PIP motifs , Pol η would not be able to compete with Pol δ even when Pol δ harbors a mutated CTD ( Fig 8C ) . According to this hypothesis , pol32-pip should suppress rad18Δ-associated UV sensitivity in a Pol η-dependent manner ( Fig 8D ) . However , this prediction is not supported by our results suggesting that Pol η requires additional PCNA-dependent engagement at the primer terminus to incorporate distorting DNA lesions , such as pyrimidine dimers , into its catalytic site . To test this hypothesis , it will be important to investigate the suppression of rad18Δ-associated phenotypes by new Pol δ structural mutants or at DNA lesions different from those induced by UV exposure . Our results also bring some insights into Pol δ regulatory role at stalled replication forks with ubiquitinated PCNA ( S7 Fig ) . The pol3-ct allele does not increase UV-induced mutagenesis and is not associated with UV sensitivity . Thus , the pol3-ct effect on the choice of DDT pathway might be too subtle to be detected in the presence of PCNA ubiquitination ( S7A Fig ) . However , the rad30Δ strain carrying pol3-ct showed higher UV resistance , and this effect was abolished in the rad30Δ rad51Δ pol3-ct mutant ( Fig 3A ) . This observation suggests that the Pol δ-ct defect might facilitate the channeling of UV-induced DNA lesions processed by Pol η towards the HR pathway ( S7B Fig ) . We observed a minor pol3-ct-dependent suppression of UV sensitivity with the rev3Δ strains ( S1B Fig ) and with the rev3Δ rad51Δ and the rev1Δ rad51Δ strains ( Fig 3B and 3C ) . These last observations suggest an easier Pol η recruitment in competition with Pol δ-ct ( S7C Fig ) . This hypothesis is supported by the clear suppression of the rad5Δ- and mms2Δ-associated UV sensitivity by pol3-ct ( Fig 2 ) that depends on Pol ζ but also on Pol η ( S2 Fig; S7D Fig ) . Pol η would be more suitable to displace the mutant Pol δ-ct in the rad5Δ and mms2Δ mutants than in the rad18Δ mutant thanks to its initial binding to ubiquitin on PCNA K164 . It remains to be determined whether Pol η always requires PCNA mono-ubiquitination to efficiently outcompete Pol δ-ct or whether this requirement is less stringent for DNA lesions not induced by UV . Nevertheless , although PCNA undergoes mono-ubiquitination following UV radiation in the rad5Δ and mms2Δ mutants , WT Pol δ still competes with TLS polymerases . Therefore , the competition between Pol δ and the TLS polymerases could play a role in the choice leading to the template switching pathway . For instance , Pol δ preferential binding to PCNA in suitable genomic contexts could prevent TLS and allow PCNA poly-ubiquitination to occur more frequently . Conversely , genomic sequences that challenge the replication fork stability and the stable interaction between Pol δ and PCNA could favor the recruitment of TLS polymerases . Interestingly , no increase in UV resistance in absence of Rad51 is observed with Pol δ-ct ( S1 and S7E Figs ) . This suggests that Pol δ regulator role in the presence of ubiquitinated PCNA might take place preferentially at stalled replication forks rather than at single-strand gaps behind the forks that could be processed by HR . Finally , such a regulatory role for Pol δ in DNA damage tolerance could be also a key feature in TLS that occurs independently of PCNA ubiquitination ( see Introduction ) . In agreement with this hypothesis , some genomic regions , such as repetitive sequence elements , hinder elongation by Pol δ and lead to its dissociation from the replication forks [78] . On the other hand , TLS polymerases are emerging as major actors in DNA synthesis at repetitive DNA sequences and their resulting non-B DNA structures [79] . Thus , a simple prediction would be that TLS polymerases sparsely rely on PCNA ubiquitination for their recruitment at intrinsically difficult to replicate loci . Other post-translational modifications might be at work in these situations , as exemplified by human Pol η recruitment to replication forks thanks to its sumoylation , but independently of PCNA ubiquitination [80] .
The S . cerevisiae strains used in the present study are isogenic derivatives of W303-1A [81] or FF18733 ( his7-2 , leu2-3 , 112 , lys1-1 , trp1-289 , ura3-52 ) and are listed in S1 Table . Gene deletions were performed by using a PCR-mediated one-step replacement technique [82 , 83] . All deletions were confirmed by PCR amplification of genomic DNA . Meiotic segregation of the pol30-K164R allele was followed by PCR amplification with the primers P96 and P97 . To study the effect of the rev1-12 allele , rev1Δ strains were transformed with centromeric pBL820 plasmids carrying either REV1 or rev1-12 ( a generous gift by Dr Peter Burgers ) [29] . The genomic pol3-R1043G mutation was generated by using the plasmid pL11 . pL11 is a derivative of pL6 obtained by cloning the C-terminal end of POL3 ( from +2503 of the ORF to 523 bp downstream the stop codon ) in pRS306 [58] . The pol3-R1043G mutation was inserted in pL11 after site-directed mutagenesis performed in pL6 . For targeting the mutation by the two-step transplacement procedure [84] , pL11 was digested with HindIII ( site located 425 bp downstream of the pol3-R1043G mutation ) . The pol3-FI1002-1003AA and pol31-YF327-328AA mutations were generated by using the pPOL519 and pPOL545 plasmids ( kindly provided by Dr Louise Prakash ) , respectively [53] . For targeting the mutations , pPOL519 and pPOL545 were digested with KpnI and MfeI , respectively . The pol32-FF344-345LL mutations were generated using plasmid pL19 that was obtained by cloning the C-terminal end of POL32 ( from +273 of the ORF to 500 bp downstream the stop codon ) in pRS306 of . Prior to transformation , pL19 was digested with XbaI . All media were prepared as previously described [85] . Mutants were selected on YPD medium containing 300 mg/L of geneticin ( Sigma ) or nourseothricine ( cloNAT; Werner BioAgents ) . Cells in stationary phase were plated at appropriate dilutions on YPD and synthetic plates containing canavanine prior to UV irradiation . UV irradiation was performed using a 264nm source . Survival was determined as the number of cells forming colonies on YPD plates following exposure to a given UV dose divided by the number of cells forming colonies on YPD plates in absence of irradiation . Data used to draw graphs represent the mean ± SEM of at least 3 independent experiments . UV-induced mutagenesis was assessed with the CAN1 forward-mutation assay . UV-induced mutagenesis frequencies were obtained by dividing the number of colonies growing on selective medium containing canavanine ( i . e . , canavanine-resistant , canR , cells ) by the number of cells that survived irradiation . The number of canR colonies obtained after irradiation was corrected by subtracting the number of canR colonies present on the non-irradiated plates and corresponding to spontaneous mutation events . UV-induced mutagenesis in the rad18Δ background has been measured at 15 J/m2 . Yeast cells were directly picked from fresh YPD plates , suspended in sterile water , serially diluted and spotted onto plates . 5 μl of the various dilutions containing 625 , 125 , 25 and 5 cells were deposited for each sample . Replicates were made on YPD plates and YPD plates containing increasing concentrations of HU . For each experiment , one YPD plate without HU was incubated at 37°C . Plates were incubated for three days at 30°C . Synthetic lethality between Pol δ mutant alleles was tested by using crosses , sporulation , tetrad dissection as well as genetic and PCR analyses . Meiotic segregation of a given allele was followed within tetrads by PCR analysis . Primers for pol3-ct: P13 ( GCAGGAGAAAGTAGAACAATT ) and P4187 ( TACGCCTTCTTATGTAGCGC ) ; Primers for pol3-R1043G: P217 ( CATAAAGGCATTATACGATGTCG ) and P4187; Primers for pol31-D304N: P180 ( GATATTATGCCCGGAACCAATA ) and P181 ( TCAATCTTGACCGTCTCTGC ) ; Primers for pol3-FI1002-1003AA: P182 ( GGAGGCTTGATGAGCTTTATT ) and P184 ( CGGTCTCATTAGAATTGCAGC ) ; Primers for pol31-YF327-328AA: P158 ( AGTCCCTAGAATCAGCCGC ) and P159 ( GTCAATCTTGACCGTCTCTGC ) ; Primers for pol32-FF344-345LL: P221 ( GGAACATTGGAAAGCTTGTTG ) and P222 ( TGAGGGACAGAGAAGATTGG ) . The strain CTY10-5d ( MATa , ade2-101 , his3Δ200 , leu2Δ1 , trp1Δ901 , gal4 , gal80 , URA3::lexAop-lacZ ) was used for two-hybrid analysis . Pol31 was fused in frame with the lexA binding domain in plasmid pBTM116 , while the Pol3 C-terminal amino-acids 1032–1097 were fused with the Gal4 activating domain of pACT2 to generate the plasmid pACT2-Pol3-ZnF2 [74] . The Pol3-R1043G , Pol31-YF327-328AA and Pol31-D304N mutations were introduced by site-directed mutagenesis and were confirmed by DNA sequencing . The resulting plasmids were called pACT2-Pol3-R1043G , pBTM116-Pol31-YF and pBTM116-Pol31-D304N , respectively . CTY10-5d was co-transformed with the pACT2 and pBTM116 plasmids that carry WT or mutated Pol3 CTD or Pol31 ( Fig 5B ) . Cells were plated in -Leu -Trp selective medium supplemented with methionine at 22°C or 30°C for 3 to 4 days , and tested for β-galactosidase production in an overlay plate assay [59] . Recombinant S . cerevisiae PCNA with an His-Tag was produced in E coli using the pET28c bacterial expression vector ( Novagen ) as described in [4] and purified on a 5 ml HisTrap column ( GE Healthcare ) . The synthetic peptides containing the PIP-box motifs of S . cerevisiae Pol3 , Pol31 , Pol32 and Msh6 were purchased from Genecust at 95% purity , and the concentrations of the stock peptide solutions were determined by amino acid composition . The interactions between PCNA and the different PIP-box peptides were determined by isothermal titration calorimetry ( ITC ) using a VP-ITC calorimeter ( Microcal ) . Prior to measurements , all solutions were degassed under vacuum . The ITC reaction cell ( vol 1 . 8 mL ) was loaded with 20–25 μM of PCNA solution . The syringe ( 500 μL ) was filled with the different PIP-box peptides at a concentration of 270 μM . Proteins were extensively dialyzed against buffer T ( 20 mM Tris [pH 7 . 5] , 50 mM NaCl , and 20 mM β-mercaptoethanol ) before ITC . The thermodynamic parameters ΔH , N , and Ka were obtained by non-linear least-squares fitting of the experimental data using the single set of independent binding sites model of the Origin software provided with the instrument . The free energy of binding ( ΔG ) and the entropy ( ΔS ) were determined using the classical thermodynamic formula , ΔG = -RT ln ( Ka ) and ΔG = ΔH -TΔS . All binding experiments were performed in duplicate or triplicate at 30°C .
|
Replicative DNA polymerases have the essential role of replicating genomic DNA during the S phase of each cell cycle . DNA replication occurs smoothly and accurately if the DNA to be replicated is undamaged . Conversely , replicative DNA polymerases stall abruptly when they encounter a damaged base on their template . In this case , alternative specialized DNA polymerases are recruited to insert nucleotides at sites of base lesions . However , these translesion polymerases are not processive and they are poorly accurate . Therefore , they need to be tightly regulated . This is achieved by the covalent binding of the small ubiquitin peptide to the polymerase cofactor PCNA that subsequently triggers the recruitment of translesion polymerases at sites of DNA damage . Yet , recruitment of translesion polymerases independently of PCNA ubiquitination also has been documented , although the underlying mechanism is not known . Moreover , this observation makes more difficult to understand the exact role of PCNA ubiquitination . Here , we present strong genetic evidence in Saccharomyces cerevisiae implying that the replicative DNA polymerase δ ( Pol δ ) prevents the recruitment of the translesion polymerases Pol ζ and Rev1 following UV irradiation unless PCNA is ubiquitinated . Thus , the primary role of PCNA ubiquitination would be to allow translesion polymerases to outcompete Pol δ upon DNA damage . In addition , our results led us to propose that translesion polymerases could be recruited independently of PCNA ubiquitination when Pol δ association with PCNA is challenged , for instance at difficult-to-replicate loci .
|
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2017
|
The translesion DNA polymerases Pol ζ and Rev1 are activated independently of PCNA ubiquitination upon UV radiation in mutants of DNA polymerase δ
|
Bone morphogenetic proteins ( BMPs ) belong to the transforming growth factor β ( TGFβ ) superfamily of secreted molecules . BMPs play essential roles in multiple developmental and homeostatic processes in metazoans . Malfunction of the BMP pathway can cause a variety of diseases in humans , including cancer , skeletal disorders and cardiovascular diseases . Identification of factors that ensure proper spatiotemporal control of BMP signaling is critical for understanding how this pathway is regulated . We have used a unique and sensitive genetic screen to identify the plasma membrane-localized tetraspanin TSP-21 as a key new factor in the C . elegans BMP-like “Sma/Mab” signaling pathway that controls body size and postembryonic M lineage development . We showed that TSP-21 acts in the signal-receiving cells and genetically functions at the ligand-receptor level . We further showed that TSP-21 can associate with itself and with two additional tetraspanins , TSP-12 and TSP-14 , which also promote Sma/Mab signaling . TSP-12 and TSP-14 can also associate with SMA-6 , the type I receptor of the Sma/Mab pathway . Finally , we found that glycosphingolipids , major components of the tetraspanin-enriched microdomains , are required for Sma/Mab signaling . Our findings suggest that the tetraspanin-enriched membrane microdomains are important for proper BMP signaling . As tetraspanins have emerged as diagnostic and prognostic markers for tumor progression , and TSP-21 , TSP-12 and TSP-14 are all conserved in humans , we speculate that abnormal BMP signaling due to altered expression or function of certain tetraspanins may be a contributing factor to cancer development .
Bone morphogenetic proteins ( BMPs ) belong to the transforming growth factor β ( TGFβ ) superfamily of secreted polypeptides that regulate a variety of developmental and homeostatic processes [1 , 2] . The TGFβ ligands are synthesized as precursor proteins that can be subsequently processed by proteases [3] . Active TGFβ ligands bind to a heterotetrameric receptor complex composed of type I and type II receptors , leading to the phosphorylation of the type I receptor by the type II receptor . The phosphorylated type I receptor then phosphorylates and activates the receptor-regulated Smads ( R-Smads ) . The activated R-Smads form a complex with common-mediator Smads ( Co-Smads ) and enter the nucleus to regulate downstream gene expression . Malfunction of the TGFβ pathway can result in numerous somatic and hereditary disorders in humans , including various cancers , bone skeletal disorders , and cardiovascular diseases [4–7] . Multiple levels of regulation ensure proper spatiotemporal activity of TGFβ signaling in the correct cellular context [8–11] . Identifying factors involved in modulating the TGFβ pathway and determining their modes of action in vivo will not only provide valuable insights into our understanding of TGFβ signaling , but may also provide therapeutic targets for the many diseases caused by alterations in TGFβ signaling . C . elegans , with its wealth of genetic and molecular tools and its well-defined cell lineage , provides an excellent model system to study the functions and modulation of TGFβ signaling during the development of a whole organism at single-cell resolution . There are at least three TGFβ-related pathways in C . elegans: one that controls dauer formation , one that regulates axon guidance and cell migration , and a third BMP-like “Sma/Mab” pathway that regulates body size and male tail formation , among its multiple functions [12] . The Sma/Mab pathway includes a BMP-like molecule DBL-1 [13 , 14] , the type I receptor SMA-6 [15] , the type II receptor DAF-4 [16] , the R-Smads SMA-2 and SMA-3 , and the Co-Smad SMA-4 [17] . Loss-of-function mutations in any component of this pathway will cause small body size and male tail sensory ray formation defects [12] . We have previously shown that the Sma/Mab pathway also plays a role in patterning the C . elegans postembryonic mesoderm . The hermaphrodite postembryonic mesodermal M lineage arises from a single pluripotent precursor cell , the M mesoblast . During larval development , the M mesoblast divides to produce a dorsal lineage that gives rise to striated bodywall muscles ( BWMs ) and macrophage-like coelomocytes ( CCs ) , as well as a ventral lineage that produces BWMs and the sex muscle precursor cells , the sex myoblasts ( SMs ) ( [18]; Fig 1A and 1C and 1E ) . This dorsoventral asymmetry is regulated by the schnurri homolog sma-9 [19] . Mutations in sma-9 lead to a dorsal-to-ventral fate transformation in the M lineage ( [20]; Fig 1B and 1D and 1F ) . We have shown that mutations in the core components of the Sma/Mab pathway ( Fig 2A ) do not cause any M lineage defect on their own , but they suppress the dorsoventral patterning defects of sma-9 mutants , suggesting that SMA-9 regulates M lineage dorsoventral patterning by antagonizing Sma/Mab signaling [20] . Using this sma-9 M lineage suppression phenotype ( Fig 1A and 1C and 1E ) , we have recently identified two new modulators of the Sma/Mab pathway , the RGM protein DRAG-1 and the DCC/neogenin homolog UNC-40 , which directly associate with each other to positively regulate Sma/Mab signaling [21 , 22 , Fig 2A] . We further showed that their functions in modulating BMP signaling are evolutionarily conserved [22 , 23] . In this study , we describe our identification and analysis of additional sma-9 M lineage phenotype suppressors that function in modulating Sma/Mab signaling . One novel modulator is TSP-21 , which belongs to a family of transmembrane molecules called tetraspanins [24] . Tetraspanins are a distinct family of integral membrane proteins that have four conserved transmembrane ( TM ) domains separated by a small extracellular loop ( EC1 ) , a small intracellular loop ( IL ) and a large extracellular loop ( EC2 ) . They are known to interact with each other to form homo- and hetero-oligomers , and organize membranes into the so-called tetraspanin-enriched microdomains that are also enriched in cholesterol and glycosphingolipids [24–27] . There are 33 tetraspanins in humans and 21 in the C . elegans genome . The in vivo functions of most of these tetraspanins are not well understood . Here we provide evidence that TSP-21 , the C . elegans ortholog of human TSPAN4 , TSPAN9 and CD53 , is localized to the cell membrane and functions positively to regulate Sma/Mab signaling in the signal-receiving cells at the ligand-receptor level . We further show that two additional tetraspanins that belong to the C8 subfamily of tetraspanins , TSP-12 and TSP-14 , also function to promote Sma/Mab signaling . TSP-12 and TSP-14 can physically interact with each other , with TSP-21 , and with the type I receptor of the Sma/Mab pathway , SMA-6 . In addition , we find that mutants defective in glycosphingolipid biosynthesis exhibit defects in Sma/Mab signaling . Collectively , our results provide in vivo evidence supporting the roles of tetraspanins and glycosphingolipid-enriched membrane microdomains in modulating BMP signaling . Finally , we provide evidence that like TSP-12 and TSP-14 , which have been previously shown to function in promoting LIN-12/Notch signaling [28] , TSP-21 also appears to function in LIN-12/Notch signaling in a cell type-specific manner .
We have previously shown that mutations in all core components of the Sma/Mab pathway , but not the TGFβ-like dauer pathway , can suppress the M lineage phenotype of sma-9 ( 0 ) mutants [20] . Here we show that null mutations in unc-129 , which encodes a TGFβ-like molecule important for axon guidance [29] , or null mutations in genes that regulate body size but do not function in the Sma/Mab pathway , such as the β-spectrin gene sma-1 [30] , or the cuticle collagen gene lon-3 [31 , 32] , do not suppress the M lineage phenotype of sma-9 ( 0 ) mutants ( Table 1 ) . Similarly , mutations in the Sma/Mab pathway do not suppress the M lineage defect of let-381 ( RNAi ) , which also leads to a dorsal-to-ventral fate transformation defect in the M lineage by inactivating the FoxF/FoxC transcription factor LET-381 ( [33]; Table 1 ) . In contrast , two deletion alleles of sma-10 , which encodes a conserved , leucine-rich repeats- and immunoglobulin ( Ig ) -like domain ( LRIG ) -containing transmembrane protein that promotes Sma/Mab signaling in regulating body size [34 , Fig 2A] , do suppress the M lineage phenotype of sma-9 ( 0 ) mutants ( Table 1 ) . Motivated by the specificity of the BMP-like Sma/Mab pathway mutants in suppressing the sma-9 M lineage defect and our previous success from the sma-9 suppressor screen in the identification of evolutionarily conserved modulators of BMP signaling , such as DRAG-1/RGM and UNC-40/DCC/neogenin [21 , 22] , we performed a large-scale screen for sma-9 suppressors , named susm ( suppressor of sma-9 ) mutations , with the aim of identifying additional modulators of BMP signaling ( see Materials and Methods ) . Using a combination of linkage analysis , complementation tests and whole genome sequencing ( see Materials and Methods ) , we identified the corresponding genes for 32 susm mutations . As shown in Table 2 , our suppressor screen successfully and specifically identified mutations in all core members and known modulators of the Sma/Mab pathway . Intriguingly , we isolated lon-1 ( jj67 ) as a sma-9 suppressor and showed that an existing , strong loss-of-function allele , lon-1 ( e185 ) , also suppresses the sma-9 M lineage phenotype ( Tables 1 and 2 ) . lon-1 encodes a member of the cysteine-rich secretory protein ( CRISP ) family of proteins and is known to function downstream of , and be negatively regulated by , the Sma/Mab pathway [13 , 35 , Fig 2A] . The suppression of the sma-9 M lineage phenotype by lon-1 mutations and the increased expression of the Sma/Mab responsive reporter RAD-SMAD [21] in lon-1 ( jj67 ) mutants ( Fig 3B ) suggest that LON-1 may exert feedback regulation on Sma/Mab signaling , rather than being strictly regulated by this pathway ( Fig 2A ) . In addition to these factors known to function in Sma/Mab signaling , we also identified a novel factor defined by two non-complementing alleles , jj60 and jj77 ( Table 2 ) . We performed whole genome sequencing ( WGS ) of the novel complementation group that includes jj60 and jj77 to identify the corresponding gene . Four lines of evidence indicate that the corresponding gene is tsp-21 . 1 ) RNAi of tsp-21 suppressed the sma-9 M lineage phenotype ( Table 3 ) . 2 ) Both jj60 and jj77 contain molecular lesions in tsp-21 ( Fig 4A ) : jj60 contains a G-to-A change in nucleotide 1827 , resulting in a Glycine ( G ) to Glutamic acid ( E ) change of amino acid 109 ( G109E ) . jj77 contains a T-to-A change in nucleotide 3327 , resulting in a Valine ( V ) to Glutamic acid ( E ) change of amino acid 236 ( V236E ) . jj77 also carries a 84bp deletion ( between nucleotides 3202 and 3287 ) and a 6bp insertion ( ATCTCT ) , resulting in a 13 amino acid deletion and 2 amino acid insertion between amino acids 209 and 223 . 3 ) A DNA fragment containing the genomic sequence of tsp-21 ( 5kb upstream , entire coding region including introns , and 1 . 7kb downstream sequences for C17G1 . 8 in pJKL1005 , Fig 4B ) rescued the Susm phenotype of jj77 ( Table 3 ) . 4 ) A deletion allele of tsp-21 that we recently obtained , tm6269 , exhibited defects similar to those of jj77 and jj60 animals ( Fig 4B and Table 3 ) . tsp-21 encodes a conserved but previously unstudied 301 amino acid transmembrane protein of the tetraspanin family , TSP-21 ( Fig 4C ) . Based on the number of cysteine ( C ) residues in the large EC2 loop , tetraspanins can be classified into three groups , C4 , C6 and C8 [36 , 37] . TSP-21 belongs to the C6a group , with the following configuration of cysteine residues in EC2: CCG——CC——C——C ( Fig 4C ) . The closest vertebrate homologs of TSP-21 are TSPAN4 , TSPAN9 and CD53 ( Figs 4C and S1 ) . These proteins , except for CD53 , share the conserved C6a configuration in the EC2 loop as well as conserved transmembrane ( TM ) domains ( Fig 4C ) . The G109E mutation in jj60 affects the last residue of TM3 ( Fig 4A and 4C ) , and likely results in the production of a partial loss-of-function TSP-21 protein . The deleted residues of TSP-21 in jj77 mutants include one of the six highly conserved cysteine residues in EC2 ( Fig 4C ) . jj77 also contains a missense mutation in a conserved residue in TM4 ( V236E , Fig 4 ) , and is therefore likely a strong loss-of-function , or likely null , allele of tsp-21 . We have therefore used jj77 for all our subsequent analyses . Because our sma-9 suppressor screen is highly specific in identifying components of the BMP-like Sma/Mab pathway , we examined tsp-21 ( jj77 ) mutants for any additional Sma/Mab signaling defects , such as body size , male tail patterning and expression of RAD-SMAD , a Sma/Mab signaling reporter that we previously generated [21] . tsp-21 ( jj77 ) animals are smaller than wild-type animals ( Fig 2B–2E ) and exhibited reduced RAD-SMAD reporter expression ( Fig 3 ) . Unlike mutants in core members of the Sma/Mab pathway , tsp-21 ( jj77 ) mutant males can mate and they do not exhibit any significant male tail patterning defects ( based on examining 100 sides of tsp-21 ( jj77 ) male tails ) . These tsp-21 phenotypes are very similar to those exhibited by null mutants in two previously identified Sma/Mab pathway modulators , drag-1 and unc-40 [21 , 22] . Furthermore , like mutants in other members of the Sma/Mab pathway [20–22] , tsp-21 ( jj77 ) mutants exhibited no M lineage defects ( Table 3 ) . Finally , tsp-21 ( jj77 ) mutants showed no dauer defects , and tsp-21 exhibited no genetic interaction with daf-1 and daf-7 , two genes functioning in the TGFβ-like dauer pathway ( [12]; S1 Table ) . Collectively , these phenotypic analyses suggest that TSP-21 positively modulates the BMP-like Sma/Mab pathway , but does not appear to play a role in the TGFβ-like dauer pathway . The smaller body size of tsp-21 ( jj77 ) mutants allowed us to use genetic epistasis to determine where in the Sma/Mab pathway TSP-21 functions . We generated double mutants between tsp-21 ( jj77 ) and null mutations in various Sma/Mab pathway components ( Fig 2A ) and measured their body sizes . As shown in Fig 2E , dbl-1 ( wk70 ) ; tsp-21 ( jj77 ) and sma-3 ( jj3 ) ; tsp-21 ( jj77 ) double mutants were as small as dbl-1 ( wk70 ) and sma-3 ( jj3 ) single mutants , respectively . These observations are consistent with TSP-21 functioning in the Sma/Mab pathway in regulating body size . lon-1 ( jj67 ) ; tsp-21 ( jj77 ) double mutants were as long as lon-1 ( jj67 ) single mutants , while lon-2 ( e678 ) tsp-21 ( jj77 ) double mutants showed intermediate body size between lon-2 ( e678 ) and tsp-21 ( jj77 ) single mutants ( Fig 2E ) , suggesting that tsp-21 is likely to function upstream of lon-1 , but in parallel to lon-2 , in the Sma/Mab pathway . drag-1 ( jj4 ) ; tsp-21 ( jj77 ) and unc-40 ( e1430 ) ; tsp-21 ( jj77 ) double mutants , or drag-1 ( jj4 ) unc-40 ( e1430 ) ; tsp-21 ( jj77 ) triple mutants were significantly smaller than each respective single mutant ( Fig 2E ) , which is consistent with tsp-21 functioning in parallel to drag-1 and unc-40 . Taken together , these results indicate that TSP-21 functions at the ligand-receptor level to positively modulate Sma/Mab signaling . To determine how TSP-21 functions in the Sma/Mab pathway , we examined the expression and localization pattern of TSP-21 . We first generated integrated transgenic lines carrying a translational TSP-21::GFP fusion ( pJKL1004 , see Materials and Methods ) that contains the entire tsp-21 genomic region including 5kb 5’ sequences and 1 . 7kb 3’ sequences ( Fig 4B ) . This translational fusion rescued the Susm phenotypes of tsp-21 ( jj77 ) mutants ( Table 3 ) . Subsequently we generated the same fusion in the endogenous tsp-21 locus via CRISPR-Cas9 mediated homologous recombination ( see Materials and Methods ) . Both reporters showed that TSP-21::GFP is plasma membrane-localized and is expressed in a wide variety of somatic cell types , including the pharynx , intestine and hypodermis starting in embryos after the 100 cell stage ( Fig 5A–5C at mid-embryogenesis ) and peaking in L1 and L2 larvae ( Fig 5D–5L ) . The TSP-21::GFP signal in these tissues decreases in late larval and adult stage animals . TSP-21::GFP is also present at the surface of M lineage cells from the 1-M stage to the 16-M stage ( Fig 5S–5Z ) . In addition to expression in these tissues , the two TSP-21::GFP lines generated via the CRISPR-Cas9 system also showed GFP expression in the somatic gonad and vulva in L2-L4 larvae and adults ( Fig 5M–5O ) , as well as in the rectal epithelium in L4 larvae ( Fig 5P–5R ) . These observations suggest that the enhancer elements for tsp-21 expression in the somatic gonad , the vulva and the rectal epithelium lie outside of the 10 . 5kb tsp-21 genomic region included in pJKL1004 . We noticed that TSP-21::GFP is enriched in the basolateral side of intestinal cells while being absent from their apical sides ( Fig 5G–5I ) . A similar localization pattern has been reported for the type I receptor SMA-6 and the type II receptor DAF-4 [38] . In addition , while TSP-21::GFP in the M lineage cells is primarily plasma membrane localized , there is also a significant intracellular distribution of TSP-21::GFP in the M mesoblast ( Fig 5S and 5W ) . At present , the functional significance of either the asymmetric localization of TSP-21::GFP in intestinal cells or its intracellular localization in the M cell is not clear . The Sma/Mab pathway is known to function in the hypodermal cells to regulate body size and in the M lineage to regulate M lineage development . We next tested whether TSP-21 functions in these cell types to exert its role in Sma/Mab signaling . Using cell-type-specific promoters to drive tsp-21 expression , we found that forced expression of tsp-21 cDNA in hypodermal cells , but not in pharyngeal or intestinal cells , rescued the small body size phenotype of tsp-21 ( jj77 ) mutants ( Table 4 ) . Similarly , forced expression of tsp-21 cDNA in the M lineage also rescued the Susm phenotype of tsp-21 ( jj77 ) mutants ( Table 3 ) . Thus TSP-21 functions autonomously in the signal-receiving cells to promote Sma/Mab signaling . There are 21 tetraspanins in C . elegans . Our finding that TSP-21 functions in Sma/Mab signaling prompted us to ask whether other tetraspanins might also function in the Sma/Mab pathway . We therefore screened through the remaining 20 tetraspanin tsp genes by RNAi injection , testing whether any of them are involved in Sma/Mab signaling using the sma-9 suppression assay . Only tsp-12 ( RNAi ) resulted in a low penetrance ( 9 . 4% , n = 767 ) Susm phenotype ( Table 5 ) . We then tested a deletion allele of tsp-12 , ok239 , and found that it also exhibited the Susm phenotype ( Table 5 ) , suggesting that the tetraspanin TSP-12 also plays a role in modulating Sma/Mab signaling . Dunn and colleagues [28] have previously reported that TSP-12 and TSP-14 function redundantly to promote Notch signaling . We asked whether tsp-14 and tsp-12 might also share a redundant role in the Sma/Mab pathway , and found that tsp-14 ( RNAi ) enhanced the penetrance of the Susm phenotype of the tsp-12 ( ok239 ) mutation ( Table 5 ) . This effect appears to be specific since tsp-10 ( RNAi ) failed to enhance the penetrance of the Susm phenotype of the tsp-12 ( ok239 ) mutation ( Table 5 ) . Thus , TSP-12 and TSP-14 also function redundantly to promote Sma/Mab signaling , in addition to their role in Notch signaling . The dual functions of TSP-12 and TSP-14 in both the Notch and the Sma/Mab signaling pathways prompted us to examine whether TSP-21 also functions in the Notch signaling pathway . The LIN-12/Notch signaling pathway is known to function in the M lineage to promote the ventral fate: loss of LIN-12/Notch function results in a ventral-to-dorsal fate transformation in the M lineage , namely the loss of M-derived SMs and the gain of M-derived CCs ( [39 , 40]; S2 Fig ) . tsp-21 ( jj77 ) single mutants exhibit no M lineage defects . We therefore examined whether tsp-21 ( jj77 ) could enhance the M lineage defect of the lin-12 temperature sensitive , partial loss-of-function allele lin-12 ( n676n930ts ) by scoring the number of M-derived CCs . As shown in Table 6 , tsp-21 ( jj77 ) significantly enhanced the M lineage defect of lin-12 ( n676n930ts ) at both 20°C and 22°C , suggesting that TSP-21 functions to promote LIN-12/Notch signaling in the M lineage . However , tsp-21 ( jj77 ) failed to enhance the sterility and embryonic lethality of bn18ts , a mutation in the second Notch receptor gene in C . elegans , glp-1 [41] . The lack of genetic interaction between tsp-21 ( jj77 ) and glp-1 ( bn18 ) is consistent with the absence of TSP-21::GFP expression in the germline and early embryo , as described above . Tetraspanins often associate with each other and with other membrane or membrane-associated proteins to organize membranes into tetraspanin-enriched microdomains [24–26] . Our finding that in addition to TSP-21 , TSP-12 and TSP-14 also function in promoting Sma/Mab signaling suggested that these tetraspanins might interact with each other . We tested this hypothesis by using the mating-based split-ubiquitin system ( mbSUS , [42] ) in budding yeast . The mbSUS is based on the observation that a full-length ubiquitin can be reconstituted when the N-terminal ubiquitin domain ( Nub ) and the C-terminal ubiquitin domain ( Cub ) are brought into close proximity [43 , 44] . This system can be used to identify potential interactions between full-length membrane proteins or between a membrane protein and a soluble protein: a mutant form of Nub , NubG , that has reduced affinity for Cub , can only reconstitute with Cub via two interacting proteins . The reconstituted ubiquitin will direct ubiquitin-specific proteases to liberate PLV ( protein A , LexA and VP16 ) from Cub , which then enters the nucleus and activates transcription of reporter genes . We generated TSP-Cub fusions and Nub-TSP or TSP-Nub fusions ( see Materials and Methods , and S2 Table for a list of the plasmids generated ) , and tested pairwise interactions among the three tetraspanins , as well as interactions between these tetraspanins and the type I and type II receptors SMA-6 and DAF-4 , respectively . Results from these experiments are summarized in Fig 6 . TSP-12-Cub appeared to auto-activate reporter expression , while the TSP-14-Cub was not detectable on western blots ( see Materials and Methods ) . For the remaining three Cub fusions ( TSP-21 , SMA-6 and DAF-4 ) , we found that TSP-21 can associate with itself , as well as with TSP-12 and TSP-14 ( Fig 6 ) . In addition , SMA-6 can associate with both TSP-12 and TSP-14 , but not TSP-21 . We also detected a very weak interaction between DAF-4 and TSP-14 ( Fig 6 ) . The use of multiple positive and negative controls in these experiments ( see Materials and Methods , and Fig 6 ) indicated that the observed interactions are highly specific . For example , TSP-21 did not show any interaction with the C . elegans LKB homolog PAR-4 ( [45]; Fig 6 ) , or the plant potassium channel KAT1 ( [42]; Fig 6 ) , or with the C . elegans ABC transporter HMT-1 [46] . Except for the weak DAF-4-TSP-14 interaction , the other observed interactions all appeared to be particularly strong , as yeast growth on SC-Trp , -Leu , -Ade , -His , -Ura , -Met plates supplemented with 0 . 3mM of methionine was detectable only 2 days after streaking the mated yeast . Thus , TSP-21 can form both homo-oligomers and heteromeric complexes with TSP-12 and TSP-14 . These findings are consistent with our genetic evidence that all three tetraspanins function to promote Sma/Mab signaling . The strong interactions between SMA-6 and TSP-12 and TSP-14 suggest that these tetraspanins might function by directly recruiting the receptor molecules to specific membrane microdomains . Tetraspanin-enriched microdomains are also enriched in cholesterol and glycosphingolipids [24–26] . We therefore tested whether cholesterol and/or glycosphingolipids are required for Sma/Mab signal transduction . Our results suggest that Sma/Mab activity is influenced by glycosphingolipids but not cholesterol . C . elegans worm survival requires exogenous cholesterol [47 , 48] . In the lab , worms are normally fed with E . coli bacteria on agar plates supplemented with 5μg/mL cholesterol [49] . Using a method that can lead to nearly complete cholesterol depletion ( [50 , 51] and see Materials and Methods ) , we grew L1 or L4 worms on cholesterol-depleted plates and scored their phenotypes or their progeny’s phenotype , respectively , at the adult stage . We found no suppression of the M lineage phenotype when sma-9 ( cc604 ) worms were grown on cholesterol-depleted media , even though the worms were sterile , a known phenotype resulting from cholesterol depletion [47 , 48] . Thus cholesterol does not seem to be essential for Sma/Mab signaling . To determine the requirement of glycosphingolipids in Sma/Mab signaling , we generated double mutants between sma-9 ( cc604 ) and mutations that reduce or eliminate the activity of enzymes involved in glycosphingolipid biosynthesis [52] , S3 Fig ) , and examined their Susm phenotype . As shown in Table 7 , mutations in cgt-3 and bre-5 partially suppressed the sma-9 M lineage phenotype . cgt-3 encodes the ceramide glucosyltransferase that converts ceramide to glucosylceramide , a precursor of complex glycosphingolipids [53 , 54] . Previous work has shown that CGT-3 is the major enzyme among the three worm CGT proteins [54] . We found that a deletion allele of cgt-3 , ok2877 , which deletes most of the coding exons of cgt-3 , resulted in a late L1 or early L2 larval arrest and a partial suppression of the sma-9 ( cc604 ) M lineage defects ( Table 7 ) . cgt-3 ( ok2877 ) mutants exhibited additional defects in Sma/Mab signaling: the relative fluorescence intensity of the RAD-SMAD reporter in cgt-3 ( ok2877 ) mutants is only 58% of that in stage-matched wild-type animals ( see Materials and Methods ) and cgt-3 ( ok2877 ) mutants exhibited a smaller body size compared to stage-matched wild-type control animals ( 72% of wild-type body length , n = 23 ) . We also observed a low penetrance of the Susm phenotype in ye17 , an allele of bre-5 that encodes a β-1 , 3-galactosyltransferease involved in glycosphingolipid biosynthesis ( Table 7 , [55 , 56] ) . Taken together , our data suggest that glycosphingolipids are required for Sma/Mab signaling . The lack of a Susm phenotype for the other mutations affecting glycosphingolipid biosynthesis ( Table 7 ) may be because many of them are partial loss-of-function alleles , since null mutations in many of these genes result in lethality [52] . Alternatively , proper Sma/Mab signaling may require specific type ( s ) of glycosphingolipids . cgt-3 is widely expressed in multiple cell types in C . elegans [53 , 54] . We tested whether cgt-3 , and therefore glycosphingolipids , are required in the signal-receiving cells for proper Sma/Mab signaling . Expression of cgt-3 in the M lineage using the hlh-8 promoter partially , but significantly , rescued the Susm phenotype of cgt-3 ( ok2877 ) mutants ( Table 7 ) , suggesting that proper Sma/Mab signaling requires glycosphingolipids in the signal-receiving cells . The lack of complete rescue suggests that glycosphingolipids are also required outside of the signal-receiving cells to promote Sma/Mab signaling . During the course of our study , we observed that both cgt-3 ( ok2877 ) and bre-5 ( ye17 ) single mutants exhibited a low penetrance M lineage phenotype like that of a lin-12 ( lf ) mutant: extra M-derived CCs due to the fate transformation of M-derived SMs to CCs ( [39 , 40]; Table 8 and S2 Fig ) . We further found that cgt-3 ( ok2877 ) enhanced the penetrance of the M lineage defects of a hypomorphic lin-12 temperature sensitive allele , n676n930 , at a semi-permissive temperature ( Table 8 ) . These observations are consistent with previous findings by Katic and colleagues [57] showing that enzymes required for glycosphingolipid biosynthesis , such as BRE-5 , are required for promoting LIN-12/Notch signaling . The requirement of glycosphingolipids in LIN-12/Notch signaling appears to be distinct from their requirement in Sma/Mab signaling . Mutations in the Sma/Mab pathway fully restore the sma-9 ( 0 ) M lineage phenotype back to that of wild-type animals ( [20–22 , 40]; S2 Fig ) . However , lin-12 ( 0 ) ; sma-9 ( 0 ) double mutants exhibit a reversal of the M lineage dorsoventral polarity , so that the double mutants have 2 SMs born on the dorsal side and 2 M-derived CCs located on the ventral side ( [39 , 40]; S2 Fig ) . Careful examination of the position of the M-derived CCs in cgt-3 ( ok2877 ) ;sma-9 ( cc604 ) and bre-5 ( ye17 ) ;sma-9 ( cc604 ) mutants showed that a majority of the double mutant animals have their M-derived CCs located on the dorsal side ( S3 Table ) , indicating a suppression rather than a reversal of polarity . Taken together , our results support the notion that glycosphingolipids are required for both LIN-12/Notch and Sma/Mab signaling .
In this study , we identified TSP-21 , a C6a class tetraspanin , as a key factor promoting the BMP-like Sma/Mab signaling in C . elegans . tsp-21 mutants exhibit small body size and Susm phenotypes similar to that shown by mutants in core Sma/Mab pathway components . The TSP-21 protein is localized to the plasma membrane , and tsp-21 is expressed and functions in the signal-receiving cells at the ligand-receptor level to promote Sma/Mab signaling . We found that among the remaining 20 C . elegans tetraspanins , TSP-12 and TSP-14 function redundantly to also promote Sma/Mab signaling . How do these three tetraspanins function to promote Sma/Mab signaling ? We envision two possible , non-mutually exclusive , scenarios . In the first scenario , the three tetraspanins might promote clustering of the receptor complexes or the ligand-receptor complexes to modulate Sma/Mab signaling . Tetraspanins are known to homo- and hetero-oligomerize to organize membranes into tetraspanin-enriched microdomains , which are also enriched in tetraspanin-associated proteins [24–26] . Previous work has shown that in mouse , TSPAN12 promotes Norrin/β-catenin signaling by enhancing clustering of the Norrin receptor FZD4 [58 , 59] . In particular , TSPAN12 and Norrin can each enhance FZD4 clustering but work together cooperatively to further increase the clustering of the ligand-receptor complex to promote Norrin/β-catenin signaling [58] . We have shown that C . elegans TSP-12 , -14 and -21 can interact with each other in yeast and that both TSP-12 and TSP-14 can interact with the type I receptor SMA-6 . In addition , we found that glycosphingolipids , which are enriched in tetraspanin-enriched microdomains , are also required for proper Sma/Mab signaling . These findings suggest that TSP-21 , TSP-12 and TSP-14 may function by recruiting the receptor complex , or the ligand-receptor complex , to glycosphingolipid-enriched membrane microdomains containing TSP-21-TSP-12-TSP-14 , thereby increasing the local concentration of the receptors , or the ligand-receptor complexes , to promote Sma/Mab signaling ( Fig 7 ) . Supporting this model , SMA-6 , DAF-4 and TSP-21 are all localized to the basolateral membranes of the polarized intestinal cells ( [38]; this work ) . We envision that several previously identified positive modulators of the Sma/Mab pathway , including DRAG-1/RGM , UNC-40/neogenin , and SMA-10/LRIG , might be localized in these microdomains as well , as all three proteins are plasma membrane-localized , are expressed and function in the signal-receiving cells , and interact with the ligand and the receptors ( for DRAG-1 ) , or the receptors ( for SMA-10 ) , or with each other ( for DRAG-1 and UNC-40 ) [21 , 22 , 34] . Further biochemical and cell biological experiments are needed to determine the presence and subcellular localization of TSP-21-TSP-12-TSP-14-containing membrane microdomains , whether the Sma/Mab pathway receptors and modulators are indeed localized to these microdomains , and what other factors are also present there . Alternatively , but not mutually exclusively , the three tetraspanins might be involved in the trafficking of essential Sma/Mab pathway components . Tetraspanins have been found to be present in the plasma membrane or various types of intracellular membranous organelles , and multiple tetraspanins are known to regulate the processing and trafficking of associated proteins [60] . In C . elegans , TSP-12 and TSP-14 have previously been shown to function redundantly in promoting Notch signaling [28] . Their Drosophila and mammalian homologs , the TspanC8 tetraspanins , interact with the ADAM ( a disintegrin and metalloprotease ) protease ADAM10 to promote its maturation and trafficking to the cell surface , which in turn promotes Notch signaling [61–63] . TSP-12 and TSP-14 may function in a similar manner in promoting Sma/Mab signaling . Since both TSP-12 and TSP-14 can bind to the type I receptor SMA-6 in yeast , they may promote Sma/Mab signaling by regulating the trafficking of SMA-6 ( Fig 7 ) , and/or other players in the Sma/Mab pathway . Further work is needed to test this hypothesis . Since the role of TspanC8 tetraspanins in promoting Notch signaling is evolutionarily conserved [61–63] , it will be interesting to determine whether the role of TspanC8 tetraspanins in modulating BMP signaling is also evolutionarily conserved , and whether these tetraspanins function in a similar manner in promoting both BMP and Notch signaling . Using C . elegans as a model , Gleason and colleagues recently showed that the type I receptor SMA-6 and the type II receptor DAF-4 utilize distinct mechanisms for their intracellular recycling , providing physiological evidence supporting the roles of endocytosis and intracellular trafficking in regulating BMP signaling [38] . In light of the roles of multiple tetraspanins in regulating the processing and trafficking of associated proteins [60] , our findings , together with that of Gleason and colleagues [38] , highlight the usefulness of C . elegans as a model system in identifying cell biological mechanisms that regulate BMP signaling . The family of tetraspanin proteins is large: there are 21 tetraspanins in C . elegans and 33 tetraspanins in humans . Recent studies have implicated tetraspanins in multiple diseases and physiological processes in humans [60] . In particular , several tetraspanins , such as CD151 [64] , TSPAN12 [65] , and TSPAN8 [66] , among others , have been implicated in cancer initiation , progression and metastasis in mammals . These and other tetraspanins have emerged as diagnostic and prognostic markers , and possible therapeutic targets , for tumor progression ( for reviews , see [27 , 67] ) . However , the mechanism by which the mis-regulation of these tetraspanins contributes to cancer is not fully understood [27 , 67] . It is well known that mis-regulation of TGFβ signaling contributes to cancer initiation and progression [6 , 68] . CD151 is the only tetraspanin whose role in cancer has been directly linked to altered TGFβ signaling [69] . Sadej and colleagues showed that CD151 is required for TGFβ1-induced proliferation and scattering of breast cancer cell line MDA-MB-231 through regulating TGFβ-induced p38 phosphorylation , rather than canonical TGFβ-induced Smad phosphorylation . Furthermore , this function of CD151 in TGFβ signaling requires its interaction with the integrins [69] . How CD151-integrin interaction regulates TGFβ-induced p38 phosphorylation is not clear . Recently a study on the tetraspanin-interacting protein EWI-2 indirectly implicates two other tetraspanins , CD9 and CD81 , in regulating TGFβ signaling in melanoma growth and metastasis [70] . But the detailed mechanism on how these two tetraspanins regulate TGFβ signaling is not known . We have provided a direct in vivo link between BMP signaling and three tetraspanins , TSP-21 , TSP-12 and TSP-14 , in living animals using C . elegans as a model . Our genetic epistasis results showed that TSP-21 acts through SMA-3 , one of the R-Smads in the canonical BMP-like Sma/Mab signaling pathway ( Fig 2E ) . Due to the embryonic arrest of null mutants in the C . elegans integrin genes , we could not determine whether the function of TSP-21 in Sma/Mab signaling is dependent on integrins . We have found that strong-loss-of function mutations in one of the two C . elegans genes encoding the α subunit of integrin , ina-1 ( gm39 ) and ina-1 ( gm144 ) [71] , did not exhibit any Susm phenotype ( n = 53 for gm39 , and n = 109 for gm144 ) . But we cannot rule out the possibility that in these mutants residual ina-1 function or function of pat-2 , another gene encoding the α subunit of integrin [72] is sufficient to mediate Sma/Mab signaling . TSP-21 is orthologous to human TSPAN4 , TSPAN9 and CD53 , but is much more distantly related to CD151 ( whose C . elegans ortholog is TSP-17; S1 Fig ) . It is therefore possible that the differences between CD151 and TSP-21 in regulating TGFβ signaling are due to intrinsic biochemical differences between the two types of proteins . Alternatively , since TSP-21 regulates a BMP-like Sma/Mab signaling pathway , it is likely that tetraspanins can regulate both TGFβ signaling and BMP signaling , but via distinct downstream effectors . Interestingly , each of the three human orthologs of TSP-21 ( TSPAN4 , TSPAN9 and CD53 ) , as well as two out of the six human orthologs of TSP-12 and TSP-14 ( TSPAN10 and TSPAN33 ) , are expressed at elevated levels in certain cancer cell lines or tumors [73–75] In addition , one human ortholog of TSP-12 and TSP-14 ( TSPAN14 ) is genetically altered in non-small-cell lung cancer [76] . However , the functional significance of their overexpression or mutation in human cancers is not fully understood . We propose that the involvement of these tetraspanins in cancer may be partially due to their role in modulating the activity of TGFβ and/or BMP signaling . Previous genetic studies in C . elegans have led to the identification of key players in BMP signaling ( for example , [16 , 17] ) . A screen based on the body size phenotype has also been fruitful in identifying factors involved in modulating Sma/Mab signaling , such as SMA-10/LRIG [32] and LON-2/glypican [34 , 77] . Potential modulators of the Sma/Mab pathway may also exist among a collection of mutants with a small body size phenotype [78] . However , it may be difficult to identify the genes for which mutations produce only a subtle effect on body size , such as tsp-21 ( jj77 ) . Furthermore , since genes not functioning in the Sma/Mab pathway also regulate body size ( for example , [30–32 , 79] ) , not all mutations affecting body size will identify factors specifically functioning in the Sma/Mab pathway . The sma-9 suppressor screen appears to be a highly specific and sensitive means to identify new components of the Sma/Mab pathway: ( 1 ) Mutations in all ( except for crm-1 , see Table 1 ) previously identified Sma/Mab pathway members suppress the sma-9 M lineage phenotype ( Table 1 and Table 2 ) . In general , partial loss-of-function alleles for a given gene exhibited lower penetrance of the Susm phenotype compared to putative null alleles ( Table 2 ) , demonstrating that the suppression of the sma-9 M lineage phenotype is highly sensitive to altered levels of Sma/Mab signaling . ( 2 ) Mutations in other signaling pathways , such as the dauer pathway or the Wnt pathway , or mutations that exclusively affect body size without affecting Sma/Mab signaling , do not suppress the M lineage phenotype of the sma-9 mutant ( [20]; Table 1 ) . ( 3 ) Using this screen , we have identified three evolutionarily conserved modulators of the Sma/Mab pathway , DRAG-1/RGM [21] , UNC-40/neogenin/DCC [22] , and TSP-21/TSPAN4 , 9 ( this study ) . Additional modulators of this pathway probably exist , as our screen has only recovered single alleles of several genes known to function in Sma/Mab signaling and is , therefore , unlikely to be genetically saturated ( Table 2 ) . In summary , we have developed a highly specific and sensitive way to identify new modulators of the BMP pathway in C . elegans . This genetic approach has confirmed known regulators and identified novel players . Because of the high degree of conservation of the BMP pathway , the factors that we identify in our screen and the mode of their action that we decipher in C . elegans will be broadly relevant in understanding modulation of BMP signaling in other metazoans , including humans .
Strains were grown using standard culture conditions , as described by Brenner [49] . Analyses were performed at 20°C , unless otherwise noted . Cholesterol depletion conditions were following those described in Merris et al . [80] by replacing agar with agarose , and by growing bacteria OP50 and C . elegans worms on defined media , which contains 3 . 5mM Tris . HCl , 2mM Tris , 34mM NaCl , and 3 . 1g/L of ether-extracted peptone . Eggs or L4 hermaphrodite animals were placed on cholesterol-depleted plates and the resulting adult animals were scored for M lineage phenotypes . The following mutations and integrated transgenes were used: Linkage group I ( LG I ) : drag-1 ( jj4 ) , arIs37 ( secreted CC::gfp ) , bre-4 ( ok3167 ) , bre-5 ( ye17 ) ; LG II: sma-6 ( e1482 ) , pod-2 ( ye60 ) , cgt-3 ( ok2877 ) /mIn1[mIs14 dpy-10 ( e128 ) ] , jjIs2437[CXTim50 . 19[pCXT51 ( 5*RLR::deleted pes-10p::gfp ) + LiuFD61 ( mec-7p::rfp ) ] , sptl-1 ( ok1693 ) ; LG III: daf-4 ( m63 ) , daf-7 ( m62 ) , sma-2 ( e502 ) , sma-3 ( e491 ) , sma-4 ( e729 ) , lon-1 ( e185 ) , cup-5 ( ar465 ) , ina-1 ( gm144 ) , ina-1 ( gm39 ) , bre-2 ( ye31 ) , bre-3 ( ye26 ) , bre-3 ( ye28 ) , lin-12 ( n676n930ts ) , hT2[qIs48] , ccIs4438[intrinsic CC::gfp]; LG IV: daf-1 ( m40 ) , daf-1 ( m213 ) , fat-2 ( wa17 ) , fat-3 ( wa22 ) , fat-6 ( tm331 ) , tsp-12 ( ok239 ) , nT1[qIs51]; LG V: dbl-1 ( wk70 ) , fat-7 ( wa36 ) , sma-10 ( wk89 ) , sma-10 ( ok2224 ) , sma-1 ( ru18 ) , lon-3 ( ct417 ) , crm-1 ( tm2218 ) , him-5 ( e1467 ) , bre-1 ( ye4 ) , bre-5 ( ye17 ) , cgt-1 ( ok1045 ) , acs-1 ( gk3066 ) V/nT1[qIs51]IV;V; LG X: lon-2 ( e678 ) , tsp-21 ( tm6269 ) , sma-9 ( cc604 ) , jjIs2433[RAD-SMAD: CXTim50 . 1[pCXT51 ( 5*RLR::deleted pes-10p::gfp ) + LiuFD61 ( mec-7p::rfp ) ]] . tsp-21 and sma-9 are located 0 . 79 map unit apart from each other on the X chromosome . We therefore separated the tsp-21 ( jj77 ) mutation from sma-9 ( cc604 ) via recombination . Specifically , progeny from tsp-21 ( jj77 ) sma-9 ( cc604 ) /+ + heterozygous parents were scored for the number of CCs . Animals with 6 CCs ( jj77 cc604/+ + or + +/+ + or jj77 cc604/jj77 + ) were genotyped for jj77 homozygosity by PCR . jj77 cc604/jj77 + animals were selected and their progeny were further genotyped by sequencing the sma-9 gene in order to obtain jj77 +/jj77 + animals . Four independent recombinants were obtained , #570 , #778 , #898 and #954 . Each recombinant was then outcrossed with N2 three more times before further phenotypic analysis . All four recombinants behaved similarly regarding body size , RAD-SMAD and male tail patterning phenotypes . The lon-2 ( e678 ) tsp-21 ( jj77 ) double mutant was generated from a lon-2 ( e678 ) egl-15 ( n484 ) /tsp-21 ( jj77 ) heterozygous worms by identifying Lon-non-Egl recombinants , and scoring for the presence of the tsp-21 ( jj77 ) and the lon-2 ( e678 ) mutations by PCR genotyping . let-381 ( RNAi ) was performed via feeding following the protocol described in [33] . Other RNAi experiments were performed by injection . In general , gene specific fragments were amplified using RNAi clones from the Ahringer library [81] or the Vidal library [82] , or using N2 genomic DNA as template . dsRNAs were generated using the T7 Ribomax RNA Production System ( Promega ) and injected into gravid adult hermaphrodite animals of specific genotypes carrying CC::gfp . The resulting progeny were scored at the adult stage for the number of CCs . arIs37 ( secreted CC::gfp ) I; cup-5 ( ar465 ) III; sma-9 ( cc604 ) X animals lacking M-derived coelomocytes ( having a total of 4 CCs ) were treated with 50 mM ethyl methanesulfonate ( EMS ) . Individual F1 animals were picked to 3F1s per plate and their combined F2 progeny were screened for the restoration of M lineage-derived coelomocytes ( having a total of 5–6 CCs ) by direct visual examination using a fluorescence stereomicroscope . Plates that segregated 5–25% of animals with 6 CCs were kept for further analysis , including determining whether the mutations bred true , the degree of suppression for each suppressor mutation when homozygous and whether the mutations are dominant or recessive . By screening through 5 , 300 haploid genomes using the above method , we isolated 37 true-breeding sma-9 suppressors , named susm ( suppressor of sma-9 ) mutations ( jj49-jj85 , Table 2 ) . Four of these , jj68 , jj80 , jj81 and jj84 showed a relatively low degree of suppression ( near 30% , Table 2 ) , and were not further characterized in this work . jj58 might be a dominant mutation and was not further analyzed . All of the remaining susm alleles appear to be recessive , single locus mutations , although some suppressors exhibited partial dominance in their Susm phenotype ( Tables 1 and 2 ) . The suppressor mutations were then mapped to chromosome X or chromosome III based on their linkage to sma-9 ( cc604 ) X or to cup-5 ( ar465 ) III . Further complementation tests were carried out between each suppressor mutation and mutations in each known members of the Sma/Mab pathway , and between different suppressor mutations that did not affect known genes in the Sma/Mab pathway . LW0214 , which has arIs37 ( secreted CC::gfp ) I and sma-9 ( cc604 ) X introgressed into the CB4856 Hawaiian strain by 6x backcrossing , was used for mapping the sma-9 suppressors via snip-SNP mapping [83] and whole genome sequencing ( WGS ) [84] . LW0214 was tested using a panel of SNP markers and subsequently by WGS , and found to contain CB4856 SNPs for all six chromosomes except for the following regions that still contain N2 SNP markers: chromosome I—from the left end to -12 and from +24 to the right end; chromosome II—from the left end to -18; and chromosome X—between +1 . 73 and +11 . Snip-SNP markers used were described in Wicks et al . [83] and Davis et al . [85] . For the sma-9 suppressor mutations that appeared to affect known genes in the Sma/Mab pathway , either by complementation tests , or by whole genome sequencing ( WGS , see below ) , their molecular lesions were identified by sequencing PCR products spanning the entire genomic regions of the corresponding genes , which include dbl-1 , daf-4 , sma-6 , sma-2 , sma-3 , sma-4 , lon-1 , sma-10 and unc-40 . For jj69 that contains a single base pair change in the upstream regulatory region of sma-6 , a plasmid pJKL1060 , which contains 3kb of upstream sequences , the genomic coding region and 2kb of downstream sequences of sma-6 , was used to rescue the Susm phenotype of jj69 . Direct WGS of the homozygous suppressor mutant DNA was performed for some sma-9 suppressors . For others , the suppressors were simultaneously mapped and identified using the SNP-WGS method of Doitsidou et al . [84] . For the SNP-WGS method , each sma-9; suppressor mutant was crossed with LW0214 , which has sma-9 introgressed into the polymorphic Hawaiian strain CB4856 ( described above ) . Between 36 and 59 F2 progeny that were homozygous for both sma-9 and the suppressor mutation were collected . F3 generation worms from these F2 progeny were pooled for DNA extraction and library construction . Worm genomic DNA was prepared using the Qiagen Gentra Puregene Kit . 5μg of genomic DNA was used to prepare the sequencing library using the NEBNext DNA Sample Prep Master Mix Set 1 . Single-end 50bp short-read ( 51 cycle ) sequencing was performed on the HiSeq 2000 instrument ( Illumina ) , yielding 38 ~ 78 million reads ( 20 ~ 41 fold coverage ) per sample . For direct WGS ( jj58 , jj60 , jj61 , jj71 , jj77 ) , data analysis was done using the MAQGene platform [86 , 87] with the default setting . SNP variants on the X chromosome compared to the reference C . elegans genome ce6 W221 were analyzed . Genes with missense SNP variants in jj60 and jj77 , but not in jj58 and jj71 , were among the candidate genes that were targeted by RNAi for their ability to suppress the sma-9 ( cc604 ) M lineage defects by injection . These included C41A3 . 1 , K09C4 . 8 and C17G1 . 8 . Further PCR and sequencing confirmed the jj60 and jj77 mutations in C17G1 . 8 ( tsp-21 ) . For mapping additional suppressors using either direct WGS ( for jj2 , jj5 , jj7 , jj50 , jj52 and jj70 ) or SNP-WGS ( for jj49 , jj57 , jj62 , jj69 , jj71 , jj73 , jj78 and jj83 ) , sequence data were aligned to C . elegans reference genome version WS220 using BFAST [88] with default parameters . SNP calling was performed by SAMTOOLS [89] . A valid SNP call required a minimum read depth of three . ANNOVAR [90] was used for annotation of SNP coding potential . For SNP-WGS , Hawaiian SNPs were annotated with a custom Perl script . Scatter plots of heterozygous ( 0 . 2–0 . 7 fraction of total reads ) Hawaiian SNPs were generated as chromosome position vs . fractional total graphs . Mapping intervals were defined by visual inspection for gaps ( i . e . , Hawaiian SNP fraction <0 . 2 ) . Candidate suppressor genes were identified as homozygous ( fraction >0 . 8 ) , non-Hawaiian , nonsynonymous SNPs in the mapped interval . The SNPs in the identified suppressor genes were verified by PCR and sequencing . jj61 was mapped via SNP-WGS to the region on the X chromosome where lon-2 is located . Direct inspection of the sequence reads around the lon-2 region showed that jj61 contains a large deletion ( 11 . 8kb ) spanning the lon-2 region , which was subsequently verified by PCR and sequencing . sma-6 reporter and rescuing constructs pJKL840: sma-6p::nls::rfp::lacZ::unc-54 3’UTR pJKL1048: sma-6 ( jj69 ) p::nls::rfp::lacZ::unc-54 3’UTR pJKL1060: sma-6p::sma-6 rescuing construct tsp-21 reporter constructs pJKL1005: 5kb tsp-21p::tsp-21 genomic ORF::1 . 7kb tsp-21 3’UTR pJKL1004: 5kb tsp-21p::tsp-21 genomic ORF::gfp::1 . 7kb tsp-21 3’UTR pJKL998: 5kb tsp-21p::nls::gfp::lacZ::unc-54 3’UTR pZL11: 5kb tsp-21p::tsp-21 genomic ORF ( sgRNA target site modified ) ::gfp::1 . 7kb tsp-21 3’UTR Constructs for tissue-specific expression of tsp-21 pJKL1015: tsp-21p::tsp-21 cDNA::tsp-21 3’UTR pJKL1017: rol-6p::tsp-21 cDNA::tsp-21 3’UTR pJKL1018: elt-3p::tsp-21 cDNA::tsp-21 3’UTR pJKL1019: elt-2p::tsp-21 cDNA::tsp-21 3’UTR pJKL1020: hlh-8p::tsp-21 cDNA::tsp-21 3’UTR pJKL1021: myo-2p::tsp-21 cDNA::tsp-21 3’UTR The full-length tsp-21 cDNA clone yk1449c02 , which contains a SL1 trans-splice leader sequence , and full length 5’ and 3’ UTRs , was kindly provided by Dr . Yuji Kohara ( National Institute of Genetics , Japan ) . A point mutation in the coding region of tsp-21 in yk1449c02 was corrected by site-directed mutagenesis to generate pJKL994 . Transgenic animals were generated using the plasmid pRF4 or pJKL449 ( myo-2p::gfp::unc-54 3’UTR ) as markers . Integrated transgenic lines carrying pJKL1004[TSP-21::GFP] ( jjIs3113 and jjIs3114 ) were generated using gamma-irradiation . pJKL840[sma-6p::nls::rfp::lacZ::unc-54 3’UTR] was used for co-localization of TSP-21::GFP and sma-6p::nls::rfp . pTAA1[hlh-8p::cgt-3 . 1a ORF::unc-54 3’UTR] was used to test for function of cgt-3 in the M lineage . The following mix of plasmid DNAs was injected into the N2 gravid adults: ( 1 ) a Cas9 expression plasmid pDD162 [91] , ( 2 ) a tsp-21-specific sgRNA plasmid pZL10 , which has GAAACTGACACGGTAGAAGATGG replacing the unc-119 sgRNA in plasmid 46169 [92] , ( 3 ) the homologous repair template pZL11: 5kb tsp-21p::tsp-21 genomic ORF ( sgRNA target site modified ) ::gfp::1 . 7kb tsp-21 3’UTR , ( 4 ) a co-injection marker pCFJ90[myo-2p::mCherry] [93] . GFP knock-in events were screened via PCR using a primer in GFP ( ZL21: CGCATATCTTGGACGCCTAATTTG ) and a primer in the tsp-21 3’ region outside of the sequences included in pZL11 ( ZL22: TCCACACAATCTGCCCTTTCG ) . Single worm PCR of 250 F1s failed to detect any germline integration event . However , we checked the F2 generation for high transmission efficiency lines ( myo-2::mCherry positive ) and screened via PCR 5–10 F3 progeny from each of the three high transmission efficiency lines ( >50% ) . One of the three transgenic lines gave us two homozygous GFP knock-in strains: LW3670: jj93 ( tsp-21::gfp ) and LW3671: jj94 ( tsp-21::gfp ) . Total RNA was isolated from mixed-stage N2 or sma-6 ( jj69 ) worms using TRIzol Reagent ( Invitrogen ) . Reverse transcription was performed with SuperScript III First-Strand Synthesis System ( Invitrogen ) following the manufacturer’s instructions . The primers used to detect the cDNAs of sma-6 and act-1 are: sma-6 , MLF-34 and MLF-44; act-1 , NMA-163 and NMA-164 . Body size measurement and RAD-SMAD reporter assay were carried out as described in Tian et al . [22] . Dauer formation assay was carried out as described in Tian et al . [21] . Statistical analyses were performed using Microsoft Excel and GraphPad Prism ( http://www . graphpad . com/scientific-software/prism/ ) . GFP and RFP epifluorescence in transgenic animals was visualized either on a Leica DMRA2 compound microscope , where the images were captured by a Hamamatsu Orca-ER camera using the OPENLAB software , or on a Zeiss LSM 710 confocal microscope . Subsequent image analysis was performed using ImageJ and Photoshop CC . We identified tetraspanin homologs by running hmmsearch from HMMER 3 . 1b1 [94] with the hidden Markov model ( HMM ) profile for tetraspanins ( PF00335 . 15 ) from PFAM 27 . 0 [95] against the reference proteome set of the Quest for Orthologs consortium ( [96]; source URL , ftp:/ftp . ebi . ac . uk/pub/databases/reference_proteomes/QfO/QfO_release_2014_04 . tar . gz ) . hmmsearch was run with the arguments '-E 1e-06—domE 1e-06—incE 1e-06—incdomE 1e-06-A [alignment]' , which generated aligned regions of similarity to these core domains . Since the regions of homology were extracted from full-length proteins with an HMM , the specific residues extracted were generally a subset of the full protein; moreover , it was possible for two or more such regions to be independently extracted from a single protein chain , although this proved rare for tetraspanins . These regions were then realigned with MAFFT v7 . 158b [97] in L-INS-i , its slowest and most reliable mode , using the arguments '—localpair—maxiterate 1000' . The resulting alignments were purged of poorly aligned members by first running trimal v1 . 4 . rev15 [98] using the argument '-gt 0 . 5' , and then running BMGE 1 . 1 [99] using the arguments '-t AA-h 1-g 0 . 5:1' . This purged the alignments of any columns in which over 50% of the columns' positions consisted of gaps rather than amino acid residues , and then any sequences in which over 50% of the residues were gapped , yielding global alignments that lacked excessive loops and gaps . From the filtered alignments , we computed protein maximum-likelihood phylogenies , with a WAG model of amino acid evolution [100] and with pseudocounts for gaps , via FastTree 2 . 1 . 7 [101] , using the arguments '-pseudo-wag' . Confidence values for the branches of trees ( ranging from 0 . 00 to 1 . 00 ) were automatically computed by FastTree with 1 , 000 internal replicates . We visualized the resulting trees with FigTree 1 . 4 . 2 ( http://tree . bio . ed . ac . uk/software/figtree ) . Branch lengths were measured in average substitutions ( when comparing full sequences or their profiles ) among non-gap positions in the aligned sequences , with distances derived from the BLOSUM45 matrix , a correction for multiple substitutions , and an allowed maximum of 3 . 0 substitutions per individual site [102] . The split-ubiquitin yeast two-hybrid experiments were carried out following the detailed method described in Grefen et al . [103] . The bait CubPLV and prey NubG constructs were generated via PCR and recombinational in vivo cloning in yeast [103] . The resulting fusion constructs were recovered from yeast and transformed into E . coli and confirmed by sequencing . The primers , cDNA templates , and the names of the resulting bait and prey constructs are summarized in S2 Table . The bait and prey constructs were transformed into the haploid yeast strains THY . AP4 ( MATa ) and THY . AP5 ( MATα ) , respectively , and the resulting yeast strains were mated to generate diploid yeast cells carrying specific combinations of bait and prey constructs [103] . Interactions among each pair of bait and prey constructs were visualized by streaking diploid cells on SC-Trp , -Leu , -Ade , -His , -Ura , -Met plates that were supplemented with four different concentrations of methionine: 0mM , 0 . 075mM , 0 . 150mM and 0 . 300mM , respectively . Methionine can repress the expression of the CubPLV fusion , which is under the control of the Met-repressible MET25 promoter [42] . Growth was monitored for 2–9 days at 30°C . The plasmids KAT-1-Cub-PLV , NubG-KAT-1 ( in pNX33 vector ) and KAT-1-NubG ( in pXN21 vector ) [42] , HMT-1-Cub-PLV and HMT-1-NubG ( in pXN21 vector ) [46] were kindly provided by Sungjin Kim ( Cornell University ) and used as specificity controls . NubG fusions for PAR-4 , a protein unexpected to interact with any of the proteins tested , was included as another control for specificity of the interactions . The empty NubG vector was used as a control to determine if any Cub-PLV fusions can auto-activate the reporters . The vector expressing soluble wild-type Nub ( NubWT ) was used as a control to indicate expression of the Cub-PLV fusion . Additional confirmation of expression of each fusion protein came from western blot analysis using rabbit polyclonal anti-VP16 antibodies ( ab4808 , Abcam , for CubPLV fusions ) and monoclonal anti-HA antibodies ( Clone 12CA5 , Sigma , for NubG fusions ) .
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The bone morphogenetic protein ( BMP ) signaling pathway is required for multiple developmental processes during metazoan development . Various diseases , including cancer , can result from mis-regulation of the BMP pathway . Thus , it is critical to identify factors that ensure proper regulation of BMP signaling . Using the nematode C . elegans , we have devised a highly specific and sensitive genetic screen to identify new modulators in the BMP pathway . Through this screen , we identified three conserved tetraspanin molecules as novel factors that function to promote BMP signaling in a living organism . We further showed that these three tetraspanins likely form a complex and function together with glycosphingolipids to promote BMP signaling . Recent studies have implicated several tetraspanins in cancer initiation , progression and metastasis in mammals . Our findings suggest that the involvement of tetraspanins in cancer may partially be due to their function in modulating the activity of BMP signaling .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
Promotion of Bone Morphogenetic Protein Signaling by Tetraspanins and Glycosphingolipids
|
The circadian clock is accountable for the regulation of internal rhythms in most living organisms . It allows the anticipation of environmental changes during the day and a better adaptation of physiological processes . In mammals the main clock is located in the suprachiasmatic nucleus ( SCN ) and synchronizes secondary clocks throughout the body . Its molecular constituents form an intracellular network which dictates circadian time and regulates clock-controlled genes . These clock-controlled genes are involved in crucial biological processes including metabolism and cell cycle regulation . Its malfunction can lead to disruption of biological rhythms and cause severe damage to the organism . The detailed mechanisms that govern the circadian system are not yet completely understood . Mathematical models can be of great help to exploit the mechanism of the circadian circuitry . We built a mathematical model for the core clock system using available data on phases and amplitudes of clock components obtained from an extensive literature search . This model was used to answer complex questions for example: how does the degradation rate of Per affect the period of the system and what is the role of the ROR/Bmal/REV-ERB ( RBR ) loop ? Our findings indicate that an increase in the RNA degradation rate of the clock gene Period ( Per ) can contribute to increase or decrease of the period - a consequence of a non-monotonic effect of Per transcript stability on the circadian period identified by our model . Furthermore , we provide theoretical evidence for a potential role of the RBR loop as an independent oscillator . We carried out overexpression experiments on members of the RBR loop which lead to loss of oscillations consistent with our predictions . These findings challenge the role of the RBR loop as a merely auxiliary loop and might change our view of the clock molecular circuitry and of the function of the nuclear receptors ( REV-ERB and ROR ) as a putative driving force of molecular oscillations .
Circadian rhythms can be found in most organisms , from bacteria to humans and are a fundamental property of living cells [1] . These endogenous rhythms provide a way to anticipate external cues and to adapt molecular and behavioural processes to specific day-times with the advantage of temporally separating incompatible metabolic processes [2] . At the core of the system is the circadian clock , a complex network of genes able to generate stable oscillations with a period of circa 24 hours . The circadian clock has been studied in detail in various organisms such as cyanobacteria [3] , Neurospora [4] , Arabidopsis [5] , Drosophila [6] and mammals [7] . In mammals the main oscillator resides within the suprachiasmatic nucleus ( SCN ) and is directly entrained by light via the retinohypothalamic tract [8] . This central pacemaker in the SCN is formed by a set of roughly 20 . 000 neurons which produce rhythmic outputs and orchestrate local clocks in the brain and peripheral clocks throughout the body . Peripheral clocks in the liver , heart , kidney and skin are implicated in the regulation of local transcriptional activity . These can be synchronized also by external cues such as temperature and feeding schedules [9] , [10] . Circadian clocks are evolutionarily conserved [6] , [11] and designed to maintain an overall optimal organism activity . The internal pacemaker is responsible for the regulation of several biological processes at the cellular level . Such processes include sleep-awake cycles , memory consolidation [12] , [13] , metabolism of glucose , lipids and drugs [14] , [15] , bone formation [16] , hormone regulation , immunity [17] , the timing of cell division cycle and the physiological rhythms such as heart rate , blood pressure and body temperature [18] . Malfunctions of the circadian clock have been reported to be involved in many diseases and disorders such as susceptibility to cancer [19] , familial sleep disorders ( FASPS ) [20] , bipolar disorder , sleep problems in the elderly , seasonal affective disorders ( SAD ) [21] , [22] , diabetes [23] and obesity [24] . The daily regulation of molecular processes has severe consequences on therapy optimization and timing of drug intake , with the potential of minimizing toxicity and increasing treatment efficacy in complex diseases such as cancer [25] . Therefore , many efforts have been made to identify and understand the molecular circuitry of the clock and its role in disease and therapy [26] , [27] . The mammalian molecular clock network is constituted by at least two large interconnected feedback loops which are able to generate approximately 24 hour rhythms [28] , [29] . The heterodimer complex , CLOCK/BMAL , formed by the product of the genes circadian locomotor output cycles kaput ( Clock ) and brain and muscle aryl hydrocarbon receptor nuclear translocator like – Arntl ( Bmal ) represents the central node in the network and the transcription initiator of the feedback loops . CLOCK/BMAL binds to E-box cis-elements in the promoter regions of target genes Period homolog 1 , 2 and 3 genes ( Per1 , Per2 , Per3 ) , Cryptochrome genes ( Cry1 , Cry2 ) , retinoic acid-related orphan receptor ( Rora , Rorb , Rorc ) and Rev-Erb nuclear orphan receptor ( Rev-Erbα , Rev-Erbβ ) to activate their transcription [7] , [30] . The negative PER/CRY ( PC ) feedback loop is commonly seen as the primary generator of the circadian rhythm [31] . Transcription of Pers and Crys is initiated during the circadian day . Aided by post translational modifications , PER and CRY proteins enter the nucleus , probably as a multimeric complex ( PER/CRY ) [32] , and inhibit CLOCK/BMAL-mediated transcription after a certain delay [31] . The PER/CRY complex is degraded during the night , which releases its inhibitory action on CLOCK/BMAL and allows a new cycle of transcription to take place . The ROR/Bmal/REV-ERB ( RBR ) feedback loop is usually seen as adding robustness to the system [31] . Rors and Rev-Erbs are transcribed during the subjective day . Following translation , ROR and REV-ERB proteins compete for ROR regulatory element ( RRE ) binding sites in the promoter region of Bmal and regulate its transcription . ROR acts as an activator of Bmal and REV-ERB as an inhibitor which results in a fine-tuning of Bmal transcription [33] . Once in the nucleus the BMAL proteins form heterodimer complexes with CLOCK and initiate transcription of target genes ( Figure 1 ) . Minimal models such as the Goodwin oscillator were the first to describe a negative feedback oscillator involving three components [34] , [35] . Several kinetic models of the mammalian circadian clock have been subsequently developed [36] , [37] , [38] , [39] . Early models miss essential components such as the nuclear receptor ROR or posttranslational modifications . Other models are rather large and thus the estimation of kinetic parameters becomes exceedingly difficult . Still , many issues regarding the clock remain unknown or not completely understood . We propose here a single cell model for the mammalian mouse clock of intermediate complexity but containing the most essential biologically relevant processes . Our model allows an independent study of the two loops ( PC and RBR ) . It is biologically comprehensive , emphasizes a parameterization based on biochemical observables , and reflects the current state of research . Although much is known about the circadian clock network , the kinetics of many reactions is not known which makes the parameterization process complex . We have explored known phases and amplitudes among the model components and made use of control theory's principles [40] , to obtain estimations for many of the unknown parameters . The resulting model is tested using published data on genome-wide RNAi experiments [41] , [42] and transcriptional inhibition data [43] . Our model was applied to address open questions in circadian rhythm biology: firstly , what are the possible reasons for the observed two-loop design ? Mathematically , one negative feedback loop with a time delay would be enough to generate stable oscillations . There is evidence from published data showing that overexpression of components of the PC loop does not destroy oscillations [44] , [45] which together with remarkable phenotypic effects for members of the RBR loop [46] motivated us to investigate the role of the RBR loop in detail . Secondly , how does degradation kinetics affect the period ? We emphasize that such questions cannot be answered intuitively but require quantitative models . The period of the system depends on the timing of gene expression , accumulation and decay , and since clock protein degradation can influence all these processes , intuitive predictions are difficult . Our simulations show that faster degradation of clock proteins can indeed lead to shorter and longer periods under certain circumstances . In addition , our model predicted that overexpression of members of the RBR loop would lead to damped or even to the loss of oscillations . We could verify these predictions experimentally by constitutively overexpressing Ror and Rev-Erb RNAs in U2OS cells . Our study represents a step forward towards a fully parameterized model holding significant predictive value . Moreover , this work brings valuable insights into circadian clock biology and helps to understand apparently contradictory results .
We developed a model for the mammalian circadian clock , which allows the study of the two main feedback loops: ROR/Bmal/REV-ERB ( RBR ) and PER/CRY loop ( PC ) . The model can also be used to study mechanisms critical for the tuning of the circadian system including transcription , translation , import/export , degradation and phosphorylation . We decided to focus on the main pacemaker in the SCN which is assumed to be responsible for the synchronization of the circadian system . Furthermore , the SCN clock might be accountable for general malfunctions and consequent failure of peripheral clocks function , leading to the disruption of normal rhythms [19] , [20] , [25] . The model was designed based on an extensive literature search and accounts for the available experimental facts ( Dataset S1 ) of the mouse core clock , but is still small enough to allow a systematic parameter determination . For our data collection we gathered available expression data for phases and amplitudes for all the components of the system , regarding the SCN . In order to compare amplitudes of different components found in the literature we normalized the expression level of each component to its mean value . This procedure enables the simulation of expression profiles that oscillate around a base line of 1 , for all variables , facilitating the comparison among them . With the developed model we were able to investigate the effects of transcription and degradation on the period of the system and to shed light in a putative role of a two-loop design . The model contains 19 dynamic variables distributed along two main feedback loops that might be virtually separated ( Figure 1 , dashed line ) . Interlocked feedback loops were also reported for Neurospora [47] , Drosophila melanogaster [48] and Arabidopsis thaliana [49] . In our model we refer to gene family groups , or gene entities: Per ( Per1 , 2 , 3 ) [50]; Cry ( Cry1 , 2 ) [51]; Ror ( Rora , b , c ) [52] , [53]; Rev-Erb ( Rev-Erbα , β ) [54] , [55]; Bmal ( Bmal1 , 2 ) [56] . The same principle applies to the proteins and respective protein complexes , represented in Figure 1 . The central component , CLOCK/BMAL complex , binds to the promoter regions of clock genes ( Rev-Erb , Ror , Per , Cry ) activating their transcription [57] , [58] . Transcription is controlled by PER/CRY ( PER/CRYpool ) which possesses an inhibitory effect [59] . In our model the complex represents the pool of all possible PER/CRY complexes present in the nucleus including phosphorylated and unphosphorylated species . We consider in the model the effect of PER/CRY as a transcription inhibitor , regardless of the detailed mechanisms [60] , [61] . The circadian core clock network ( Figure 1 ) can be translated into a system of 19 ordinary differential equations ( ODEs ) with 71 parameters given in Text S1 . The system of equations was assembled using mostly the law of mass action [74] and linear degradation kinetics . A Michaelis-Menten degradation kinetics could be used as done in other models allowing smaller Hill coefficients [36] , [75] . However , such kinetic laws need more parameters , therefore , we decided to use linear laws in order not to increase the complexity of the model . Nonlinearities were introduced to describe transcription reactions by means of Michaelis-Menten [76] kinetics and Hill functions [77] . Many parameters could be retrieved from the literature and others were estimated based on known phases and amplitudes using LTI ( linear-time-invariant ) systems theory ( Text S2 ) . The LTI system theory is often used in electrical engineering , signal processing and control theory . It implies the linearization of the system . Therefore , we created a linear ODE version of the network and applied LTI to our system which allowed a partial determination of the parameters . Linear models allow the analytical calculation of amplitudes and phases as functions of the parameters [40] . Each feedback loop was transformed into a linear open loop system which was then closed , re-establishing the feedback . The parameters were optimized in order to achieve the optimal amplitude and phase-relations . In a subsequent step values for the corresponding parameters of the nonlinear system were determined using a Taylor expansion . After closing the loop the parameters were finally optimized to fine-tune the model . We based our calculations using key biological assumptions relevant for the mammalian circadian oscillator , such as a period of about 23 . 5 hours and measured phase/amplitude relations between the components of the model . The parameter estimation procedure is described in detail in Text S2 . Still 11 of 71 parameters remain free and their values were adapted to fine-tune the phase and amplitude relations . The resulting model generates oscillations with a period of 23 . 5 hours and is able to simulate RNA and protein peaks of expression in the range of the ones found in the literature ( Figure 2 ) . The circular graphic shows a comparison between the in silico peaks of expression and the corresponding experimental intervals found in the literature . Represented are 4 mRNA sets ( Ror , Rev-Erb , Bmal , Per , Cry ) and the nuclear protein complex PER/CRYpool ( PER/CRY nuclear pool ) , covering both parts of the model ( RBR loop and PC loop ) . Bmal mRNA reaches its maximum of expression in the early night . After translation the protein participates in the activation of its target genes in the nucleus . Rev-Erb has its highest expression in the early morning , followed by Ror and Per and finally Cry in the late morning/early afternoon . The heterodimer complex PER/CRY reaches its nuclear expression peak in the late afternoon closing the cycle . We have tested the predictive capability of the model by comparing results of our simulations with mutation data from knockout mice ( Dataset S1 ) and RNAi data from U-2OS cells [41] , [42] . The resulting period of the oscillations was analyzed and given as an output of the simulations . As shown by Brown et al . [78] single cell data might reflect behavioural phenotypes . Thus predictions from our single cell model can be compared with observations from animal mutational phenotypes . The experimental variability between animal model and cell line data , or even the same system but different publications is higher than the discrepancy between in silico and experimental data ( Table 1 ) . This might be due to the fact that the clock system is extremely complex , eventually with more redundancy and further parallel sub-pathways than established so far . It would be conceivable that more feedback loops involving the clock and interconnected networks [79] exist and explain the variability of the phenotypes . Moreover , our control analysis indicates ( see Table S1 ) that variability of some parameters such as degradation rates might be accountable for phenotypic differences between animals and cell lines . We used the optimized model to analyse the oscillatory potential of each loop as an independent oscillator [80] . Our complete model shows oscillatory expression patterns with a period of 23 . 5 hours for all components ( Figure 3A ) and simulates the phase differences and relative amplitudes found in the literature ( for comparison see Dataset S1 ) . Analysing the delays between the different gene species involved in the model ( Dataset S1 ) large delays in the RBR loop can be found . This suggests that this loop could act as an oscillator , also when decoupled from the system . We have therefore hypothesized that the RBR loop should be able to oscillate in the absence of an oscillatory driving force . To test this hypothesis , we replaced the variable PER/CRYpool by its mean value ( Text S1 , PC = 1 . 71 ) , creating a constitutive inhibitor . We further wished to analyse the robustness of the model regarding PC and carried out a set of 6 in silico experiments were the PC wild type value is perturbed ( PCWT = 1 . 7 ) to +/−10% , +/−20% , +/−50% ( Supplementary Figure 2 ) . As shown in the figure the oscillations are preserved also under these conditions . This RBR subsystem is a low amplitude oscillator , with a 25 . 1 hours period ( Figure 3B ) . Interestingly the expression pattern of Ror RNA is almost constant which is consistent with the fact that the inhibitor Rev-Erb might be the driving force of the RBR loop . We aimed to further investigate the independent role of the PC loop . Therefore , we simulated the decoupling of the PC loop by replacing CLOCK/BMAL and REV-ERBN by their mean values ( Text S1 , x1 = 1 . 7; x5 = 2 . 4 ) generating a constitutive inhibitor and activator respectively . The PC sub-system is a damped oscillator ( Figure 3C ) with a shorter period ( 20 . 7 ) then the coupled oscillator system . A negative feedback can induce circadian oscillations if the delay is at least 6 hours [81] . The observed delays between Bmal transcription and its inhibition via REV-ERBN exceed 6 hours ( Figure 4 ) . Thus it is conceivable that RBR loop is indeed an oscillator on its own as indicated by our findings . The nuclear receptors ROR and REV-ERB have been reported to control Bmal expression by competing for RORE elements in the promoter region of the gene and exert an opposite effect on the regulation of Bmal . Our model can simulate the pattern of RORN and REV-ERBN protein expression and its correlation with Bmal RNA expression , thereby illustrating the mechanism of Bmal regulation ( Figure 4 ) . The expression curve of both proteins is almost in anti-phase , which was obtained as a result of imposing a specific amplitude and phase for Bmal RNA . From the theoretical standpoint REV-ERB and ROR need to have opposite expression values in order to induce robust transcription of Bmal with a concentration and time for peak of expression according to published data . When the inhibitor REV-ERBN is at its maximum Bmal reaches its minimum expression value and RORN starts increasing its production . Some hours later RORN reaches its maximum and REV-ERBN reaches its minimum level , leading to a peak of Bmal expression . Both REV-ERBN and RORN act antagonistically to enhance Bmal oscillations , which will then regulate the transcription of the genes in the model . These observations are in agreement with experimental findings [33] . Is rhythmic activation of REV-ERB and ROR necessary for Bmal oscillation ? To answer this question we carried out further simulations in which we replaced the activator and inhibitor by constitutive ones with corresponding mean value . When REV-ERBN is replaced by its mean value ( Text S1 , x5 = 2 . 4 ) the oscillations of all components in our network are lost . Interestingly , if we increase the concentration of the constitutive inhibitor we recover Bmal oscillations . This could be related to the fact that REV-ERBN acts as an inhibitor of Cry as well . Increasing REV-ERBN induces an inhibitory effect on Cry transcription leading to a decrease of the PER/CRYpool and therefore to a decrease of the inhibition on CLOCK/BMAL . This leads to an increase of RORN and a consequent recovery of Bmal oscillations . If on the other hand , RORN is replaced by its corresponding mean value ( Text S1 , x6 = 5 . 8 ) , Bmal still oscillates but with smaller amplitude ( data not shown ) . These results indicate that the amplitude and phase relation between activator and inhibitor is crucial to generate a proper oscillating Bmal with the correct phase and amplitude . Taken together , results from our simulations point to a more important role of the RBR loop on the clock system , than previously assumed . Published data indicate an influence of the transcription rate on the period of the system [43] . We have addressed this question by perturbing the transcription of each of the five gene entities present in the model and measured the resulting period . A detailed table with all data corresponding to a gradient of the transcription rate from a 10 fold decrease to a 10 fold increase to the wild type is given as Table 3 in Dataset S2 . Analysing the effect of an overall increase in the transcription rate on the system , we observe a direct correlation to the period . As a response to an overall transcription increase , we obtain a longer period revealing a delay of the clock ( period measured for the in silico reporter gene Bmal ) . On the other hand by decreasing the overall transcription rates we obtain a shorter period which accounts for a hastening of circadian oscillations as reported by Dibner et al . [43] . Interestingly , we observe that only perturbations on Cry transcription do not lead to loss of oscillations . The same type of perturbation in the remaining 4 gene entities , leads to loss of oscillations . Moreover , for a decrease of the transcription rate of Per and Cry an increase of the period is observed pointing to their role as inhibitors . The same can be seen when decreasing the rate of transcription for Rev-Erb . This effect is opposite for the activators Ror and Bmal where an increase of the respective transcription rates leads to an increase of the period of the system . The effects of the degradation of Per on the period are very complex and not yet clarified [82] . This aspect can be exemplified by the following question: Is a faster degradation of a clock element , such as Per2 , leading to a shortening or lengthening of the period ? Degradation rates are intimately related to the effective delay [65] , [83] , [84] and consequently one might expect that faster degradation leads to a shorter delay and , subsequently , to a shorter period . This is indeed observed in a cellular model of the FASPS disorder [20] . On the other hand , fast degradation might slow down the nuclear accumulation of the inhibitory PER/CRY complexes leading to a prolonged period . This expectation sounds reasonable as well , thus , intuition alone leads to contradictory predictions and therefore detailed quantitative considerations are required to answer the question raised above . Mutational phenotypes of Per genes indicate in most cases period shortening or arrhythmic phenotype ( Table 1 ) . However , simulation data in Table 1 shows also an increase of the period , with increasing degradation rate . We found these observations remarkable and used the model to find a possible explanation . Our results are quite surprising as can be seen in Figure 5A . We analysed in detail the behaviour of Per when continuously changing its RNA degradation rate ( Text S1 , dy1 ) from 0 to 1 ( 3 . 3 fold increase of the WT value ) . Per has a non-monotonic behaviour regarding the degradation rate . This could explain why we see an increase in the period when increasing the degradation rate ( Table1 ) and on the contrary there are published phenotypes showing a decrease . Figures 5B–5D show simulated time-series of clock genes which can be analysed to understand the underlying mechanisms of non-monotonic period changes . If we choose a value for the degradation rate within the first part of the graphic ( marked points B , C ) then a decrease of the period with increasing degradation rate would also be seen ( Figure 5A ) . In the second part ( points D , E ) an increase of the period with the degradation rate is observed . As the degradation rate increases , the system moves from a scenario where the amplitudes of Per and Bmal are small and Per is in phase with Cry ( Figure 5B ) to another where Per and Bmal amplitudes are larger ( Figure 5C ) . Analyzing the profile of the inhibitor ( PER/CRY ) it is visible that the shape of the wave varies considerably . The time needed for PER/CRY to reach its inhibitory peak of action ( inhibition time , it ) and the time needed for it to reach the trough of expression ( release time , rt ) is different for the 4 points marked ( Figure 5A ) . This might account for the variation in the period . Therefore , we extracted the inhibition times and release times for Figure 5B ( it = 11 hours; rt = 16 hours ) and Figure 5C ( it = 10 . 5 hours; rt = 15 hours ) . The values measured ( 3 . 4% decrease in it and a 7 . 4% decrease in rt ) together with a sharper peak of the inhibitor complex due to amplitude and phase changes of Per and Cry are correlated with a shorter period ( Figure 5C ) . Due to the earlier phase of Per in Figure 5C compared to Figure 5B the release from inhibition is fastened . In the second part of the graphic ( Figure 5D , 5E ) the opposite happens . The period increases with the increase of the degradation rate . The increase in the degradation rate leads to even larger phase shifts between Per and Cry . Following the same methodology , we measured the inhibition and release times for PER/CRY for Figure 5 D , ( it = 11 . 5 hours; rt = 12 . 1 hours ) and for Figure 5E ( it = 12 , 9 hours; rt = 11 hours ) . These changes correspond to a 10 , 8% increase of the inhibition time and a 10% decrease of the release time leading to a 1 . 2% increase of the period . Long inhibition times might be correlated with an increase of the period . This intricate discussion of phase relationships and wave forms helps to understand seemingly counter-intuitive observations . Interestingly , non-monotonic dependencies were found also in much smaller models and with different kinetics than ours [85] , [86] . One well studied effect of the degradation on the period of the system is a circadian disorder , FASPS [20] , which was the first reported pathology to link known core clock genes to a human disorder . The disease results from a mutation in a casein kinase binding site which affects the phosphorylation of PER and therefore its degradation and results in a circadian oscillator with a shorter period . We wished to analyse the possible cause for the period shortening knowing that PER's degradation is affected . One possible mechanism could be that FASP mutation reduces the nuclear retention of PER2 but the turnover is not affected [20] . In order to simulate this situation we have increased the export rate of the PER*/CRY nuclear complex to ( kex2 = 0 . 05 ) and we obtained a decrease in the amplitude of Per and a shorter period , as reported . An alternative situation could be that the turnover of nuclear PER is enhanced , as well as its degradation by the proteasome . This has been previously described as another form of FASPS from the reports on the tau mutation in CKIepsilon [87] . To simulate this hypothesis we have increased the degradation rate for the nuclear protein PER* ( dx2 = 0 . 1 ) . As a result we obtain as well a shortening of the period and a decrease in the amplitude of Per . These results show that our model can simulate this particular biological problem and is able to illustrate possible alternative scenarios . In this case the model indicates two possible perturbations in the PER* protein , either affecting the degradation rate or the import/export of the phosphorylated protein , both leading to the experimentally observed decrease in the period . With more precise experimental measurements regarding localization and degradation kinetics of Per , the model should be able to discriminate between the two scenarios . Does a perturbation in the transcription of members of the RBR loop influence the system ? To test this property of the upper RBR loop we perturbed the transcription of each gene entity independently and analysed its behaviour and influence on the system . We investigated the robustness of the 4 genes ( Rev-Erb , Ror , Per , Cry ) represented in the model . In other words we have tested if the oscillations in the expression of these genes are kept in regard to variations in the corresponding transcription rate ( Vmax ) . For each of the genes the transcription rate was varied from 0 to about 3 times the original wild type value , Vmax ( WT ) . This simulates two scenarios: a down regulation of gene expression , for values of Vmax lower than Vmax ( WT ) ; an increase in transcription of the RNA , for values of Vmax above Vmax ( WT ) . The results from these simulations are displayed in the form of “rainbow-plots” ( Figure 6 ) . These plots provide similar information as bifurcation diagrams [88] with the benefit of allowing the simultaneous visualization of the gene expression dynamics . The rainbow plots allow the detection of sudden qualitative changes in dynamical behaviour of the system , upon small changes of the parameter analysed . We aimed to study the long term effect of the perturbations and hence have simulated 24 days and analysed the last 4 days ( Figure 6 ) . For all 4 gene entities there is an optimal parameter range , around Vmax ( WT ) value which allows the generation of oscillations with the desired phase and amplitude . Furthermore , for Rev-Erb , Ror and Per there is a defined optimal region where the system is able to oscillate , outside this region no oscillations are visible . Interestingly , Cry seems to be very resilient to perturbations . This could be related to the fact that this gene has two inhibitory mechanisms: PER/CRY and REV-ERBN which together could compensate for the increase in transcription levels . We aimed to explore the role of the RBR loop in more detail and therefore overexpressed in silico both Ror and Rev-Erb . To attain such a perturbation we added a constant RNA , to the endogenous one , for both gene entities independently ( Text S1 ) . The constitutive exogenous RNA was taken together with the endogenous one and used for the subsequent protein production . As an output we analysed Bmal patterns of expression . We took care to run our simulations in an in silico set up which would correspond to a real experimental set up , and therefore examined the transient region of the simulations . The result of the simulations for 6 days is given in Figure 7 . Our predictions show that Bmal magnitude increases upon Ror constitutive overexpression but the oscillations are lost after 6 days ( Figure 7A ) . Rev-Erb constitutive overexpression leads to a decrease of Bmal magnitude . Similarly to what happens with Ror , the oscillations are also damped and lost after 6 days ( Figure 7C ) . To experimentally verify our prediction , we have constitutively overexpressed Rora in human osteosarcoma cells harbouring a circadian reporter ( Bmal1-promoter-luc ) [42] , [89] which resulted in loss of oscillations , in agreement with our modelling data ( Figure 7B ) . Higher signals of luciferase activity in Rora overexpressing cells than in GFP controls indicate that overexpression was effective since RORa is a known activator of Bmal1 transcription . Constitutive overexpression of Rev-Erbα dose-dependently dampened circadian oscillation ( Figure 7D ) . Furthermore , higher levels of Rev-Erbα decreased Bmal1-promoter driven luciferase activity as expected for the transcriptional repressor of Bmal1 [46] . We are aware that a dampening of luminescence signals can reflect both a desynchronization of the cells and a dampening of single cell rhythm . The stronger decay observed after overexpressing both Ror and Rev-Erb ( Figure 7b and Figure 7C ) is larger than the GFP control . The same can be observed regarding amplitude and magnitude of the oscillations , indicating an effect of the overexpression on the system independent of the desychronization of cells .
The effect of perturbing the degradation of clock components on the period represents a difficult open question in circadian biology . Due to the complexity of the system results are difficult to predict . We show theoretically that the effect of mRNA degradation of Per on the period is non-monotonic which generates regions of opposite period variation . With a continuous increase of the degradation rate of Per mRNA it is possible to obtain first a decrease in the period and subsequently an increase . Our findings regarding a non-monotonic behaviour of Per can be related and help to explain apparently contradictory reports regarding perturbations on Per and effects on the period . Indications of opposite change in RNA levels have been found experimentally to induce the same change in the period . Dibner et al . [43] reduced overall transcription and observed a period shortening . On the other hand , Chen et al . [82] reports that , overexpression of Per leads to a period shortening as well . We could simulate both situations with our model ( Table 3 in Dataset S2 ) In these experiments , [43] , [82] changes in RNA levels ( in both directions ) lead to a decrease in the period which resembles the in silico dual behaviour regarding Per . The reported non-monotonic behaviour might as well explain these seemingly opposite experimental results . Interestingly , Cry seems to be very resilient to perturbations ( Figure 6 ) . This could be related to the fact that this gene has two sources of inhibition: PER/CRY and REV-ERBN which together could compensate for the increase in transcription levels . We have tested this hypothesis by removing REV-ERBN inhibition . The new network layout has an effect on Cry amplitude but does not lead to loss of oscillations on Cry . We therefore speculate that this might be related to the fact that Cry , in our system , does not hold posttranslational modifications . These results would be in discrepancy with Ueda et al . [90] , where overexpression of Cry leads to loss of oscillation . However in the Ueda study the exogenous Cry was given to the cells introducing additional complexity regarding transcriptional and posttranslational modification . It would be conceivable that CRY protein exhibits posttranslational modifications which would eventually account for the loss of oscillations . On the other hand Fan et al . [44] showed that addition of cell-permeable CRY ( CP-CRY ) does not lead to loss of oscillations and this biological scenario might be closer to our model and therefore related to our predictions . Further experiments and an extension of the mathematical model to incorporate posttranslational modifications of Cry would be necessary to answer this question , and will be addressed in future work . The combined activity of the CLOCK/BMAL activator and the P/C inhibitor regulates individual genes with different strengths . Moreover , Bmal itself is fine-tuned by REV-ERB and ROR , allowing the generation of oscillations with the appropriate amplitude and phase . A further fine control of the relative phase relations is subsequently achieved by tuning the degradation rates for each element . This fact raises many questions regarding the role of degradation in the individual control of the concentration and peak of expression of the clock genes . The development of a new model for the mammalian circadian clock ( Figure 2 ) and its fitting to state of the art experimental facts ( Dataset S1 ) rouse our awareness to the importance of the RBR loop . The conventional idea of a single driving core loop might not account for the complexity of the circadian clock and might not be sufficient to explain the redundancy mechanisms reported and the robustness of the system . Our results indicate that the RBR loop might have a more prominent role than previously thought . We present theoretical data that propose the RBR loop as being relevant for the generation of oscillations with appropriate amplitude and phases . The RBR loop can act as an independent oscillator even if we disrupt the oscillations of the lower PC loop ( Figure 3B ) . Moreover , we demonstrate experimentally that the overexpression of elements of this loop ( Rev-Erb and Ror ) can disrupt oscillations of Bmal mRNA . Additionally , the cross-connection between Rev-Erb and Cry can protect the system from external perturbations of Cry , due to the inhibitory action of REV-ERB . Our work brings new insight into circadian biology , it points to alternative scenarios able to explain experimental findings . It also raises important questions and might motivate further theoretical and experimental work to explore the RBR loop . The medical consequences of such findings should also not be overseen given that the RBR loop involves nuclear receptors which play a crucial role in hormonal processes and metabolism . Their disruption is connected to many diseases , they can be pharmacologically manipulated by agonists or antagonists and therefore represent an important drug target . Moreover , nuclear receptors bind hormones which could make them key players in synchronization and entrainment of clocks . Elements of the RBR loop might represent the missing link between central and peripheral clocks and could be involved in tissue specific circadian regulation .
The model was designed as a system of 19 ODEs and implemented using Matlab R2010a ( Mathworks , Cambridge , UK ) , with a solver for non-stiff systems ( ODE45 ) which implements a Runge-Kutta method . We have used a relative and absolute tolerance of 10−9 , with an integration step of 0 . 01 . The system of equations was assembled using Hill-type kinetics and mass action kinetics ( Text S1 , Figure S1 ) . Most parameters were derived from the literature or analytically determined using LTI theory ( Text S2 ) . The remaining parameters were found by fitting the expression profiles of the variables to published phase and amplitude values . The rainbow plots in Figures 6 and 7 were produced using Xppaut , version 5 . 85 ( http://www . math . pitt . edu/~bard/xpp/xpp . html ) and the Xppaut subsystem Auto . Lentiviral particles containing hRora , hRev-Erbα or GFP overexpression constructs in a pLenti6 backbone ( Invitrogen , Karlsruhe , Germany ) were generated as described in published reports [89] , [91] . For the high-throughput overexpression analysis of Rora , virus production was performed in 96-well format as described in detail in previous studies [89] , [91] . After filtration of the supernatant , U-2 OS cells harbouring a Bmal1-luciferase reporter were transduced in the presence of protamine sulfate ( 8 µg/ml , Sigma-Aldrich , Hamburg , Germany ) . Next day , medium was substituted by a blasticidine containing medium ( positive selection for 3 days; 10 µg/ml , Invitrogen , Karlsruhe , Germany ) . For viral transduction of hRev-Erbα and GFP in a larger scale , U-2 OS reporter cells were transduced with 250 , 500 or 1500 µl lentiviral containing supernatant including 8 µg/ml protamine sulfate . One day after transduction , cells were selected for 7 days with 10 µg/ml blastidicidin and subsequently seeded into 96-well plates . For online bioluminescence monitoring cells were synchronized by 1 µM dexamethasone ( Sigma-Aldrich , Hamburg , Germany ) . Bioluminescence was recorded for 7 days in a stacker-equipped TopCount luminometer with a sampling rate of about 0 . 5 hours . Two independent measurements for GFP and hRora ( each n = 3 ) were performed . Note that due to technical variations the first peak shows variable amplitudes . Dose-dependent overexpression of hRev-Erbα and GFP was monitored with an n = 4 per dosage . Raw data were de-trended by dividing a 24 h-running average . Periods and amplitudes were estimated by fitting the cosine wave function via the Chronostar analysis software [92] . For visualization , data were smoothened by a 4 hours-running average . Different basal luciferase levels from raw data were included by the fold change in luciferase activity relative to GFP controls for de-trended and smoothed data . Efficiency of dose-dependent hRev-Erbα overexpression was analyzed via quantitative real-time PCR using QuantiTect primer assays ( hRev-Erbα QT00000413 and hGAPDH QT01192646; Qiagen , Düsseldorf , Germany ) .
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Most organisms have evolved an internal clock which allows them to anticipate and react to the light/dark daily rhythm and is able to generate oscillation with a circa 24 hour rhythm . A molecular network involving feedback loops is responsible for the rhythm generation . A large number of clock-controlled genes pass on time messages and control several biological processes . In spite of its medical importance ( role in cancer , sleep disorders , diabetes and others ) the mechanism of action of the circadian clock and the role of its constituent's feedback loops remains partially unknown . Using a mathematical model , we were able to bring insight in open circadian biology questions . Firstly , increasing the mRNA degradation rate of Per can contribute to increase or decrease of the period which might explain contradictory experimental findings . Secondly , our data points to a more relevant role of the ROR/Bmal/REV-ERB loop . In particular , that this loop can be an oscillator on its own . We provide experimental evidence that overexpression of members of the ROR/Bmal/REV-ERB lead to loss of Bmal reporter mRNA oscillations . The fact that REV-ERB and ROR are nuclear receptors and therefore important regulators in many cellular processes might have important implications for molecular biology and medicine .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"systems",
"biology",
"biology",
"computational",
"biology",
"genetics",
"and",
"genomics"
] |
2011
|
Tuning the Mammalian Circadian Clock: Robust Synergy of Two Loops
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Measles virus ( MeV ) and all Paramyxoviridae members rely on a complex polymerase machinery to ensure viral transcription and replication . Their polymerase associates the phosphoprotein ( P ) and the L protein that is endowed with all necessary enzymatic activities . To be processive , the polymerase uses as template a nucleocapsid made of genomic RNA entirely wrapped into a continuous oligomer of the nucleoprotein ( N ) . The polymerase enters the nucleocapsid at the 3’end of the genome where are located the promoters for transcription and replication . Transcription of the six genes occurs sequentially . This implies ending and re-initiating mRNA synthesis at each intergenic region ( IGR ) . We explored here to which extent the binding of the X domain of P ( XD ) to the C-terminal region of the N protein ( NTAIL ) is involved in maintaining the P/L complex anchored to the nucleocapsid template during the sequential transcription . Amino acid substitutions introduced in the XD-binding site on NTAIL resulted in a wide range of binding affinities as determined by combining protein complementation assays in E . coli and human cells and isothermal titration calorimetry . Molecular dynamics simulations revealed that XD binding to NTAIL involves a complex network of hydrogen bonds , the disruption of which by two individual amino acid substitutions markedly reduced the binding affinity . Using a newly designed , highly sensitive dual-luciferase reporter minigenome assay , the efficiency of re-initiation through the five measles virus IGRs was found to correlate with NTAIL/XD KD . Correlatively , P transcript accumulation rate and F/N transcript ratios from recombinant viruses expressing N variants were also found to correlate with the NTAIL to XD binding strength . Altogether , our data support a key role for XD binding to NTAIL in maintaining proper anchor of the P/L complex thereby ensuring transcription re-initiation at each intergenic region .
Measles virus ( MeV ) , a member of the Morbillivirus genus , belongs to the Paramyxoviridae family of the Mononegavirales order [1] . These viruses possess a non-segmented RNA genome of negative polarity that is encapsidated by the nucleoprotein ( N ) to form a helical nucleocapsid . Not only does N protect viral RNA from degradation and/or formation of viral dsRNA , but it also renders the latter competent for transcription and replication . Indeed , the viral polymerase cannot processively transcribe nor replicate RNA unless the viral genome is encapsidated by the N protein within a helical nucleocapsid [2 , 3] . Transcription and replication are ensured by the RNA-dependent RNA polymerase complex made of the large protein ( L ) and the phosphoprotein ( P ) , with P serving as an essential tethering factor between L and the nucleocapsid . The complex made of RNA and of the N , P and L proteins constitutes the replication machinery . In order to perform messenger RNA synthesis , the polymerase has not only to bind to the 3’ transcription promoter , but also to re-initiate the transcription of downstream genes upon crossing each intergenic region ( IGR ) . Following polyadenylation , which serves as gene end ( GE ) signal , the polymerase proceeds over three nucleotides ( 3’-GAA-5’ or 3’-GCA-5’ ) without transcribing them and then restarts transcription upon recognition of a downstream gene start ( GS ) signal . Within infected cells , N is found in a soluble , monomeric form ( referred to as N0 ) and in a nucleocapsid assembled form [4] . Following synthesis , the N protein requires chaperoning by the P protein so as to be maintained in a soluble and monomeric form . The P N-terminal region ( PNT ) binds to the neosynthesized N protein thereby simultaneously preventing its illegitimate self-assembly and yielding a soluble N0P complex the structure of which have been characterised for MeV [5] as well as for four other members of the Mononegavirales order [6 , 7 , 8 , 9] . N0P is used as the substrate for the encapsidation of the nascent genomic RNA chain during replication [10] , ( see also [4 , 11 , 12 , 13] for reviews on transcription and replication ) . In its assembled homopolymeric form or nucleocapsid , N also makes complexes with either isolated P or P bound to L , with all these interactions being essential for RNA synthesis by the viral polymerase [14 , 15 , 16] . Throughout the Mononegavirales order , P and P+L binding to the nucleocapsid is mediated by interaction of the C-terminal region of P with either the C-terminal tail of N ( Paramyxoviridae members ) , or to the N-terminal globular moiety ( or core ) of N ( see [11 , 17] for review ) . The MeV N protein consists of a structured N-terminal moiety ( NCORE , aa 1–400 ) , and a C-terminal domain ( NTAIL , aa 401–525 ) [18 , 19] that is intrinsically disordered , i . e . it lacks highly populated secondary and tertiary structure under physiological conditions of pH and salinity in the absence of a partner ( for a recent review on intrinsically disordered proteins see [20] ) . While NCORE contains all the regions necessary for self-assembly and RNA-binding [10 , 21 , 22] and a binding site for an α-MoRE located at the N terminus of the P protein , NTAIL is responsible for interaction with the C-terminal X domain ( XD , aa 459–507 ) of P [11 , 18 , 21 , 23 , 24 , 25 , 26 , 27] ( Fig 1A ) . NTAIL binding to XD triggers α-helical folding within a molecular recognition element [28 , 29] of α-helical nature ( α-MoRE , aa 486–502 ) located within one ( Box2 , aa 489–506 ) out of three conserved NTAIL regions [18 , 24 , 27 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37] . XD-induced α-helical folding of NTAIL is not a feature unique to MeV , being also conserved within the Paramyxoviridae family [38 , 39 , 40 , 41 , 42 , 43] . XD consists of a triple α-helical bundle [27 , 34 , 44] , and binding to the α-MoRE leads to a pseudo-four-helix arrangement that mainly relies on hydrophobic contacts [18 , 27 , 44] . The α-MoRE of NTAIL is partly preconfigured as an α-helix prior to binding to XD [31 , 32 , 35 , 37 , 45] and adopts an equilibrium between a fully unfolded form and four partly helical conformers [37] . In spite of this partial pre-configuration , NTAIL folds according to a “folding after binding mechanism” [45 , 46] . Previous mutational studies showed that Box2 is poorly evolvable in terms of its binding abilities towards XD , in that amino acid substitutions therein introduced lead to a dramatic drop in the binding strength , as judged from a protein complementation assay ( PCA ) based on split-GFP reassembly ( gfp-PCA ) [47] . In particular , substitutions within the N-terminal region of Box2 ( aa 489–493 ) and at position 497 were found to lead to the most dramatic drops in the interaction strength [47] . In the context of the viral nucleocapsid , NTAIL points towards the interior of the latter and then extrafiltrates through the interstitial space between NCORE moieties , with the first 50 residues ( aa 401–450 ) being conformationally restricted due to their location between successive turns of the nucleocapsid [37] . The NTAIL region spanning residues 451–525 and encompassing the α-MoRE is , by contrast , exposed at the surface of the viral nucleocapsid and thus accessible to the viral polymerase . Binding of XD to NTAIL has been proposed to ensure and/or contribute to the recruitment of the viral P/L polymerase complex onto the nucleocapsid template . However , its precise function has remained enigmatic so far with reports of apparent conflicting observations . From the analysis of four NTAIL variants it was concluded that the accumulation rate of primary transcripts is rather insensitive to a drop in the apparent XD to NTAIL affinity [26] , while an XD variant showing a 1 . 7 times stronger interaction with NTAIL was associated with a 1 . 7-fold reduction in the accumulation rate of viral transcripts [48] . Furthermore , deletions studies of NTAIL have indicated that the interaction between XD and NTAIL may be dispensable for transcription and replication [49] . In the present work , we further investigate the molecular mechanisms by which substitutions in critical positions of NTAIL previously identified by a random approach [47] affect the viral polymerase activity . We did so by combining biochemical studies and molecular dynamics ( MD ) simulations on one hand with functional studies that made use of minigenomes and recombinant viruses on the other hand . Results identify positions 491 and 497 as the most critical in terms of both binding affinities and functional impact . In addition , thanks to the availability of a newly conceived minigenome made of two luciferase reporter genes , with the second one being conditionally expressed via RNA edition of its transcript by the viral polymerase , we could quantify the efficiency of transcription re-initiation after polymerase scanning through each of the five IGRs of MeV genome and on an elongated un-transcribed IGR ( UTIGR ) . A low NTAIL-XD affinity was found to be associated to a reduced ability of N to support expression of luciferase from the second gene . Furthermore , in infected cells , the accumulation rate of primary transcripts and transcript ratios were found to correlate with the equilibrium dissociation constant ( KD ) of the NTAIL/XD pair . Altogether obtained data argue for a key role of the NTAIL/XD interaction in transcription re-initiation at each intergenic region .
In a previous random mutagenesis study that made use of a PCA based on split-GFP re-assembly ( gfp-PCA ) [47] , we identified NTAIL variants that either decrease or increase the interaction strength towards XD [47] . Variant MX208 , which bears the D437V , P485L and L524R substitutions that are all located outside the α-MoRE , is an example of the latter group . We previously reported the generation and assessment of binding properties by gfp-PCA of six single-site variants ( R489Q , R490S , S491L , A492T , D493G and R497G ) bearing each a unique substitution within the α-MoRE [47] . Here , we additionally designed and generated the MXSF variant , which bears D437V , R439S , P456S and P485L substitutions that are all found in variants displaying an increased fluorescence [47] . Gfp-PCA in E . coli showed that the binding strength of these variants towards XD is scattered over a wide range , with the S491L and R497G variants showing the lowest interaction and with variant MXSF displaying interaction strength only moderately higher than wt NTAIL ( Fig 1B ) . Incidentally , this latter finding indicates that the effects of the substitutions are not cumulative . We then sought at assessing to which extent results afforded by the split-GFP assay in E . coli cells reflect NTAIL/XD binding occurring in the natural host cells of MeV . To this end , the interaction between XD and NTAIL variants was measured using the split-luciferase reassembly assay [50] . This technique is based on the same principle as the split-GFP reassembly assay . The reporter ( i . e . Gaussia princeps luciferase ) and the measured parameter ( luminescence ) are however different , and the assay is performed in human cells . Moreover , contrary to the split-GFP reassembly assay where reporter reassembly is irreversible , in the split-luciferase assay ( glu-PCA ) , association of the two luciferase fragments is reversible . As such , while the measured parameter in the former assay is dominated by the kon , the measured parameter in the latter assay does reflect the equilibrium between a kon and a koff and hence a true KD . A significant correlation was obtained between the two PCA methods ( Fig 1C ) , a finding that provides additional support for the significance of the observed differences in binding strength among variants . Furthermore , a significant correlation was also observed when comparing binding strengths as obtained using monomeric constructs ( i . e . NTAIL/XD ) and binding strengths obtained using their natural multimeric counterparts , i . e . P multimerization domain ( PMD ) -XD ( P303-507 ) and full-length mutated N protein constructs ( Fig 1D ) . The rationale for using P multimeric constructs devoid of the N-terminal region ( PNT ) was to eliminate the binding site to NCORE located within PNT and involved in P chaperoning of N protein to form N0P complexes [5] ( see Fig 1A for depicting scheme ) . Importantly , all N variants accumulated in cells in similar amounts ( S1 Fig ) indicating that variations in the level of reconstituted Gaussia luciferase likely reflects variations in NTAIL to XD binding strength . In order to characterize Box2 variants ( Fig 2A ) at the biochemical level , we expressed and purified six α-MoRE variants of NTAIL as N-terminally hexahistidine tagged proteins . All NTAIL variants were purified to homogeneity from the soluble fraction of the bacterial lysate through immobilized metal affinity chromatography ( IMAC ) followed by size exclusion chromatography ( SEC ) ( Fig 2B ) . The identity of all purified proteins were checked and confirmed by mass spectrometry . Even if their molecular mass is ~16 kDa , they all migrate on a denaturing gel with an apparent molecular mass of approximately 20 kDa ( Fig 2B , inset ) . This aberrant electrophoretic migration has been systematically observed for all NTAIL variants reported so far [26 , 30 , 31 , 32 , 46] including wt NTAIL [19] . This anomalous migration is frequently observed in IDPs and is due to a high content in acidic residues [51] and/or a large extension in solution [43] . All NTAIL variants , including wt NTAIL , have the same SEC elution profile ( Fig 2B ) . In particular , they are all eluted with an apparent molecular mass higher than expected and typical of a premolten globule ( PMG ) state [52] , as already observed in the case of wt NTAIL [19] . Thus , the amino acid substitution ( s ) causes little ( if any ) effect on the hydrodynamic volume sampled by the protein . Analysis of the secondary structure content of the NTAIL variants by far-UV circular dichroism ( CD ) shows they are all disordered , as judged from their markedly negative ellipticity at 200 nm ( Fig 2C ) . In addition , they are all similarly able to gain α-helicity in the presence of 20% 2 , 2 , 2 trifluoroethanol ( TFE ) ( Fig 2D ) , as already observed for wt NTAIL [19] . All variants have an estimated α-helical content similar ( within the error bar ) to that of wt NTAIL , with the only exception of variant R489Q that exhibits a lower α-helicity both in the absence and in the presence of TFE ( Fig 2E ) . Thus , most of the amino acid substitutions cause little ( if any ) effect on the overall secondary structure content and folding abilities of NTAIL . The binding abilities of the NTAIL variants , including wt NTAIL , were assessed using isothermal titration calorimetry ( ITC ) . To this end , the purified NTAIL proteins were loaded into the sample cell of an ITC200 microcalorimeter and titrated with wt XD . For each variant , two independent experiments were carried out . Fig 3 shows , for each variant , one representative ITC curve along with the relevant binding parameters . The XD/NTAIL molar ratios achieved at the end of the titration were 2 . 0 ( wt , R489Q , A492T , D493G ) , 2 . 5 ( R490S ) or 3 . 0 ( R497G ) ( Fig 3 ) . The data , following integration and correction for the heats of dilution , were fitted with a standard model allowing for a set of independent and equivalent binding sites . Consistent with the unfavorable entropic contribution associated to the disorder-to-order transition that takes place upon NTAIL binding to XD , whenever binding parameters could be determined , they revealed a decrease in entropy , with a ΔS ranging from -13 to -29 . 5 cal mol-1 deg-1 ( Fig 3 ) . Binding reactions were all found to be enthalpy-driven , with ΔH values in the same order of magnitude and ranging from -10 . 9 to -14 . 5 kcal/mol ( Fig 3 ) . The estimates for the model parameters of the wt NTAIL/XD pair were found to be in very good agreement with those recently reported [46] . The estimates for binding parameters of variants R489Q , A492T and D493G yielded equilibrium dissociation constant ( KD ) very close to that observed for wt NTAIL , indicating that these substitutions poorly affect the interaction ( Fig 3 ) . On the other hand , the R490S substitution resulted in a 7-fold decrease in the binding affinity ( KD of 20 μM ) . The decrease in affinity was even further pronounced ( KD of 44 μM ) in the case of the R497G variant , although the interaction remained measurable ( Fig 3 ) . In the case of the S491L variant the interaction strength was below the ITC detection limit and thus KD could not be estimated ( Fig 3 ) . The n values for the A492T/XD and D493G/XD binding pairs were found to deviate from unit , a behaviour that is not unusual and that has been already observed with single-site tryptophan variants [46] and that may arise from relatively poorly defined baselines . In light of all the numerous previous studies [18 , 19 , 27 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37] showing that NTAIL and XD form a 1:1 complex , these deviations were not taken to be significant . We next focused on how binding affinities obtained by ITC correlate with binding strengths inferred from split-GFP and split-luciferase reassembly assays . In fact , although it has already been established that the higher the fluorescence the higher the interaction strength [53] , no attempts were done at establishing which type of relationship exists between KD values and fluorescence or luminescence values . As shown in Fig 4 , we found a significant correlation between fluorescence or luminescence values obtained by gfp-PCA [47] and glu-PCA and the ln of KD values ( p = 0 . 02 in both cases ) . Although this finding needs to be confirmed on a larger set of data points , it lays the basis for the possibility of inferring KD values directly from fluorescence or luminescence values . Notably , if the results obtained by gfp-PCA ( see Fig 1B ) pointed out similarly low interaction strengths for variants S491L and R497G , ITC studies yielded a different profile . Indeed , while no interaction could be effectively detected for the S491L/XD pair , the KD could be measured for variant R497G ( see Fig 3 ) . Using the empirically determined equation relating luminescence and KD values ( Fig 4 ) , the KD of the S491L/XD pair was estimated to be 85 ± 33 μM , a value consistent with our inability to detect the interaction by ITC . Indeed , an interaction characterized by a KD of approximately 100 μM could escape detection unless extremely high ( and hardly achievable ) protein concentrations are used ( typically 1 mM NTAIL/10 mM XD ) [54] . Altogether , obtained results confirmed that not all Box2 residues are equivalent in terms of their role in NTAIL/XD complex formation . In particular , while substitutions at positions 489 , 490 , 492 and 493 have a slight to moderate impact , substitutions at positions 497 and 491 drastically affect complex formation without having a strong impact on the overall α-helicity . The role of Box2 residues in complex formation follows the order 491>497>490 , reflecting either the orientation of side chains towards the partner ( residues 490 and 491 ) or involvement in stabilizing interactions with XD residue Tyr480 in spite of solvent exposure ( residue 497 ) , as already proposed ( Fig 2A ) [47] . In order to further investigate the mechanisms by which residues Ser491 and Arg497 stabilize the NTAIL/XD complex , we performed MD simulations in aqueous solvent using the CHARMM force field [55] . MD simulations were carried out starting from the X-ray structure of the XD/α-MoRE complex [44] or from the in silico generated XD/α-MoRE S491L and XD/α-MoRE R497G models . In the case of the S491L variant , the three most favorable orientations of the side chains were generated . We first assessed the dynamical stability of the complexes . For this purpose , we analyzed the root-mean square deviation ( RMSD ) of the Cα atoms with respect to the initial structure as a function of time for the three complexes ( i . e . wt , S491L and R497G ) ( S1 Table ) . The RMSD values showed very little variations between the different constructs during the time course of the 50 ns simulations ( S1 Table ) . The average RMSD for XD and for the α-MoRE were approximately 0 . 8 and 0 . 5 Å , respectively , indicating structural stability of each domain during the simulations ( S1 Table ) . The relative orientation of the α-MoRE compared to XD was also assessed and revealed slightly higher average RMSD values for the two variants due to small local rearrangements of the structures to adapt to the substitutions . However , RMSD fluctuations were in the same order of magnitude . Secondary structure analyses of wt and mutated complexes confirmed that all α-helices are conserved during the whole trajectories . Overall , the different systems were stable during the whole simulation . Since the orientation of the side-chain of L491 showed no impact on the behavior of the complex during the MD simulation , only one conformer was selected in the rest of the study . Although the association between XD and NTAIL is essentially driven by hydrophobic contacts , the two partners also interact through hydrogen bonds that are thus expected to play a role in the binding affinity . Two intramolecular hydrogen-bond interactions are present in the crystallographic structure of the complex ( Table 1 ) . These interactions involve the side-chain of NTAIL residue Ser491 and side-chain of Asp493 and main-chain of Lys489 from XD . These interactions are preserved in the simulations of the wt and R497G complex ( Table 1 and S2 Fig ) . Due to the absence of the polar OH group in leucine , hydrogen bonds involving the OH group of Ser491 were lost in the simulations of the S491L complex . Three additional hydrogen bonds that are not present in the X-ray structure were observed in the MD trajectories of the wt complex ( Table 1 and S2 Fig ) . Two of them involve the side-chain of Asp487 from XD and side-chains of either Arg490 or Arg497 of NTAIL . Only the former was also observed in the simulations of both variants ( Table 1 and S2 Fig ) . The third one was formed between the side-chains of Lys489 from XD and Asp487 from NTAIL and was detected in the simulation of the three complexes with the two variants exhibiting even a higher frequency ( Table 1 and S2 Fig ) . In addition , a water-mediated hydrogen bond could be identified between the side-chains of Tyr480 of XD and Arg497 of NTAIL , 55 and 41 percent of the time in the wt and S491L complex , respectively . This interaction was not maintained with the same water molecule throughout simulation . However , when a water molecule moved away from this site it was almost immediately replaced by another water molecule . This interaction could not occur in the R497G complex and was not compensated by another interaction . The presence of this water-mediated interaction correlates with the stabilization of the aromatic ring of Tyr480 . The side-chain of Tyr480 was found in almost only one conformation corresponding to a χ2 angle ( CA-CB-CG-CD ) of approximately -130° in both wt and S491L complexes , whereas in the R497G complex , the ring oscillates between 2 conformations ( 50 and -130° ) corresponding to a 180° rotation . Although the position of this water molecule in the crystal structure cannot be estimated with precision because the molecule is poorly defined in the electron density , the fact that a water molecule is systematically observed at this position during the simulation argues for its critical role in stabilizing the Arg497-Tyr480 interaction . That water molecules can play crucial roles in stabilizing protein-protein interactions has been widely documented [56] . To further investigate the importance of the effect of the substitutions on the binding affinity , additional MD simulations were carried out using the free energy perturbation ( FEP ) method ( see details of the method in the Materials and Methods section ) . The calculations were based on the thermodynamic cycle shown in S3 Fig which allowed us to estimate the impact of an amino acid substitution on the binding energy by measuring the ΔΔG between the wt and mutated complexes at 300K . Replacement of Ser491 of NTAIL by Leu led to an average binding free energy change ranging from 3 . 22 to 3 . 91 kcal . mol-1 . These ΔΔG values correspond to a 200-fold to 700-fold reduction in binding affinities for the S491L variant which is compatible , although a bit more pronounced , with the KD calculated for this variant using the empirically determined equation between luminescence and KD values ( see above and Fig 4 ) . In a similar manner , substitution of R497 with Gly led to ΔΔG values ranging from 1 . 29 to 1 . 85 kcal . mol-1 . This corresponds to a 10 to 20-fold reduction of binding affinity which nicely correlates with the KD reduction-fold as measured by ITC . The dissociation of the XD/NTAIL complex cannot be observed during the time course of free MD simulations . To obtain more insights into the dissociation process , we therefore performed simulations using adaptive biasing force ( ABF ) , a method that allows overcoming barriers of the free-energy landscape [57] . The center of geometry between the two partners was selected as ordering parameter and both proteins were allowed to diffuse reversibly along this reaction coordinate during the different stages of the simulations ( no average force was exerted along the ordering parameter ) . The free energy profiles of the wt and mutated complexes are shown Fig 5A . The global minimum corresponds to a distance around 11 . 3 Å , very close to the distance observed in the X-ray structure ( 11 . 03 Å ) . Analysis of the wt complex reveals that the dissociation between the two partners proceeds from the C-terminal part of NTAIL corresponding to the more hydrophobic residues ( Fig 5B and S2 Fig ) . The final step of the dissociation corresponds to the disruption of hydrogen bonds between Ser491 of NTAIL and Lys489 and Asp493 of XD . The R497G complex exhibits an energy profile similar to that of the wt complex with slightly lower energy values indicating a lower resistance against disruption . In the case of the S49IL complex , the disruption can occur from either end of the α-helix of NTAIL depending on the trajectory . This behavior can be explained by the loss of hydrogen bonding with Lys489 and Asp493 of XD . As a consequence , the energy profile is profoundly affected and this variant shows less resistance toward disruption . Altogether , these data provide a mechanistic basis illuminating the critical role played by NTAIL residues Ser491 and Arg497 in stabilizing the NTAIL-XD complex . In order to investigate the functional consequences of attenuating the interaction between NTAIL and XD we tested the ability of each N variant to support the expression of a reporter gene from a minigenome rescued into a functional nucleocapsid by cotransfecting a plasmid coding for the minigenome under the T7 promoter together with P and L expression plasmid [58] . To take into account the transcription re-initiation at IGRs , we conceived and built new dual-luciferase minigenomes coding for Firefly and Oplophorus gracilirostris ( NanoLuc ) luciferase as first and second reporter gene respectively separated by each of the five IGRs of MeV genome ( Fig 6A ) . To this end , the NanoLuc luciferase was chosen because it has a ~150-times higher specific activity compared to Firefly luciferase [59] . Like many other paramyxoviruses , MeV polymerase has the ability to edit P mRNA by adding one non-templated G when transcribing the specific sequence termed P editing site ( 3’-uguggguaauuuuuccc-5’ ) [12 , 60] . We introduced this editing site just downstream the 3’-UAC-5’ START codon of the NanoLuc gene so as to condition the creation of the NanoLuc ORF and the ensuing translation of NanoLuc to the co-transcriptional insertion of one non-templated G by MeV polymerase . If minigenome RNA transcripts made by the T7 RNA polymerase are basally translated in spite of the lack of both cap and polyA signals ( S4A Fig ) , the T7 RNA polymerase does not recognize the P editing signal [61] . As a result , while the signal to noise ratio is ~24 for Firefly , it reaches ~521 for the edited NanoLuc , i . e . a 20-fold increase of the dynamic range ( S4B Fig ) . As a measure of the efficacy of each N variant to support the rescue of each minigenome , Firefly luciferase signals specifically driven by MeV polymerase from the first gene ( as obtained after subtraction of background levels observed in the absence of a functional L , ( see S5 Fig ) ) were compared . They were all found to be of similar magnitude irrespective of the MeV IGR within the minigenome and of the N variant , thus indicating comparable efficiencies of the rescuing step which relies on the random but ordinated encapsidation by the N protein of the naked RNA minigenome transcribed by the T7 polymerase ( [62] see [63] for review ) ( S5A and S5B Fig ) . We then verified that these newly built dual-luciferase minigenomes harboring individually one of the five IGR faithfully reproduce the expected re-initiation strength gradient . Indeed , when normalized to the NanoLuc/Firefly signal ratio observed with a minigenome carrying the N-P IGR , the ratios observed for the minigenomes harboring the downstream IGRs decrease with their remoteness from the genome 3’end with P-M being equivalent to N-P , M-F and F-H being significantly lower and H-L being the lowest of all ( Fig 6B , wt N ) . These results are in agreement with the transcription gradient observed in MeV infected cells [12 , 64 , 65 , 66] and with the efficacy of Sendai virus re-initiation at each IGR as determined using recombinant viruses [67] . Interestingly , this trend was absolutely conserved for every NTAIL variant upon normalization to the ratio observed with N-P IGR minigenome ( Fig 6B ) indicating that the observed re-initiation strength gradient is an intrinsic property of each IGR region . When NanoLuc/Firefly ratios observed for each N variant were plotted without normalization as a function of NTAIL/XD binding strength for each of the five MeV IGR minigenome , the NanoLuc/Firefly signal ratio was found to decrease with decreasing binding strength , with the correlation being significant at p~0 . 05 or below for N-P , P-M , M-F and F-H IGR minigenomes ( Fig 6C–6E ) , and the trend conserved for the minigenomes bearing the remotest H-L IGR ( Fig 6F and 6G ) . Since in the natural situation MeV polymerase has to travel through every IGR , we estimated for each individual variant a mean re-initiation rate through all MeV IGRs by calculating the mean NanoLuc/Firefly ratio of the 5 IGR regions for each N variant . Remarkably this mean re-initiation rate correlates with the NTAIL/XD binding strength ( Fig 6H , p = 0 . 021 ) . In few percent cases , the viral polymerase fails to recognize an intergenic region . This results in read-through transcripts . To investigate the possible impact of NTAIL/XD binding on read-through generation , a 3-gene minigenome was built as follows: the first gene code for the Firefly luciferase , the second gene codes for an irrelevant inactive protein ( here the C-terminal half of the Gaussia luciferase ( Glu2 ) ) followed by a linker that remains in the same coding phase throughout the second downstream N-P IGR and the third gene which contains the NanoLuc luciferase coding sequence devoid of a start codon and out of frame by one missing nucleotide that can be restored by the editing signal . Consequently , among all possible viral transcripts , only the edited read-through mRNA over gene 2 and gene 3 can give rise to a NanoLuc luciferase activity ( Fig 7A and 7B ) . Therefore , with the 3-gene minigenome , the NanoLuc/Firefly ratio is dependent on two IGR-related effects: the re-initiation of the transcription at the first IGR and the failure to recognize the second . As expected , the NanoLuc/Firefly signal ratios obtained with this 3-gene minigenome were found to be of a much lower level ( i . e . few percent ) than those observed with the 2-gene minigenome shown in Fig 6C . We normalized the NanoLuc/Firefly signal obtained with the 3-gene minigenome by the signal obtained with the 2-gene minigenome in order to cancel out the effect on the re-initiation at the first IGR and to focus on the generation of read-through transcripts at the second IGR . The resulting ratios are similar for all the variants , thus indicating they all roughly produce the same amount of read-though transcripts ( Fig 7C ) . We conclude that the NTAIL/XD binding strength does not significantly impact the failure of the viral polymerase to recognize the N-P intergenic region . Upon crossing an IGR , the polymerase from Mononegavirales having ceased RNA synthesis at the GE is able to scan forward and backward the genome template until it recognizes the transcription re-initiation site GS of the next downstream gene . This search for next GS had been initially observed as measurable temporal pause in transcription [68] ( see viral transcription scheme in S6 Fig and [13 , 69] for reviews ) . Since the frequency of re-initiation decreases with the length of the un-transcribed IGR ( UTIGR ) [70 , 71] dual-luciferase Firefly/NanoLuc 2-gene minigenomes with elongated UTIGR based on MeV N-P IGR were also built ( see scheme Fig 8A ) according to previous work based on the related Sendai virus that has served as the reference study model for Paramyxoviridae [70] . The Firefly signals specifically driven by MeV polymerase ( as obtained after subtraction of background levels observed in the presence of an inactive L protein ) observed with each combination of minigenome of variable UTIGR length and N variant were of similar magnitude irrespective of the UTIGR length and of NTAIL variant ( S7A Fig ) and did not show any correlation with the NTAIL/XD binding strength ( S7B Fig ) . These data confirmed that the rescue of the minigenome , is neither dependent on the sequence of the minigenome nor on the N variant . Incidentally , these experiments also allowed appreciating the reproducibility of our dual-luciferase minigenome-based experiments , as judged by comparing S5A and S7A Figs . As observed in the previous set of experiments , the NanoLuc/Firefly signal ratios obtained with the N-P minigenome ( i . e . UTIGR “+0” ) nicely correlate with the NTAIL/XD binding strengths ( Fig 8B , compare also with Fig 6C for data reproducibility ) . When N variants were tested with elongated UTIGR minigenomes , the NanoLuc/Firefly signal ratio exponentially declined with UTIGR elongation ( Fig 8C , p<0 . 001 for every N variant ) . However the declining rate varied between N variants ( compare the slopes in Fig 8C ) . This allowed us to calculate and compare the percentage of unpriming per UTIGR nt ( %unpriming/UTIGRnt ) . The D493G variant exhibits a significantly lower %unpriming/UTIGRnt compared to wt N , whereas that of R490S , R497G and S491L variant was significantly higher ( Fig 8D ) . Furthermore , the %unpriming/UTIGRnt of N variants tends to vary according to the log of the NTAIL/XD KD , ( Fig 8E , p = 0 . 062 ) . Remarkably , the %unpriming/UTIGRnt and mean re-initiation rate through the five MeV IGR regions significantly correlate to each other ( Fig 8F , p = 0 . 0032 ) . Overall these data reveal that lowering the NTAIL/XD binding strength significantly increases the unpriming rate of MeV polymerase during transcription re-initiation and its scanning over un-transcribed genomic sequences , i . e . over each UTIGR . Since even NTAIL variants with the highest KD for XD were able to reconstitute functional dual-luciferase minigenomes , we sought at evaluating the impact of substitutions in the viral context by expressing N variants into two types of recombinant viruses , namely unigene and biG-biS viruses . Unigene viruses possess only one copy of the N gene and thus express solely the mutated N protein . By contrast , biG-biS viruses contain a duplicated viral gene , here the N gene , one encoding the wt N protein ( wt Flag-N1 ) and one encoding the mutated N protein with a HA tag ( HA-N2 ) , the expression of which can be independently silenced thanks to the use of two cell lines expressing shRNA that selectively target one of the two N genes ( S8 Fig ) [48] . Unigene viruses harboring NTAIL variants were all rescued . The biG-biS viruses were also all rescued in cells allowing the selective expression of the wt Flag-N1 gene copy , although the too low virus production by the R489Q and R490S viruses prevented further analysis . Virus production by recombinant viruses at 3 d . p . i . were determined for unigene viruses in Vero cells , while that of biG-biS viruses was measured in three host cells allowing selective expression of either the wt Flag-N1 gene copy , the HA-N2 gene variant , or both of the N gene copies simultaneously ( Fig 9A ) . Virus production was found to be very low ( at least 2 log reduction with respect to the wt counterpart ) in the case of unigene and biG-biS S491L viruses . Note that the possibility that the observed differences in virus production of unigene viruses could be ascribed to a defect in N variant expression ( S1 and S9A Figs ) or to a significant contamination by defective interfering ( DI ) mini-replicons was checked ( S9B–S9D Fig ) and ruled out . When plotted against the NTAIL/XD binding strength as determined by glu-PCA , the virus production of unigene NTAIL variants does not significantly correlate with binding strength ( Fig 9B ) . However , the virus titer of biG-biS viruses under the selective expression of HA-N2 variant and under the combined expression of both N copies were found to correlate with NTAIL/XD binding strength ( p = 0 . 04 and p = 0 . 008 , respectively ) ( Fig 9C and 9D ) , while no such a correlation was found upon selective expression of the wt Flag-N1 copy as expected ( Fig 9E ) . We noticed that the coexpression of N wt with D493G variant appears deleterious for virus production ( Fig 9D ) . However , in a minigenome assay such a mixture of N was as efficient as N wt alone ( S10 Fig ) , thus ruling out the possibility that NTAIL heterogeneity could directly impact the polymerase activity . Overall these data indicate that the NTAIL/XD binding strength may control the virus production to some extent . We then took advantage of unigene viruses expressing the single-site Box2 variants to determine which activity of the viral polymerase could be affected by a change in the NTAIL/XD binding affinity . Vero cells were infected with wt , R489G , R490S , A492T , D493G and R497G unigene viruses . Note that the S491L variant was not investigated since it could not be further amplified to reach a workable titer . RNA synthesis parameters reflecting primary transcription ( i . e . mostly , if not solely , transcription , mediated by the active polymerases brought by infecting virions ) , secondary transcription and replication were determined by quantification of ( + ) and ( - ) RNA accumulation at different times post-infection as previously reported [48 , 65] . When RNA synthesis parameters were plotted along with NTAIL/XD KD , it appeared that both ( + ) RNA transcript accumulation rate and ratios between P ( or F ) and N transcripts could be roughly predicted from the interaction strength between the NTAIL variant and XD as measured by either method ( Fig 10 ) . The correlations were statistically significant between the accumulation rate of P ( + ) transcripts and NTAIL/XD KD ( Fig 10A ) and between the F/N transcript ratios measured at 24 h . p . i . and the KD ( Fig 10B ) . In further support of the coherence of the results , a good correlation was found between the accumulated levels of N and P ( + ) RNAs during primary transcription and at 24 h . p . i . ( S11A and S11B Fig ) , and between both N ( + ) and P ( + ) RNA transcripts and ( - ) genomic RNA ( S11C and S11D Fig ) . When the F/N mRNA ratios at 24 h . p . i . observed with unigene viruses were plotted against the calculated mean re-initiation rate of the 5 IGRs and the %unpriming/UTIGRnt a significant positive and a negative correlation were found , respectively ( Fig 11 ) . Altogether , these data support that the NTAIL/XD binding strength controls , at least in part , the steepness of the viral transcription gradient .
For most of the NTAIL variants the observed variations in binding affinities cannot be ascribed to differences in the extent of α-helical sampling of the free form of the α-MoRE , nor to differences in the ability of the latter to undergo induced α-helical folding . However , the R489Q substitution represents an exception in this respect: indeed , it has a reduced extent of α-helicity and a slightly increased KD towards XD . The reduced α-helical content of this variant is in line with secondary structure predictions , as obtained using the Psipred server ( http://bioinf . cs . ucl . ac . uk/psipred/ ) [72] , that predicts a slightly lower helical propensity . Whether the experimentally observed reduction in affinity towards XD arises from this lower helicity or from other attributes , including charge-related ones , remains to be established . This variant also displays a reduced accumulation rate of primary transcripts . The subtle molecular mechanisms underlying the peculiar behavior of this variant remain however to be elucidated . The complex hydrogen bonding revealed by MD simulations of NTAIL/XD complexes allows the drops in binding affinities experimentally observed for the S491L , R497G and R490S variants to be rationalized . Interestingly , these substitutions , which have the most dramatic effects in terms of binding affinities , are also the ones that have the strongest effect on virus replication , with the S491L substitution being very poorly tolerated even in biG-biS viruses . The poor ability of the low-affinity S491L variant in mediating efficient virus replication is reminiscent of the comparable deleterious effect of the F497D XD substitution [48] and of the detrimental effect of the deletion of the NTAIL region encompassing the α-MoRE [49] . We provide here compelling evidence indicating that the strength of the NTAIL/XD interaction controls , at least in part , the ability of the P+L polymerase complex to re-initiate at IGRs: data obtained using our highly sensitive and reproducible dual-luciferase minigenome assay reveal a significant correlation between the NTAIL/XD binding strength and the efficiency of the transcription re-initiation . Since our minigenome assays rely on the edition of the second reporter gene , we cannot formally exclude that the editing may be also impacted by the NTAIL/XD binding strength . However , the calculated %unpriming/UTIGRnt only depends on the decrease of the NanoLuc/Firefly signals ratios with the length of the UTIGR . The observed effect is therefore independent of any potential effect on the edition ( i . e . if N mutations only had an effect on editing , then this effect should be the same irrespective of the IGR under study and of its length , which is not the phenotype we observed ) . Moreover , the correlation in the viral context between the P/N and F/N mRNA ratio and the KD , supports a role for the XD/NTAIL interaction strength in the re-initiation at IGRs . A N protein truncated of its last 86 C-terminal amino acids , i . e . truncated of most of NTAIL including the XD binding site , had been shown to be active in transcription and replication both in a minigenome assay and when introduced into a recombinant virus [49] . We confirmed that the N1-439 truncated protein is as good as , if not better than , the wt N in transcribing the Firefly gene from our N-P 2-gene minigenome construct ( S12A Fig ) . However , its ability to support transcription re-initiation over the N-P junction was significantly reduced , with the extent of reduction being comparable with that observed with the low affinity R497G variant ( S12B Fig , UTIGR 0 nt ) , thus confirming the role of NTAIL/XD interaction in transcription re-initiation . This low efficiency of transcription re-initiation may explain the extreme growth defect of the recombinant virus bearing the truncated N until reversion to a wt N [49] . Assuming a very slow degradation of viral mRNA [65 , 66 , 73] , the transcripts accumulation rate in cells infected with unigene viruses reflects the RNA synthesis rate by the polymerase , the number of active polymerases ( and their recruitment onto the nucleocapsid template ) , and the number of polymerases that are recruited per time unit on a given gene . For the same reason , the transcript ratios between the different genes are likely mostly governed by the efficiency with which the polymerase re-initiates the transcription at each IGR . Assuming this being a conserved feature for every N variant , we can reasonably interpret the inverse correlation we observed between multiple transcript ratios and KD as reflecting a direct control of the NTAIL/XD binding strength on the efficiency of the re-initiation at each IGR . A lower binding strength leads to lower levels of downstream transcripts . After completion of the polyadenylation of the messenger encoded by the upstream gene , the polymerase may remain firmly in contact with its genomic RNA template embedded into the nucleocapsid only if maintained by the anchoring of its P subunit via a dynamic binding of its X domain to the TAIL domain of N subunits located at the IGR ( Fig 12 ) . Therefore , a decrease in the XD/NTAIL affinity may favour the unpriming of the polymerase . Whether unprimed polymerases can detach from the nucleocapsid or stay on the template and move forward to the end of the nucleocapsid remain to be established . Hence , XD to NTAIL anchoring would tightly control the re-initiation level of the RNA synthesis by the polymerase in the transcription mode , thus determining the steepness of the transcription gradient ( Fig 12 , see also S6B Fig ) . What could be the functional significance of the relationship between the accumulation rate of primary N and P transcripts and the XD/NTAIL binding strength ? As speculated , the dynamics of XD/NTAIL binding and release may also affect the polymerase processivity on the nucleocapsid [48] . The XD/NTAIL interaction may act as a brake and slows down the polymerase: the weaker is the interaction , the weaker is the brake . Also , because of the efficient recycling of the polymerases on the promoter [65] , if , in the absence of transcription re-initiation , the polymerase detaches from the RNA template , a steeper gradient would release more polymerases available for transcription of the first genes . With weaker NTAIL/XD interactions , the viral production by unigene viruses tends to be negatively affected although the correlation was not statistically significant likely because of the small number of available virus variants and the too high variability of the result due to the multiple intervening parameters ( see S6A Fig and the complete scheme of virus replication dynamics in [65] ) . However with biG-biS viruses , we did observe a significant correlation between virus production and NTAIL/XD binding strength in conditions where the N variant was selectively expressed . This significance may reflect both the higher number of available virus variants and/or the higher impact of the modulation of the transcription re-initiation process in viruses possessing an additional transcription unit ( i . e . where the polymerase has to go through one additional IGR ) . The similar correlation observed upon the co-expression of both wt Flag-N1 and variant HA-N2 copies may indicate similar impact on transcription re-initiation because of the tetrameric valence of the P anchoring on ( contiguous ? ) heterogeneous NTAIL appendages . Alternatively , it is possible that the heterogeneity of NTAIL within a given nucleocapsid template may have a negative impact on other mechanisms such as nucleocapsids packaging into particles since NTAIL also recruits the M protein [74] , a key virion assembly factor [75] . The discrepancy we observed between virus production from biG-biS viruses and minigenome data with mixed NTAILs argues for this later hypothesis . Using minigenomes with elongated UTIGR , we were able to measure the unpriming rate of the polymerase in the “scanning mode” and we show that a decrease in the NTAIL/XD affinity induces an increase of the unpriming rate . In this situation , without the stabilization and the active motion of the polymerase due to the RNA synthesis , the role of the NTAIL/XD interaction in maintaining the polymerase on the nucleocapsid may overcome the “brake” effect . Alternatively , as suggested by Krumm et al [49] , the NTAIL may need to be rearranged by P to allow an efficient RNA synthesis . In this case , a too low NTAIL/XD affinity may weaken the efficiency of P in rearranging NTAIL and would favor the unpriming of the polymerases . The fact that the N1-439 variant , that lacks most of NTAIL , has the lowest unpriming rate on UTIGR supports this second hypothesis ( 0 . 6 vs 0 . 81%unpriming/UTIGRnt for N1-439 and wt N respectively ) ( S12C Fig ) . In conclusion , the XD/NTAIL interaction may play a critical role in the polymerase processivity , in maintaining the polymerase anchored to the nucleocapsid during its scanning upon crossing the intergenic regions , and/or in the transcription re-initiation at each intergenic region . Since both increasing [48] or decreasing ( this study ) the XD/NTAIL affinity negatively affect the viral growth , the wild type XD/NTAIL binding strength seems to have been selected to mediate an optimal equilibrium between polymerase recruitment , polymerase processivity and transcription re-initiation efficiency . A corollary of this is that substitutions that strongly affect affinity towards XD are poorly tolerated . Consistent with this , the substitutions with the most dramatic impact herein investigated ( i . e . R490S , S491L and R497G ) do not naturally occur in any of the 1 , 218 non-redundant MeV sequences , while those that have a less drastic impact ( i . e . R489Q , A492T and D493G ) are found in circulating measles strains [47] . Interestingly , in the case of Ebola virus ( EBOV ) , an additional protein , i . e . VP30 , serves as an anti-terminator transcription factor , and mutations that either decrease or increase the binding affinity between N and VP30 , decrease RNA synthesis [76] thus arguing for a similarly tightly regulated interaction . According to our work , the NTAIL to XD binding strength tightly controls the transcription gradient . However , this does not rule out the possibility that other mechanisms may be at work in controlling the steepness of the gradient . Indeed , in the brain of three patients suffering from subacute sclerosis encephalitis ( SSPE ) or measles inclusion bodies encephalitis ( MIBE ) the transcription gradient was found to be steeper than the one measured in in vitro infected cells [77] although the amino acid sequences of NTAIL and XD were found to be unvaried [78] . Furthermore , in the absence of the C protein , a steeper transcription gradient is also observed [79] . These two lines of evidence advocate for a multi-parametric control of the transcription gradient . The major role of the N binding site on the C-terminus of P has been postulated to mediate L anchoring to the nucleocapsid without understanding the implication of such anchoring on the polymerase and/or on the nucleocapsid dynamics . The need for an optimized interaction between the P and N proteins might be one of the major evolution constraints to which the polymerase machinery of MeV , and possibly of paramyxoviruses in general , is subjected . Our findings raise also the question as to whether binding of the C-terminus of P to the globular moiety of N , as observed in other Mononegavirales members , needs to be similarly controlled reflecting a similar functional role . The bipartite nature of P to N binding ( see scheme Fig 1A ) is remarkably conserved throughout the Mononegavirales order [80] . An α-MoRE located at N-terminus of P binds to the C-terminal globular domain of the NCORE to form the so-called N0P complex that is used by the polymerase as the encapsidation substrate . Solved N0P structures from members of the Rhabdoviridae family ( vesicular stomatitis virus , VSV ) [8] , Filoviridae family ( VP35 , of EBOV ) [81 , 82] , Pneumoviridae family ( human metapneumovirus , HMPV ) [9] and Paramyxoviridae family ( Nipah virus , NiV a Henipavirus member ) [7] , MeV a Morbillivirus member [5] , mumps virus , MuV a Rubulavirus member [83] revealed a common mechanism whereby the N terminus of P competes out with N arms that stabilize the oligomeric form of N and directly or indirectly prevents RNA binding . Structural and functional evidences indicate that , via its N-terminus , P can transiently uncover the genome at its 3’end from the first N subunits to give L access to its genomic RNA template ( see [83] and [84] for review ) . An additional N-binding site is located at the C-terminus of P ( or VP35 for EBOV ) ( see scheme Fig 1A ) [85] and allows binding to the assembled form of N . While this secondary binding site is required for the polymerase activity in minigenome experiments from several viruses [3 , 83 , 85 , 86 , 87] , the structures of the reciprocal N-binding and P-binding site on P and N , respectively , look less conserved . In the case of NiV [42] , Hendra virus [88] , SeV [38 , 89] and MeV [27 , 30 , 44 , 89] the C-terminal domain of P ( XD ) is structurally conserved and consists of a bundle of 3 α-helices that are structurally analogous , and that dynamically binds to a α-MoRE located near the C-terminus of NTAIL ( [90 , 91] , see [92] for reviews ) . This NTAIL-XD interaction is commonly characterized by a rather low affinity ( KD within the 3–50 μM range , [39 , 46 , 89] and this work ) . In Rubulavirus members , the C-terminal region of P spans in solution a structural continuum ranging from stable triple α-helical bundles to largely disordered , with crystal packing stabilizing the folded form [93 , 94] . In MuV , this triple α-helical bundle analogous to XD binds directly to the core of N subunits of the nucleocapsid [24] without excluding a complementary binding to the extremity of NTAIL [83] . By analogy with MuV XD , MeV XD might also bind to another binding site located on NCORE . This would explain how transcription and replication can still be observed in the presence of the N1-439 truncated where interaction of P relies only on NCORE ( [49] and this paper ) . Indeed in other Mononegavirales members , the C-terminus of P binds to the core of N . In the case of RSV , the minimal nucleocapsid-binding region of P , which encompasses the last nine P residues , is disordered [95] and remains predominantly disordered even upon binding to the N-terminal lobe of NCORE [96] . The C-terminal domain of P from Rabies virus ( RABV ) [97] , Mokola virus [98 , 99] and VSV [100] share a fold made of a bundle of α-helices that binds to the core of two adjacent N proteins of the nucleocapsid [101 , 102] . The N protein of Rhabdoviridae members , along with the N protein from RSV lacks the disordered NTAIL domain that characterizes N proteins from Paramyxoviridae members . In contrast to the XD-NTAIL interaction , the C-terminal domain of RABV P binds to the nucleocapsid with a high affinity ( KD in the nanomolar range ) [101] . In spite of the diversities of both structural features and binding modes within Mononegavirales members , does the binding of C-terminus of P to the assembled form of N fulfill common functions , namely ensuring the proper efficiency in polymerase scanning and re-initiation at intergenic regions ? Further works will unveil to which extent our present findings are relevant for other members of the Paramyxoviridae or other families of the Mononegavirales order .
The pDEST17O/I vector [103] , allowing the bacterial expression of N-terminally hexahistidine tagged recombinant proteins under the control of the T7 promoter , was used for the expression of all NTAIL variants . The pDEST17 derivatives encoding single-site NTAIL variants bearing substitutions within Box2 were obtained either by Gateway recombination cloning technology ( variants R489Q , R490S , S491L and R497G ) using the previously described pNGG derivatives [47] as the donor vectors , or by site-directed mutagenesis ( variants A492T and D493G ) . In the latter case , we used a pair of complementary mutagenic primers ( Operon ) designed to introduce the desired mutation , Turbo-Pfu polymerase ( Stratagene ) , and the pDEST17O/I construct encoding wt MeV ( Edmonston B ) NTAIL as template [47] . After digestion with DpnI to remove the methylated DNA template , CaCl2-competent E . coli TAM1 cells ( Active Motif ) were transformed with the amplified PCR product . The pNGG derivative encoding the MXSF NTAIL variant N-terminally fused to the N-terminal fragment of GFP was obtained in four steps using pNGG/NTAIL as template [47 , 104] and site-directed mutagenesis PCR . In the first step , the pair of mutagenic primers was designed to introduce the first amino acid substitution . After PCR and DpnI digestion , CaCl2-competent E . coli TAM1 cells ( Active Motif ) were transformed with the amplified PCR product . After having sequenced the construct to ensure that the desired mutation had been introduced , a second PCR was carried out using another pair of mutagenic primers designed to introduce the second substitution . Repeating this procedure four times led to the final construct bearing the four desired substitutions ( i . e . D437V , R439S , P456S and P485L ) . The sequences of the coding regions of all constructs generated in this study were checked by sequencing ( GATC Biotech ) and found to conform to expectations . The pDEST17/NTAIL construct encoding wt NTAIL has already been described [47] , as is the pDEST14 construct encoding C-terminally hexahistidine tagged MeV XD [30] . The plasmid p ( + ) MVNSe previously described in [48] was used as the MeV genome backbone . MeV genomic plasmids were built by direct recombination of one or two PCR fragments according to the InFusion user manual ( Clontech ) . To build biG-biS recombinant viruses , the N gene was duplicated in N1 and N2 in gene positions 1 and 2 , respectively . N1 was tagged with an N-terminal Flag peptide and three copies of the GFP RNAi target sequence ( GAACGGCATCAAGGTGAA ) in the 3’UTR of its mRNA . N2 was tagged with an N-terminal hemagglutinin ( HA ) peptide and three copies of the P RNAi target sequence ( GGACACCTCTCAAGCATCAT ) in the 3’UTR . Mutations into the NTAIL domain of N , R489Q , R490S , S491L , A492T , D493G , R497G , MXSF ( D437V/R439S/P456S/P485L ) and MX208 ( D437V/P485L/L524R ) , were introduced by subcloning PCR-amplified fragments from the pDEST17/NTAIL vectors . Full length wt and mutated N , wt and mutated NTAIL , PPMD-XD and P376-507 fragments were subcloned downstream Gaussia glu1 and/or glu2 domains by InFusion recombination of PCR-amplified fragments as previously described [48] . All plasmids and viruses ( N1 , N2 , P , M , and L gene ) were verified by sequencing the subcloned PCR fragments or cDNA obtained by reverse transcription-PCR ( RT-PCR ) performed on virus stocks . Plasmids encoding dual-luciferase editing-dependent 2-gene minigenomes were built by InFusion subcloning of PCR amplicons encompassing Firefly and NanoLuc coding sequences flanked by N UTR and L 3’UTR . The two luciferase coding sequences are separated by the N-P IGR either unmodified or exchanged with P-M , M-F , F-H and H-L IGRs ( i . e . untranscribed 3’-GAA-5’ ( or 3’-GCA-5’ for H-L ) triplet flanked by canonical upstream and downstream gene end and gene start sequences arbitrarily fixed to 15 nt ) or elongated by 12 , 36 , 108 or 324 nt ( see sequences in S2 and S3 Tables ) into the p107 ( + ) MeV minigenome construct that drives the synthesis of ( + ) genomic strand under the control of the T7 promoter [62] . According to the rule of six that governs the strictly conserved hexameric length of measles virus genome [62 , 105] , all minigenomes share identical phasing of the last U of the polyadenylation signal of the firefly gene ( phase 6 , i . e . the last nucleotide covered by the N subunit ) and of the editing site with the C being in phase 6 as defined in [106] . A 3-gene minigenome coding for Firefly and chimeric Glu2-linker-NanoLuc luciferase as a results of read-through between gene 2 and gene 3 and RNA editing was built by modifying the N-P 2-gene minigenome . As a second gene , the ORF of the C-terminal domain of Glu ( glu2 ) was inserted downstream to a START codon but without a STOP codon . This ORF is followed by a second N-P IGR and by the NanoLuc ORF without its own START codon , in frame “-1nt” to the upstream Glu2 ORF . Following addition of a G thanks to the presence of the P editing site , the NanoLuc ORF becomes in frame with the upstream Glu2 ORF . Consequently , the full-length chimeric Glu2-linker-NanoLuc can be uniquely translated from a read-through transcript over the second N-P IGR that is also edited ( see sequence in S4 Table ) . All plasmids will be deposited in the Addgene plasmid repository service except the glu1 and glu2 constructs that Addgene cannot accept . Those constructs are available upon request . The E . coli strain Rosetta [DE3] pLysS ( Novagen ) was used for the expression of all recombinant proteins . Transformants were selected on ampicillin and chloramphenicol plates . 50 mL of Luria-Bertani ( LB ) medium supplemented with 100 μg/mL ampicilin and 34 μg/mL chloramphenicol were seeded with the selected colonies , and grown overnight to saturation . An aliquot of the overnight culture was diluted 1/25 in LB medium containing ampicillin and chloramphenicol and grown at 37°C . When the optical density at 600 nm ( OD600 ) reached 0 . 6–0 . 8 , isopropyl ß-D-thiogalactopyranoside ( IPTG ) was added to a final concentration of 0 . 2 mM , and the cells were grown at 37°C for 4 additional hours . The induced cells were harvested , washed and collected by centrifugation ( 5 , 000 g , 12 min ) . The resulting pellets were frozen at –80°C . All the NTAIL and XD proteins were purified to homogeneity ( > 95% ) from the soluble fraction of bacterial lysates in two steps: Immobilized Metal Affinity Chromatography ( IMAC ) , and size exclusion chromatography ( SEC ) . Cellular pellets of bacteria transformed with the different expression plasmids were resuspended in 5 volumes ( v/w ) of buffer A ( 50 mM Tris/HCl pH 8 , 300 mM NaCl , 20 mM imidazole , 1 mM phenyl-methyl-sulphonyl-fluoride ( PMSF ) ) supplemented with lysozyme ( 0 . 1 mg/mL ) , DNAse I ( 10 μg/mL ) , 20 mM MgSO4 and protease inhibitor cocktail ( Sigma ) . After a 30-min incubation with gentle agitation , the cells were disrupted by sonication . The lysate was clarified by centrifugation at 20 , 000 g for 30 min . The clarified supernatant , as obtained from a one-liter culture , was incubated for 1 h with 5 ml ( 50% ) Chelating Sepharose Fast Flow Resin preloaded with Ni2+ ions ( GE , Healthcare ) , previously equilibrated in buffer A . The resin was washed with buffer A supplemented with 1 M NaCl to remove contaminating DNA , and the proteins were eluted in buffer A containing 1 M NaCl and 250 mM imidazole . Eluents were analyzed by SDS-PAGE . Fractions containing the recombinant product were concentrated using centrifugal filtration ( Centricon Plus-20 , 5000 Da molecular cutoff , Millipore ) . The proteins were then loaded onto a Superdex 200 ( NTAIL ) or Superdex 75 ( XD ) 16/60 column ( GE , Healthcare ) and eluted in 10 mM Tris/HCl pH 8 , 150 mM NaCl . Protein concentrations were calculated using the theoretical absorption coefficients at 280 nm as obtained using the program ProtParam at the EXPASY server . Mass analysis of the purified mutated NTAIL proteins was performed using an Autoflex II ToF/ToF ( Bruker Daltonics ) . Spectra were acquired in a linear mode . 15 pmol of samples were mixed with an equal volume ( 0 . 7 μL ) of sinapinic acid matrix solution , spotted on the target and dried at room temperature . The identity of the purified NTAIL proteins was confirmed by mass spectral analysis of tryptic fragments obtained by digesting ( 0 . 25 μg trypsin ) 1 μg of purified recombinant protein isolated onto SDS-PAGE . The tryptic peptides were analyzed as described above and peptide fingerprints were obtained and compared with in-silico protein digest ( Biotools , Bruker Daltonics ) . The mass standards were either autolytic peptides or peptide standards ( Bruker Daltonics ) . The CD spectra of NTAIL proteins were recorded on a Jasco 810 dichrograph using 1-mm thick quartz cells in 10 mM sodium phosphate pH 7 at 20°C . CD spectra were measured between 190 and 260 nm , at 0 . 2 nm/min and are averages of three acquisitions . Mean ellipticity values per residue ( [Θ] ) were calculated as [Θ] = 3300 m ΔA/ ( l c n ) , where l ( path length ) = 0 . 1 cm , n = number of residues , m = molecular mass in daltons and c = protein concentration expressed in mg/mL . Number of residues ( n ) is 147 , while m is 16 310 Da . Protein concentrations of 0 . 1 mg/mL were used when recording spectra . Structural variations of NTAIL proteins were measured as a function of changes in the initial far-UV CD spectrum following addition of 20% 2 , 2 , 2 trifluoroethanol ( TFE ) ( Sigma-Aldrich ) . The experimental data in the 190–260 nm range were analyzed using the DICHROWEB website which was supported by grants to the BBSRC Centre for Protein and Membrane Structure and Dynamics [107 , 108] . The CDSSTR deconvolution method was used to estimate the content in α-helical and disordered structure using the reference protein set 7 . ITC experiments were carried out on an ITC200 isothermal titration calorimeter ( Microcal ) at 20° C . Protein pairs used in the binding analyses were dialyzed against the same buffer ( 10 mM Tris/HCl pH 8 , 150 mM NaCl ) to minimize undesirable buffer-related effects . The dialysis buffer was used in all preliminary equilibration and washing steps . The concentrations of purified wt and mutated NTAIL proteins in the microcalorimeter cell ( 0 . 2 mL ) ranged from 25 μM to 180 μM . XD was added from a computer-controlled 40-μL microsyringe via a total of 19 injections of 2 μL each at intervals of 180 s . Its concentration in the microsyringe ranged from 300 μM to 960 μM . A theoretical titration curve was fitted to the experimental data using the ORIGIN software ( Microcal ) . This software uses the relationship between the heat generated by each injection and ΔH° ( enthalpy change in kcal mole-1 ) , KA ( association binding constant in M-1 ) , n ( number of binding sites per monomer ) , total protein concentration and free and total ligand concentrations . The variation in the entropy ( ΔS° in cal mol-1 deg-1 ) of each binding reaction was inferred from the variation in the free energy ( ΔG° ) , where this latter was calculated from the following relation: ΔG° = -RT ln 1/KA . All MD simulations were performed in explicit solvent with periodic conditions with CHARMM and NAMD software packages and CHARMM force field version 27 with CMAP corrections . The initial coordinates of the XD/α-MoRE complex were taken from the crystal structure ( PDB code 1T6O ) [44] . The two XD/α-MoRE mutated models bearing either the S491L or the R497G NTAIL substitution , were built with VMD plugin ‘mutator’ starting from the X-ray structure of the wt complex ( PDB code 1T6O ) . In the case of the S491L variant , the three most favourable orientations of the leucine side chain were generated with Sybyl . Non-protein derivatives were discarded . Orientation of the side chains of Asn , Gln , and His residues were checked using in-house VMD plugin and the WHAT IF web interface ( http://swift . cmbi . kun . nl/ ) . Residue His498 of XD was assigned HSD type and all other titratable groups were assigned standard protonation state at pH 7 . 0 . Coordinates of missing hydrogen atoms were added using the hbuild algorithm in CHARMM . To improve conformational sampling , three independent simulations were carried out using different initial velocities . The system was solvated with a pre-equilibrated solvation box ( edge length around 60 Å ) consisting of TIP3P water molecules . Crystallographic water molecules were included in the initial model . Chloride and sodium ions were added to achieve neutralization of the whole system . Periodic boundary conditions were applied . Unfavorable contacts were removed by a short energy minimization with conjugate gradient and ABNR . Electrostatic interactions were treated using the particle-mesh Ewald summation method , and we used the switch function for the van der Waals energy interactions with cuton , cutoff and cutnb values of 10 , 12 and 14 Å respectively . Vibration of the bonds containing hydrogen atoms were constrained with the Shake algorithm and a 1-fs integration step was used . The system was heated gradually to 300K , followed by an equilibration step ( 500 ps ) . During these two early steps , harmonic constraints were applied to protein heavy atoms . The constraint harmonic constant ( k ) was equal to 1 and 0 . 1 kcal/mol/Å2 for the backbone and side chains , respectively , and was removed after 250 ps equilibration . The production phase of 50 ns was performed without any constraints . Snapshots of the coordinates were saved every 0 . 5 ps . Trajectories were analyzed using a combination of in-house and VMD scripts . Overall <RMSD> variations were computed with VMD after superimposition of the Cα atoms of each conformation generated onto the initial structure ( last structure of the equilibration step ) . Flexible N- and C-terminal residues were not included in the calculation . Three types of RMSD were computed as it follows . For each frame , the XD protein was superimposed onto the initial XD model and RMSD was computed over XD Cα atoms only . For each frame the α–MoRE was superimposed onto the corresponding region of the initial structure and RMSD was computed over NTAIL Cα atoms only . For each frame , the XD protein was superimposed onto the initial XD protein and RMSD was computed over NTAIL Cα atoms only . Free-energy perturbation ( FEP ) module implemented in NAMD was used to perform alchemical transformation of Ser491 to Leu and Arg497 to Gly . Free energies differences resulting from the Ser to Leu or Arg to Gly substitution were computed using the thermodynamic cycle shown in S3 Fig . The free form of the α–MoRE in solution was taken from the XD/NTAIL complex . The free energy profile for the dissociation of the XD/α-MoRE complex ( wt and mutated forms ) was computed using the adaptive biasing force ( ABF ) method , implemented in NAMD [109] . This method relies upon the integration of the average force acting on a selected reaction coordinate ( here , the center of mass between the two partners ) . A biasing force is applied to the system in such a way that no average force acts along the reaction coordinate thus allowing overcoming free energy barriers . For a complete description of the method please refer to http://www . edam . uhp-nancy . fr/ABF/theory . html and references therein shown . The distance separating the centers of mass of the two proteins was selected as reaction coordinate . The distance was calculated on the Cα atoms not taking into account the three atoms at each end ( N-term and C-term end ) of each protein partner due to their high flexibility . This distance is about 11 Å in the associated form and the partners are considered dissociated after a 10 Å increase in this distance . The reaction coordinate was subdivided into sections of 0 . 5 Å and each one was successively explored during 5 ns . Bin width was kept at 0 . 02 Å , the number of samples prior to force application was 500 and the wall force constant is 100 kcal . mol-1 . Å2 . Once a section is sampled , the conformation in which COM distance is the nearest to the upper boundary is selected as the starting point of the following 0 . 5 Å section . A post-processing step merges the sampling counts and the PMF of each part and generates the whole profile of PMF along the dissociation process . The trajectories were generated using the same protocol as described for free MD . Cells were cultured in DMEM medium ( Life Technologies ) supplemented with 10% of heat-inactivated ( 30 min at 56°C ) fetal bovine serum , 1% L-glutamine , gentamicin ( 10 μg/ml ) at 37°C and 5% CO2 . Medium of 293-3-46 helper cells was supplemented with G418 at 1 . 2 mg/ml . Vero ( si2 ) and Vero-SLAM ( si1 ) cells stably expressing shRNA targeting the P and GFP mRNAs , respectively , were previously described [48] . To rescue recombinant viruses , the helper cell line 293-3-46 stably expressing T7 polymerase , MeV N , and P was transfected by using the ProFection kit with two plasmids coding for the MeV genome and MeV-L protein ( pEMC-La ) [110] . Three days after transfection , the cells were overlaid on either Vero ( single N gene virus ) or Vero-si2 cells ( bi-N virus ) . Upon appearance , isolated syncytia were picked and individually propagated on relevant Vero ( from CelluloNet BioBank BB-0033-00072 , SFR BioSciences , Lyon France ) ( single N virus ) or Vero-si2 ( bi-N virus ) cells . Virus stock was produced after a second passage at a multiplicity of infection ( MOI ) of 0 . 03 in the relevant cell line . This stock was checked to rule out mycoplasma contamination , has its N1 , N2 , P , M , and L genes sequenced , and was titrated on the relevant host cell before use . Gaussia princeps luciferase-based complementation assay and data analysis ( normalized luminescent ratio , NLR ) were performed according to [50] . Human 293T cells ( from CelluloNet BioBank BB-0033-00072 , SFR BioSciences , Lyon France ) were cultured in Dulbecco's Medium Eagle’s Modified ( DMEM ) ( Life Technologies ) supplemented with 10% of heat inactivated ( 30 min at 56°C ) fetal bovine serum , 1% L-Glutamine and 10 μg/ml gentamycin at 37°C and 5% CO2 . Cells were transfected using the jetPRIME reagent ( Polyplus transfection ) . NLR was calculated by dividing the luciferase value of the two chimeric partners by the sum of the luciferase value of every chimeric partner mixed with the other “empty” glu domain . Results were expressed as fold increase with respect to the reference NTAIL/XD , which was set to 1 . Parental Vero , si1 and si2 cells were infected at MOI 1 with recombinant viruses with or without addition of 10 μg/ml of fusion inhibitor peptide z-fFG to prevent syncytium formation . Virus production was measured after freeze-thaw cycles of infected cells using a 50% tissue culture infective dose ( TCID50 ) titration assay . Contamination of virus stock with internal deletion and copyback defective interfering ( DI ) minigenomes were assessed according to the method of [111] . Detection of the expression of viral N , Flag-N1 , HA-N2 , P and cellular GAPDH proteins was performed by Western blotting . Infected cells were lysed in NP40 buffer ( 20 mM Tris/HCl pH 8 , 150 mM NaCl , 0 . 6% NP-40 , 2 mM EDTA , protease cocktail inhibitor Complete 1 x ( Roche ) ) for 20 minutes on ice . The proteins were then separated from the cell debris by centrifugation at 15 , 000 g during 10 minutes . The proteins were denatured by the addition of Laemmli 1 x loading buffer before analysis by SDS-PAGE and immunoblotting using anti-N ( cl25 antibody ) , anti-Flag ( Sigma ) , anti-HA ( Sigma ) , anti-P ( 49 . 21 antibody ) and anti-GAPDH ( Mab374 , Chemicon ) monoclonal antibodies . Western blotting was revealed by chemiluminescence as detailed previously [48] . Quantification of the MeV genome and mRNA contents of infected cells was performed by reverse transcription-quantitative PCR essentially as described previously [65] , using the following primers . To quantify mRNA , sense N primer ( 5’-AAGAGATGGTAAGGAGGT-3’ ) , antisense N primer ( 5’-ATGATACTTGGGCTTGTC-3’ ) , sense P primer ( 5’-TGGACGGACCAGTTCCAGA-3’ ) , antisense P primer ( 5’-GGCTCCTTTGATATCATCAAG-3’ ) , sense F primer ( 5’-GCTCAGATAACAGCCGGCATT-3’ ) , antisense F primer ( 5’-AGCTTCTGGCCGATTA-3’ ) were used . Negative-strand genome was reverse transcribed using sense 5’-tagged N primer ( 5’-gcagggcaatctcacaatcaggAAGAGATGGTAAGGAGGT-3’ ) , and the cDNA was PCR quantified using sense tag primer ( 5’-gcagggcaatctcacaatcagg-3’ ) and antisense N primer . For the genome the results were expressed as copy number/μg RNA , and for transcripts the results were expressed either as the number of polymerized nucleotides/genome copy or as the viral transcript/μg RNA after normalization for the genome copy contents of each sample . The assay was performed essentially as described in [62 , 112] with minor modifications . 2 . 104 BSRT7 cells that constitutively express the T7 phage DNA-dependent RNA polymerase [113] were seeded in 96-well plates and transfected the day after with 66 ng of pEMC-N ( either wt or mutated ) 44 ng of pEMC- ( Flag/L+P ) ( a home-made T7-driven bicistronic construct ) [58] and 90 ng of plasmid encoding for the different minigenomes mixed with the transfection reagent as indicated in the manufacturer protocol ( jetPRIME Polyplus-transfection ) . Two days after transfection , Firefly and NanoLuc activity were measured using the Nano-Glo Dual-Luciferase Reporter Assay ( Promega ) . The background luciferase activity from of both luciferases observed in the absence of active L protein was subtracted from the signal measured in the presence of L , and data obtained from three independent experiments were normalized to each other to level the mean signal observed for all combinations tested at the same time . The percentage of unpriming per nucleotide of the un-transcribed intergenic ( UTIGR ) region ( %unpriming/UTIGRnt ) was calculated as follow . The luciferase signals ratios were plotted in relation to the length of the UTIGR region and the equation of the exponential regression curve was calculated ( y = b*ea ) . The %unpriming/UTIGRnt = 1-ea .
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Three proteins , the polymerase L , the phosphoprotein P and the nucleoprotein N , interplay to ensure transcription and replication of measles virus , a member of the Paramyxoviridae family . A regular array of nucleoprotein shields the viral genomic RNA . The resulting nucleocapsid constitutes the template of RNA synthesis used by the polymerase complex made of L and P , with the latter ensuring L anchoring onto the nucleocapsid . We herein report a correlation between the binding affinity of the C-terminal X domain of P ( XD ) and the intrinsically disordered C-terminal tail of N ( NTAIL ) , the ability to reinitiate the transcription at the intergenic regions and the accumulation rate of viral transcripts from recombinant viruses . We therefore propose that the NTAIL/XD interaction contributes to maintaining the polymerase complex anchored onto the nucleocapsid while ending the upstream transcript and re-initiating the downstream transcript at every intergenic region . As such , the NTAIL/XD interaction strength must be controlled so as to keep the viral transcription gradient within an optimal efficiency window . The conservation of this mode of interaction between the viral P and N proteins in many members of the Paramyxoviridae family reflects one of the major evolution constraints to which their polymerase machinery is subjected .
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[
"Abstract",
"Introduction",
"Results",
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2016
|
Modulation of Re-initiation of Measles Virus Transcription at Intergenic Regions by PXD to NTAIL Binding Strength
|
During the development of the visual system , high levels of energy are expended propelling axons from the retina to the brain . However , the role of intermediates of carbohydrate metabolism in the development of the visual system has been overlooked . Here , we report that the carbohydrate metabolites succinate and α-ketoglutarate ( α-KG ) and their respective receptor—GPR91 and GPR99—are involved in modulating retinal ganglion cell ( RGC ) projections toward the thalamus during visual system development . Using ex vivo and in vivo approaches , combined with pharmacological and genetic analyses , we revealed that GPR91 and GPR99 are expressed on axons of developing RGCs and have complementary roles during RGC axon growth in an extracellular signal–regulated kinases 1 and 2 ( ERK1/2 ) -dependent manner . However , they have no effects on axon guidance . These findings suggest an important role for these receptors during the establishment of the visual system and provide a foundational link between carbohydrate metabolism and axon growth .
GPR91 and GPR99 are G-protein-coupled receptors ( GPCRs ) activated by Krebs cycle intermediates , part of the larger class of carbohydrate metabolites—an observation that renewed interest in a biochemical pathway discovered decades ago [1 , 2] . GPR91 , through its activation by succinate outside the tricarboxylic acid ( TCA ) cycle , has a wide range of functions in diverse diseases , such as hypertension and diabetes . Its study allowed greater understanding of the molecular links between the TCA cycle and metabolic diseases [2 , 3] . The development of the visual system requires high levels of energy to propel mitochondrial-enriched axons properly through the nervous system , as retinal ganglion cells ( RGCs ) are essential for transmitting information from the retina to the brain . The growth and survival of neurons depend on mitochondria as they perform aerobic ATP synthesis and play a significant role in apoptotic and necrotic cell death [4] . Thus , failures of mitochondrial function appear to be involved in degenerative diseases of the nervous system [5] . One of the most mitochondria-enriched regions of the axon is the active growth cone ( GC ) at the tip of the axon [6] . The GC contains multiple receptors that interact with guidance molecules , allowing the front end of a developing axon to navigate through the complex landscape of the early nervous system toward its appropriate targets [7] . However , the role of intermediates from carbohydrate metabolism during the development of the visual system has not been well characterized . In the past decade , increasing evidence has highlighted GPCRs as mediators of both repulsive and attractive axon guidance , as their ligands may serve as guidance cues for axon pathfinding; however , GPCRs involved in axon growth still remain to be found [8–11] . In a groundbreaking study in 2004 , GPR91 ( succinate receptor 1 [Sucnr1] ) and GPR99 ( 2-oxoglutarate receptor 1 [Oxgr1] ) were both identified as receptors of the Krebs cycle intermediates succinate and α-ketoglutarate ( α-KG ) , respectively [2] . GPR91 and the closely related GPR99 are expressed in multiple tissues , such as the kidney [2 , 12] and cardiac muscle [13–15] . Previous reports have shown that succinate and GPR91 regulate normal retinal vascularization , proliferative ischemic retinopathy [16] , and cortical revascularization post-ischemia [17] . Moreover , through the activation of GPR91 , succinate has been shown to have an effect on motility , migration , and growth , as it directly promotes chemotaxis and potentiates activation initiated by Toll-like receptor agonists in dendritic cells [18 , 19] . However , to date , scarce literature exists on GPR99 functions . Human neuronal mapping and vascular innervation are closely related , as similar molecules and signaling mechanisms are shared between axon guidance , neuronal migration , and blood vessel guidance and growth . For example , the Slit/Robo pathway plays a critical role in both angiogenesis and the guidance of neuronal migration of the olfactory system [20 , 21] . Moreover , semaphorins and their receptors play a pivotal role as axon guidance cues [22 , 23] while also acting as a vasorepulsive force that misdirects new retinal vessels toward the vitreous in a murine model of oxygen-induced retinopathy [24] . Therefore , we investigated the growth-promoting actions and guidance effects of the carbohydrate metabolites succinate and α-KG , through their respective receptor GPR91 and GPR99 , during the establishment of the retino-thalamic pathway in an embryonic mouse model . Elucidating carbohydrate metabolite functions during visual development may provide crucial insights regarding their potential roles in the plasticity and regeneration of the nervous system and allow the development of further pharmacological tools , expanding and improving central and peripheral nervous system repair strategies .
We utilized murine retinas obtained from embryos ( embryonic day 14/15 [E14/15] ) to characterize the presence of GPR91 and GPR99 and their possible involvement during retinal projection navigation . At E14/15 , GPR91 and GPR99 proteins were mainly present in the ganglion cell layer but were also detected in the ganglion cell fiber and neuroblast layers ( Fig 1A–1F ) . The retinas from adult and E14/15 knockout ( KO ) mice ( gpr91KO or gpr99KO ) showed no expression of GPR91 or GPR99 , confirming the antibodies’ specificity ( S1A–S1H Fig ) . In E14/15 wild-type ( WT ) murine retinal explants , GPR91 and GPR99 were present in neurites , GCs , and filopodia , in dendrites and axons ( Fig 1G–1R and S1I–S1L Fig ) . Retinal explants obtained from gpr91KO and gpr99KO E14/15 embryos did not express GPR91 or GPR99 , respectively ( S1M–S1P Fig ) , which also confirms the specificity of the antibodies used in this study . Moreover , we observed the presence of GPR91 and GPR99 at the RGC layer of P1 Syrian golden hamsters ( S1Q–S1R Fig ) . As previous studies have shown that GPCRs are involved in axon guidance , we evaluated the roles of GPR91 and GPR99 on GC actions using retinal explants isolated from E14/15 mouse embryos after 2 days in vitro ( DIVs ) in culture . Explants treated for 60 min with the specific agonists succinate ( 100 μM ) or α-KG ( 200 μM ) showed a significant increase in the GC surface area and the number of filopodia , compared to controls ( Fig 2A–2C and S2A–S2D Fig ) . As expected , the effect of succinate on GC size and filopodia number was completely abolished in gpr91KO but not in gpr99KO mouse retinal explants , demonstrating a specific action of succinate on GPR91 ( Fig 2A–2C and S2A–S2D Fig ) . Similarly , α-KG effects were maintained in gpr91KO and decreased in gpr99KO . The effects of both agonists were abolished in the retinal explants from double-KO ( gpr91KO/gpr99KO ) mice ( Fig 2A–2C and S2A–S2D Fig ) . Moreover , following 60-min succinate ( 100 μM ) or α-KG ( 200 μM ) treatment , similar effects were observed on GC surface area and filopodia number of cortical neurons ( 2 DIVs ) ; these effects were also abolished in neurons lacking the expression of GPR91 and/or GPR99 ( S2E–S2G Fig ) . To further evaluate the effects of GPR91 and GPR99 ligand treatment on axon growth , retinal explants from WT mouse embryos were treated for 15 h with succinate ( 100 μM ) or α-KG ( 200 μM ) . Both agonists induced an increase in total neurite growth ( Fig 2D and 2E ) . Moreover , stimulation of gpr91KO murine retinal explants with α-KG and the stimulation of gpr99KO murine retinal explants with succinate also induced neurite growth ( Fig 2D and 2E ) . Again , the effects of succinate were essentially abolished in gpr91KO murine retinal explants , whereas the increased outgrowth produced by α-KG was markedly reduced in gpr99KO murine retinal explants . In double-KO murine retinal explants , the effect produced by either succinate or α-KG was abolished ( Fig 2D and 2E ) . To investigate whether the effects of intermediates of carbohydrate metabolism on GC morphology and neurite outgrowth could also affect cell viability , we treated murine embryonic retinal explants or cortical neurons with succinate or α-KG and then used a LIVE/DEAD assay to evaluate cell death . Following a 15-h treatment with succinate ( 100 μM ) or α-KG ( 200 μM ) , retinal explants or cortical neurons showed no differences in cell viability compared to control explants ( S3 Fig ) . However , we observed a high induction of cell death in the positive control condition of staurosporine-treated explants or neurons ( S3 Fig ) . Taken together , these results indicate that the Krebs cycle intermediates succinate and α-KG , via GPR91 and GPR99 , increase axon growth in retinal explants and modulate GC morphology in retinal explants and primary neurons . GPR91 is coupled to at least two signaling pathways , Gi/Go and Gq11 , whereas the activation of GPR99 by α-KG triggers a Gq-mediated pathway [2] . Moreover , previous reports have demonstrated that succinate activates the mitogen-activated protein kinase ( MAPK ) signaling pathways via GPR91 [2 , 12 , 13 , 18 , 19 , 25] . Since MAPKs mediate axon outgrowth , migration , and guidance [26] , we determined whether the effects observed with succinate/GPR91 and α-KG/GPR99 were mediated via the ERK1/2 pathway . ERK1/2 phosphorylation was significantly increased , both in vitro in neurons and ex vivo in retinal explants , following succinate and α-KG stimulation , while these effects were abrogated by CI-1040 , a selective ERK1/2 inhibitor ( Fig 3A , 3B and 3H ) . CI-1040 treatment also abolished succinate- and α-KG-induced increases in GC surface area and filopodia number ( Fig 3C–3E ) ; no significant differences were observed between the untreated control and a control pretreated with CI-1040 . Inhibition of ERK1/2 interfered with succinate- and α-KG-induced projection length ( Fig 3F and 3G ) , whereas CI-1040 treatment alone had no significant effect on the total projection length , as observed in control conditions . Moreover , CI-1040 treatment did not affect the viability of embryonic retinal explants and cortical neurons , as no significant neuronal cell death was observed compared to controls with the LIVE/DEAD assay ( S3 Fig ) . These data implicate the ERK1/2 pathway in the GPR91- and GPR99-induced modulation of GC morphology and axon outgrowth via their respective TCA cycle metabolite ligand . To determine the contribution of GPR91 and GPR99 to the development of retinal projections in vivo , E14/15 murine embryos received an intraocular injection of DiI ( DiIC18[3] [1 , 1’-dioctadecyl-3 , 3 , 3’ , 3’-tetramethylindocarbocyanine perchlorate] ) , a lipophilic tracer . After 7 d of tracer diffusion , surgery was performed to visualize the optic nerve , chiasm , and tract . The photomicrographs obtained revealed that genetic deletion of either GPR91 or GPR99 had no detrimental effects on RGC axon guidance , as axon steering at the optic chiasm , after a single genetic deletion of gpr91 or gpr99 , was similar to the WT group ( S4A and S4B Fig ) . Moreover , succinate and α-KG treatment also failed to modulate axon steering in time-lapse microscopy experiments performed on GCs from E14/15 WT murine retinal explants at 1 DIV ( S5A–S5E Fig ) . Microgradient application of succinate or α-KG did not induce any significant directional GC turning compared to the vehicle control ( S5A–S5E Fig ) . Interestingly , short-term exposure to succinate induced an increase in the growth of retinal axons , while α-KG exposure had no significant effects ( S5E Fig ) . However , in double-KO mice , few retinal axon fibers projected to the ipsilateral side of the brain although , some extended into the contralateral optic nerve . The concomitant absence of GPR91 and GPR99 appeared to induce some abnormal projections in the ipsilateral and contralateral sides of the optic chiasm , suggesting a potential compensatory role played by each receptor in the absence of the other ( S4A and S4B Fig ) . Moreover , to assess the involvement of the citric acid cycle intermediate receptors in retino-geniculate development , we examined the projections to the dorsal lateral geniculate nucleus ( dLGN ) of adult mice . Contralateral and ipsilateral projections in the dLGN from all genetically modified mouse strains occupied the same area as those of WT mice ( S4C Fig ) . These data indicate a similar overlap between contralateral and ipsilateral RGC projections in the dLGN for all mouse genotypes ( S4D Fig ) . Taken together , these observations demonstrate that GPR91 and GPR99 do not appear to be implicated in guidance and target selection during the development of the retinogeniculate pathway in vivo . To investigate the in vivo effects of intermediates of carbohydrate metabolism during the development of the visual system , the mouse model presents limitations . Because the mouse visual system is completed at birth [27] , we further utilized a different rodent model . The Syrian golden hamster has a shorter gestation period ( 15 d versus 18 . 5 d ) , and pups are born with a relatively premature visual system [27] . As the axons of RGCs reach their thalamic and midbrain targets at P3 in the hamster , this model allows examination of the induction of axon growth by different agonists [10 , 28] . Taking advantage of this observation , hamsters were injected intravitreally 24 h after birth ( P1 ) with a mixed solution of cholera toxin subunit B ( CTb ) with either 0 . 9% saline solution , 100 mM succinate , or 200 mM α-KG , and immunohistological analyses were performed at P5 . Intraocular injections of CTb produced intense labeling of thalamic and midbrain targets such as the dLGN and superior colliculus , making the evaluation of the collateral growth of RGC axons difficult . Thus , we evaluated the RGC branch growth at the dorsal terminal nucleus ( DTN ) , one of the nuclei composing the accessory visual pathway and involved in mediating visuomotor reflexes underlying the generation of optokinetic nystagmus [29] . Compared with the control group , unilateral intraocular injections of succinate or α-KG induced significant increases in RGC collateral axon projection length and branch number in the DTN ( Fig 4A–4C ) . We next proceeded to investigate the impact of genetic deletions of gpr91 and gpr99 on axon growth during development in vivo . Within 24 h of birth , pups from all 4 murine genotypes received a unilateral intraocular injection of CTb to label their retinal projections . At P5 , immunohistological experiments revealed the effects of GPR91 and GPR99 on RGC axon development . Investigating RGC branch growth at the DTN , we showed a significant decrease in the collateral projection lengths of the KO animals compared to the control group ( Fig 4D and 4E ) . In addition , axon collateral density was significantly decreased in gpr91KO , gpr99KO , and , to a greater extent , in double-KO mice , compared to WT controls ( Fig 4F ) . These findings demonstrate—for the first time , to our knowledge—the essential role of GPR91 and GPR99 in the growth of RGC projections .
Most functional studies of GPR91 and GPR99 , receptors of intermediates of carbohydrate metabolism , have been performed outside the central nervous system , primarily in the kidney and heart [2 , 14 , 15] . In the present study , we showed that GPR91 and GPR99 are expressed on axonal and dendritic projections , GCs and filopodia of murine embryonic retinal explants , and on retinal projections and cell body of RGCs during the development of the retinothalamic pathway . We demonstrated that succinate and α-KG increase ERK1/2 phosphorylation , corroborating a large number of studies on signaling pathways triggered by GPR91 [2 , 12 , 18 , 25] . Moreover , stimulation of both GPR91 and GPR99 resulted in the modulation of GC morphology and an increase in RGC axon growth in an ERK1/2-dependent manner . The increased GC size , number of filopodia , and growth of RGC axons following stimulation of GPR91 and GPR99 by succinate and α-KG , respectively , is the first report , to our knowledge , implicating these ligands and receptors in axon growth . Interestingly , the deletion of GPR91 completely blocked the effects of succinate but also partially abolished the effects observed with α-KG . Nevertheless , in double-KO animals , the effects of both succinate and α-KG were abrogated . These results tend to demonstrate that succinate’s effects on RGC axon growth were mediated only through GPR91 , while α-KG could , through an as-yet-unknown mechanism , activate both GPR91 and GPR99 . A possible mechanism could be the conversion of α-KG into succinate , since α-KG is a precursor of succinate in the Krebs cycle . Moreover , our findings showed that GPR91 and GPR99 , while having no effect on axon guidance , have complementary roles in RGC axon growth during development . These data are consistent with previous observations in which succinate , via GPR91 , has shown highly proliferative and stimulating vascular effects in different tissues [16 , 17] , to promote chemotaxis [19 , 30] and to potentiate the activation and aggregation of platelets [18 , 31] . Axon guidance and angiogenesis share several fundamental challenges during the formation of their extensive networks . Tip cells—specialized endothelial cells at the end of each vessel sprout—are motile and dynamically extend long filopodia protrusions reminiscent of axonal GCs [32] . In light of the spatiotemporal link between axon growth and angiogenesis , as well as the morphological similarities between endothelial tip cells and axonal GCs , the observed increase in the morphology of GC and neurite growth could be explained by a similar mechanism in the presence of succinate . As the only type of neuron that sends axons out of the retina , RGCs ensure the visual and cognitive processing of information from the outside world to the brain . A combination of intrinsic and extrinsic signals also plays an important role in driving the axons through the visual pathway via responsive GCs , which detect and effectively translate a multitude of external chemotactic cues . In the mouse , the axon decussation occurs at the level of the optic chiasm at around E14–16 [33] . We observed that in WT , gpr91KO , or gpr99KO mice , the optic chiasm appeared relatively normal , as the majority of the axons at the midline crossed to project contralaterally . Our results suggest that in the mouse visual system , the absence of either GPR91 or GPR99 is insufficient to affect decussation . Moreover , neither GPR91 nor GPR99 activity at the GC modulated axon turning in an ex vivo experiment of retinal explants , since GCs are not attracted nor repelled in the presence of a succinate or α-KG microgradient , whereas succinate induced significant axon extension . Based on these results , succinate plays an essential role in axon growth by increasing axon motility , but succinate and α-KG do not affect GC and axon guidance . However , the visual projections of double-KO mice showed some mild abnormalities in axon guidance that could be explained by a compensatory effect between the two receptors , which would allow a rescue of this mild phenotype in gpr91KO or gpr99KO mice . Nevertheless , further experiments are needed to study this subtle defect in a more quantitative fashion in order to draw significant conclusions . In addition , our data show that deletion of either GPR91 or GPR99 in vivo did not affect target selection of retinal projections . Indeed , during perinatal development , RGC axons connect with multiple targets in the dLGN , sharing common terminal space , while RGC axons occupy distinct eye-dependent nonoverlapping regions of the dLGN in the adult rodent . Eye-specific segregation only occurs during postnatal development [34] . Accordingly , a similar relative eye-specific segregation of retinal projections was observed in the adults of all 4 mouse genotypes . Thus , our in vivo results support previous ex vivo findings that GPR91 and GPR99 do not modulate RGC axon guidance and target selection during the establishment of the visual pathway . However , we demonstrated that TCA cycle intermediates induce axon growth in vivo during the development of the visual system , as intraocular injection of succinate and α-KG induced significant increases in RGC collateral axon projection length and branch number in the DTN . Moreover , accordingly , genetic interference with GPR91 or GPR99 activity profoundly affects retinal projection growth in the DTN . We showed a significant difference between WT , gpr91KO , and gpr99KO mice in axon projection length and branching at the DTN . Furthermore , the relative lack of growth of retinal projections in double-KO mice demonstrates the fundamental role played by GPR91 and GPR99 during RGC axon growth . Nonetheless , these in vivo experiments do not conclude that the receptors involved in the growth-promoting actions of intermediates of carbohydrate metabolism are only those expressed at the GCs but could also be , to some extent , those expressed throughout the projections or on the cell body of RGCs as well . The levels of intermediates of carbohydrate metabolism adapt depending on tissue needs and the conditions in the surrounding regions . Investigating RGC projections and GC actions in the developing visual system faces technical limitations regarding intermediates of carbohydrate metabolism dosing . The amount of tissue needed ( and its isolation ) from mouse embryos or hamster newborn pups does not allow detection of metabolites due to the technique sensitivity and the rapid turnover of the metabolites . Nevertheless , based on previous published data and our own findings , we sought to avoid nonspecific responses by determining the lowest responsive doses for succinate and α-KG in our system , even if the physiological levels could not be measured [2 , 3 , 16–18] . In summary , this study demonstrates—for the first time , to our knowledge—a role for the intermediates of carbohydrate metabolism succinate and α-KG and their respective receptor GPR91 and GPR99 in axon growth during development in vivo . These receptors mediate axon growth in an ERK1/2-dependent manner , although succinate and α-KG have no effect on axon guidance . Moreover , these findings suggest a potential link between mitochondria and axon growth in development , outside the strict production of energy . This study not only demonstrates a new role for TCA cycle intermediates in the visual system development but also provides a foundation for the investigation of metabolite receptors in the visual , central , and peripheral nervous system development . This novel concept also provides new avenues for the elaboration of effective therapies aimed at the development and regeneration of the nervous system .
All experimental procedures were approved by the Animal Care Committee of Sainte-Justine’s Hospital Research Center or the relevant University of Montreal animal care committee’s regulations and were conducted in accordance with the Association for Research in Vision and Ophthalmology statement regarding the use of animals in ophthalmic and vision research and the guidelines established by the Canadian Council on Animal Care . The C57BL/6 WT control mice were purchased from Jackson Laboratory . Syrian golden hamsters ( Charles River Laboratories , Saint-Constant , Canada ) were used in this study . Sucnr1KO mice , generated by Deltagen through partial replacement of exon 2 ( 5’-GGCTACCTCTTCTGCAT-3’ ) with a lacZ-neomycin cassette , were generously provided by Dr . José M . Carbadillo at Norvartis Institutes for Biomedical Research , Vienna , Austria [19] . As described by Rubic and colleagues in 2008 , correctly targeted 129/OlaHsd embryonic stem cells were used for the generation of chimeric mice , which were crossed with C57BL/6 ( called “WT” here ) . F1 mice with germline transmission of the mutated gene were further backcrossed with WT mice for 10 generations ( in specific pathogen-free conditions at the Novartis Institutes for Biomedical Research , Vienna ) before being intercrossed to produce homozygous gpr91KO mice . gpr91KO mice were healthy and bred normally when maintained in specific pathogen-free conditions . All experiments in the production of the gpr91KO mice were conducted in accordance with Austrian Law on Animal Experimentation and the Novartis Animal Welfare Policy . All procedures were approved by the local government and the animal care and user committee of the Novartis Institutes for Biomedical Research , Vienna . Heterozygous ( GPR99+/− ) mice with mixed genetic background ( C57BL/6J− Tyrc-Brd x 129 Sv/EvBrd ) were developed and generously provided by Lexicon Pharmaceuticals Incorporated ( The Woodlands , TX ) . The full-length gpr99 gene was removed by homologous recombination as the PCR-generated selection cassette was introduced in a murine genomic clone by yeast recombination , followed by the electroporation of the linearized targeting vector in 129 Sv/EvBrd embryonic stem cells . In selected clones , gpr99 deletion was confirmed by Southern hybridization followed by their injection into C57BL/6J-Tyrc-Brd blastocysts . To generate F1 heterozygous offspring , the resulting chimeras were backcrossed to C57BL/6J-Tyrc-Brd . Heterozygous mice were intercrossed to generate WT control ( gpr99WT ) , homozygous-null ( gpr99KO ) , and heterozygous littermates , consistent with Mendelian ratios . The resulting homozygous-null gpr99KO mice were backcrossed onto the C57BL/6 background with C57BL/6 obtained from Jackson Laboratory ( Connecticut , USA ) for 10 generations in CHU Sainte-Justine’s Research Center animal facility before using them in experiments . The gpr99KO mice were viable , healthy , and bred normally when maintained in specific pathogen-free conditions . gpr99KO / gpr91KO mice ( double KO ) were generated by crossing gpr99KO and gpr91KO mice to produce gpr99+/− / gpr91+/− ( double-heterozygous ) parents . The double-heterozygous parents were then crossed together until we obtained double-KO gpr99KO / gpr91KO ( 1:16 pups according to Punnett Square ) male and female mice that were then crossed together to obtain a stable double-KO mouse lineage . The double-KO mice were viable , healthy , and bred normally when maintained in specific pathogen-free conditions . Mice were genotyped by PCR reactions of tail genomic DNA using specific primers for either the WT or mutant allele . For GPR91 mice , the primer pair WT-F: 5′-GTTCATTTTTGGACTGCTTGGG-3′ and WT-R: 5′-AATGGCAAATTCCTTCTTTTGTAGA-3′ generated a GPR91-specific fragment only present in the WT allele , while the primer pair KO-F: 5′- GGCACATATCGGTTGCTTATACAGA-3′ and KO-R: 5′- GGGTGGGATTAGATAAATGCCTGCTCT-3′ amplified a fragment specific to the selection cassette of the gpr91KO mutant allele . For GPR99 mice , a GPR99-specific fragment present in the WT but absent in the mutant allele was generated using the specific primer pair UTT069-21 ( 5′-GAGCCATGATTGAGCCACTG-3′ ) and UTT069-25 ( 5′-CACCACTGGCATAGTAATGG-3′ ) . Another primer pair amplified a fragment specific to the selection cassette of the gpr99KO mutant allele: UTT069-3 ( 5′-CAGAGCCATGCCTACGAG-3′ ) and GT ( 5′-CCCTAGGAATGCTCGTCAAGA-3′ ) . For double-KO mice , all pairs of primers were used ( 4 reactions ) to determine whether both genetic modifications were present . BSA , ciliary neurotrophic factor , DNase , forskolin , Hoechst 33258 , insulin , laminin , poly-D-lysine , progesterone , selenium , putrescine , succinate , α-KG , trypsin , and triiodothyronine were purchased from Sigma Aldrich ( Oakville , ON , Canada ) . B27 , N2 , Dulbecco’s phosphate-buffered saline , FBS , glutamine , Neurobasal medium , penicillin-streptomycin , Minimum Essential Medium Eagle Spinner Modification ( S-MEM ) , and sodium pyruvate were purchased from Life Technologies ( Burlington , ON , Canada ) . The standard donkey and goat sera were from Jackson ImmunoResearch ( West Grove , PA , USA ) . ERK1/2 inhibitor ( CI-1040 ) was obtained from Selleck Chemicals ( Houston , TX , USA ) . LNAC was acquired from EMD ( La Jolla , CA , USA ) . The CTb was from List Biological Laboratories ( Campbell , CA , USA ) . Triton X-100 was purchased from US Biological Life Sciences ( Salem , MA , USA ) . DiI stain was obtained from Molecular probes ( Eugene , OR , USA ) . Adult mice and P1 hamsters were euthanized by an overdose of isoflurane . Transcardiac perfusion was conducted with phosphate-buffered 0 . 9% saline ( PBS; 0 . 1 M , pH 7 . 4 ) , followed by 4% formaldehyde in PBS , until the head was fixed . The nasal part of the eyes of murine embryos and adult mice was marked with a suture and removed . Two small holes were made in the cornea before a first postfixation step in formaldehyde for a period of 30 min . The cornea and lens were removed , and the eyecups were postfixed for 30 min in formaldehyde . The eyecups were then washed in PBS , cryoprotected in 30% sucrose overnight , embedded in NEG 50 tissue Embedding Media ( Thermo Fisher Scientific Burlington , ON , Canada ) , flash-frozen , and kept at −80 °C . Sections ( 14-μm thick ) were cut with a cryostat ( Leica Microsystems , Concord , ON , Canada ) and placed on gelatin/chromium-coated slides . Retinal sections were washed in 0 . 1 M PBS , postfixed for 5 min in a 70% solution of ethanol , rinsed in 0 . 03% Triton X-100 in PBS , and blocked in 10% normal donkey serum and 0 . 5% Triton X-100 in PBS for 1 h . The sections were then incubated overnight with antibodies against GPR91 or GPR99 . The antibody Brn-3a was also used as a specific marker for RGCs . After incubation with the primary antibodies , the sections were washed in PBS , blocked for 30 min , and incubated for 1 h with the secondary antibodies Alexa Fluor 647 donkey anti-rabbit and Alexa Fluor 488 donkey anti-mouse . After washing , the sections were mounted using a homemade PVA-Dabco medium . The specifications of all the antibodies used in this study are detailed in S1 Table . Images of the central retina ( within 200 μm of the optic nerve head ) were taken using a laser scanning confocal microscope ( TCS SP2 , Leica Microsystems ) with a 40X ( NA: 1 . 25 ) oil immersion objective and 488 and 633 nm lasers . Image stacks ( 1 , 024 × 1 , 024 pixels × 0 . 5 μm per stack ) were captured with a frame average of 3 using the LCS software ( version 2 . 6 . 1; Leica Microsystems ) . The stacks were taken sequentially and in distant wavelengths to ensure no “bleed through” between channels and were collapsed into projection images . All images in which labeling intensities were compared were obtained under identical conditions of gain intensity . Because gray-scale photographs provide better contrast and more detail , individual channels are presented in gray scale , and the merged images are presented in color . The retinas were isolated from E14/15 mouse embryos , dissected into small segments in ice-cold Dulbecco’s phosphate-buffered saline , and plated on 12-mm glass coverslips previously coated with poly-D-Lysine ( 20 μg/ml ) and laminin ( 5 μg/ml ) in 24-well plates . The explants were cultured in Neurobasal supplemented with 100 U/ml penicillin , 100 μg/ml streptomycin , 5 μg/ml LNAC , 1% B27 , 40 ng/ml selenium , 16 μg/ml putrescine , 0 . 04 ng/ml triiodo-thyronine , 100 μg/ml transferrin , 60 ng/ml progesterone , 100 μg/ml BSA , 1 mM sodium pyruvate , 2 mM glutamine , 10 ng/ml ciliary neurotrophic factor , 5 μg/ml insulin , and 10 μM forskolin at 37 °C and 5% CO2 . At 0 DIV , 1 h following plating , the explants were treated for 15 h for projection analysis or for 1 h at 1 DIV for GC analysis . The photomicrographs were taken using an Olympus IX71 microscope ( Olympus , Markham , ON , Canada ) and analyzed with Image-Pro Plus 5 . 1 software ( Media Cybernetics , Bethesda , MD , USA ) . The total length of axon bundles was quantified and expressed as the mean ± SEM . Statistical significance of differences between means was evaluated by analysis of variance ( ANOVA ) with Bonferroni’s post-hoc test ( Systat Software Inc , Chicago , IL , USA ) . Primary cortical neurons were used in this study because of the large number of neurons that can easily be cultured and harvested for biochemical assays , which is hardly possible with RGCs . C57BL/6 WT , gpr91KO , gpr99KO , and double-KO pregnant mice were used . Brains from E14/15 embryos were dissected , and the superior layer of each cortex was isolated and transferred in 2 ml S-MEM containing 2 . 5% trypsin and 2 mg/ml DNase and incubated at 37 °C for 15 min . The pellet was transferred into 10 ml S-MEM with 10% FBS and stored at 4 °C . After centrifugation , the pellet was again transferred in 2 ml S-MEM supplemented with 10% FBS and triturated 3 to 4 times . The supernatant was transferred in 10 ml Neurobasal medium . Dissociated neurons were counted and plated at 50 , 000 cells per well on 12 mm glass coverslips previously coated with poly-D-lysine ( 20 μg/ml ) for immunocytochemistry or at 250 , 000 cells per 35 mm petri dish for western blot . Neurons were cultured for 2 d in Neurobasal medium supplemented with 1% B-27 , 100 U/ml penicillin , 100 μg/ml streptomycin , 0 . 25% N2 , and 0 . 5 mM glutamine . They were then treated with either a GPR91 agonist ( 100 μM succinate ) , GPR99 agonist ( 200 μM αKG ) , or ERK1/2 inhibitor ( 20 μM CI-1040 ) for 1 h to study GC morphology or 2 , 5 , and 15 min for ERK1/2 quantification using western blot analysis . LIVE/DEAD cell viability assay: Cell viability was assessed with the LIVE/DEAD assay using an ethidium homodimer/calcein acetoxy methyl ester ( L-3224 , Molecular Probes , Eugene , OR , USA ) combination of vital dyes , as previously described [35 , 36] . Staurosporine ( 5 μM ) , an inducer of apoptotic cell death , was used as a positive control [37] . After treatment , retinal explants and primary cortical neuron cultures were washed with PBS ( pH 7 . 4 ) , fixed in 4% formaldehyde ( pH 7 . 4 ) , and blocked with 2% normal goat serum ( NGS ) and 2% BSA in PBS containing 0 . 1% Tween 20 ( pH 7 . 4 ) for 30 min at room temperature . The samples were then incubated overnight at 4 °C in a blocking solution containing anti-GAP-43 , anti-GPR91 , anti-GPR99 , anti-MAP2 , or anti-NFM . The following day , the samples were washed and labeled with Alexa Fluor 488 and 555 secondary antibodies and Hoechst 33258 ( 1:10 , 000 ) , and the coverslips were mounted with a homemade PVA-Dabco medium [38] . Primary cortical neurons were cultured for 2 DIVs at a density of approximately 250 , 000 cells/dish in 35 mm poly-D-lysine-coated petri dishes . Following treatment , neurons were washed once with ice-cold PBS ( pH 7 . 4 ) and then lysed with Laemmli sample buffer . Thirty micrograms of protein/sample of the homogenate were resolved with 12% SDS-polyacrylamide gel electrophoresis , transferred onto a nitrocellulose membrane , blocked with 5% BSA , and incubated overnight with antibodies directed against ERK1/2 , p-ERK1/2 , and β-actin , the latter serving as a loading control . The blots were exposed to the appropriate HRP-coupled secondary antibodies ( Jackson Immunoresearch Laboratories , West Grove , PA , USA ) . Detection was performed using homemade enhanced chemiluminescence western blotting detection reagent ( final concentrations: 2 . 5 mM luminol , 0 . 4 mM p-coumaric acid , 0 . 1 M Tris-HCl [pH 8 . 5] , 0 . 018% H2O2 ) . Embryonic retinal explants were cultured on a coverglass in a borosilicate chamber ( Lab-Tek; Rochester , NY , USA ) for 2 DIVs and placed in an incubator mounted on an inverted microscope ( Olympus IX71 ) . They were maintained at 37 °C and 5% CO2 with a live cell chamber ( Neve Bioscience , Camp Hill , PA , USA ) throughout the whole experiment . A microgradient was created using a Picoplus micro-injector ( Harvard Apparatus , St-Laurent , QC , Canada ) . Glass micropipettes with a tip of 2–3 μm diameter were positioned at 45° and at 100 μm away from the GC of interest , as described previously [8 , 10 , 11] . Syrian golden hamsters ( Charles River ) were used for investigating the in vivo implication of succinate/GPR91 and α-KG/GPR99 in RGC projection growth during postnatal development . At P1 , 24 h after birth , anesthetized hamsters received a unilateral injection of 2 μl solution of CTb with either 0 . 9% saline solution , succinate ( 100 mM ) , or α-KG ( 200 mM ) . Briefly , under an operating microscope , a small incision was made in the eyelids to access the right eye . The injections were administered using a glass micropipette attached to a 10 μl Hamilton syringe . The micropipette was carefully inserted into the vitreous at an angle to avoid damage to the lens . Following the injection , the eyelids were closed with surgical glue ( Vetbond; 3M ) . At P5 , 4 d after the injection , hamsters were anesthetized and perfused transcardially with 0 . 1 M PBS , pH 7 . 4 , followed by 4% PFA in PBS . The brains were removed , postfixed overnight at 4 °C and cryoprotected with sucrose . Then , brains were frozen and kept at −80 °C until processing by immunohistochemistry according to a protocol previously described by Argaw and colleagues in 2011 [8] . Briefly , 40 μm—thick coronal sections of tissue were incubated in 90% methanol and 0 . 3% H2O2 in 0 . 1 m PBS , pH 7 . 4 , for 20 min . They were then rinsed and incubated in 0 . 1 M glycine/PBS for 30 min , followed by an overnight incubation ( 4 °C ) in PBS containing 4% NDS , 2 . 5% BSA , and 1% Triton X-100 . The sections were subsequently rinsed and immersed for 48 h at room temperature in a solution containing goat anti-CTb diluted 1:4 , 000 in PBS with 2% NDS , 2 . 5% BSA , and 2% Triton X-100 . Afterward , the sections were rinsed and incubated in 2% NDS and 2 . 5% BSA/PBS for 10 min . This was followed by a 1 h incubation in donkey anti-goat biotinylated secondary antibody diluted 1:200 in PBS with 2% NDS , 2 . 5% BSA , and 1% Triton X-100 . Tissues were rinsed , incubated in 2% NDS and 2 . 5% BSA in PBS for 10 min , and subsequently processed with an avidin-biotin-peroxidase complex ABC Kit ( diluted 1:100 in PBS ) for 1 h in the dark at room temperature . The sections were then rinsed and preincubated in 3 , 3′-diaminobenzidine tetrahydrochloride ( DAB ) in PBS for 5 min . The peroxidase reaction product was visualized by adding 0 . 004% H2O2 to the DAB solution for 2–4 min . Sections were finally washed 5 times ( 1 min each ) with PBS , mounted on gelatin-chromium alum-subbed slides , air-dried , dehydrated in ethanol , cleared in xylenes , and mounted on coverslips with Depex ( EMS ) . After 14–15 d of gestation , pregnant mice ( WT , gpr91KO , gpr99KO , and double KO ) were euthanized , and the embryos were removed . The lambdoid sutures of the embryos were incised , and the occipital bones were removed to expose the brain to the fixative ( 4% formaldehyde ) , where they were placed for 1 wk at 4 °C until tracing with DiI . For complete optic nerve labeling , 1 eye of each embryo was enucleated and crystals of DiI implanted unilaterally into the optic disk . Embryos were incubated at 37 °C in 4% formaldehyde for 7 d . Tissue clearing was performed according to Hama and colleagues ( 2011 ) [39] . Briefly , embryos were incubated for 2 d in Scale A2 solution ( 4 M urea , 10% glycerol , 0 . 1% Triton X-100 , in water ) followed by 2 d in Scale B4 solution ( 8 M urea , 0 . 1% Triton X-100 , in water ) and then to a fresh Scale A2 solution for 1 wk to complete the clearing [39] . The brains were then carefully removed with their optic nerves , and the proximal visual system was imaged with a fluorescence microscope to allow the observation of subtle guidance defects at the optic chiasm . For eye-specific segregation studies in the dLGN , C57BL/6 WT , gpr91KO , gpr99KO , and double-KO adult mice received an intraocular injection of CTb conjugated to Alexa Fluor 555 into the left eye and CTb coupled to Alexa Fluor 488 into the right eye ( 2 μl; 0 . 5% in sterile saline ) . Four days after the injection , the animals were anesthetized and perfused transcardially with 0 . 1 M PBS ( pH 7 . 4 ) followed by 4% formaldehyde . The brains were removed , postfixed overnight at 4 °C , cryoprotected , frozen , and kept at −80 °C . Retinal projections marked with the CTb were visualized on brain sections washed 5 times ( 1 min each ) with PBS , mounted on gelatin-chromium alum-subbed slides , air-dried , and mounted on coverslips with DEPEX ( EMS , Hatfield , PA , USA ) . The photomicrographs of the optic chiasm were taken with an IX71 microscope ( Olympus , Richmond Hill , ON , Canada ) , an Evolution VF camera ( Media Cybernetics , Warrendale , PA , USA ) and Image-Pro Plus 5 . 1 image analysis software . Universal gains and exposures were established for each labeling . Raw images of the dLGN were imported to MATLAB ( Natick , MA , USA ) , and an area of interest comprising the dLGN was cropped , excluding the ventral lateral geniculate nucleus and the intergeniculate leaflet . Then , the degree of left and right eye projection overlap was quantified using an established multithreshold method of analysis [40–42] . This approach allows for a better analysis of overlapping regions independent of the threshold . For these experiments , an observer “blind” to the experimental conditions to avoid any bias performed the quantification . Values are expressed as the means ± SEM . The significance of differences between means was evaluated by Student t test analysis ( Systat ) . To assess axon growth in vivo , photomicrographs of the DTN of mice and P5 hamsters were taken with a microscope ( Leica Microsystems , Concord , ON , Canada ) coupled to an Evolution VF camera ( Media Cybernetics ) . The images were quantified using Image-Pro Plus 5 . 1 software . The growth of axon branches was quantified on consecutive photomicrographs of coronal slices of brain tissue comprising the DTN . On each photomicrograph , the distance between the lateral border of the DTN and the tips of the longest axon branches was measured . To take into account brain size differences , axon branch lengths were normalized with the interthalamic distance ( distance between the right and left lateral borders of the thalamus; see S6A Fig for a schematic representation of such quantification ) . Axon collateral number was quantified on consecutive photomicrographs comprising the DTN using an adaptation of the Sholl technique [43] , as described by Duff and colleagues in 2013 [11] and illustrated in S6B Fig . Values are expressed as the means ± SEM . The significance of differences between means was evaluated by ANOVA with Bonferroni’s post-hoc test ( Systat ) .
|
Development of the visual system requires high levels of energy and tight regulation of multiple factors integrated by axon projections during navigation to their appropriate targets . While intermediates of carbohydrate metabolism have key roles in many biological processes , much less is known about their effects on receptors in the developing nervous system . We hypothesized that activation of two G-protein-coupled receptors ( GPCRs ) by metabolic intermediates could promote growth during retinal ganglion cell ( RGC ) axon extension and guidance from the retina to the brain . We first demonstrated that receptors for two intermediates of carbohydrate metabolism—succinate and α-ketoglutarate ( α-KG ) —are expressed on developing RGCs and their projections . We revealed that these receptors have a complementary role in regulating axon growth in an extracellular signal–regulated kinases 1 and 2 ( ERK1/2 ) -dependent manner , although with no effect on axon guidance . The absence of either receptor caused a strong decline in axonal projections from the retina to the thalamus , while the combined absence of both receptors had an additive effect . Taken together , our findings indicate , for the first time , an important role for intermediates of carbohydrate metabolism and their receptors in stimulating axon growth during the establishment of the visual system and suggest a wider involvement in the nervous system development .
|
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2018
|
Receptors of intermediates of carbohydrate metabolism, GPR91 and GPR99, mediate axon growth
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Human African Trypanosomiasis ( HAT ) is a neglected tropical disease caused by infections due to Trypanosoma brucei subspecies . In addition to the well-established environmental and behavioural risks of becoming infected , there is evidence for a genetic component to the response to trypanosome infection . We undertook a candidate gene case-control study to investigate genetic associations further . We genotyped one polymorphism in each of seven genes ( IL1A , IL1RN , IL4RN , IL6 , HP , HPR , and HLA-G ) in 73 cases and 250 controls collected from 19 ethno-linguistic subgroups stratified into three major ethno-linguistic groups , 2 pooled ethno-linguistic groups and 11 ethno-linguistic subgroups from three Cameroonian HAT foci . The seven polymorphic loci tested consisted of three SNPs , three variable numbers of tandem repeat ( VNTR ) and one INDEL . We found that the genotype ( TT ) and minor allele ( T ) of IL1A gene as well as the genotype 1A3A of IL1RN were associated with an increased risk of getting Trypanosoma brucei gambiense and develop HAT when all data were analysed together and also when stratified by the three major ethno-linguistic groups , 2 pooled ethno-linguistic subgroups and 11 ethno-linguistic subgroups . This study revealed that one SNP rs1800794 of IL1A and one VNTR rs2234663 of IL1RN were associated with the increased risk to be infected by Trypanosoma brucei gambiense and develop sleeping sickness in southern Cameroon . The minor allele T and the genotype TT of SNP rs1800794 in IL1A as well as the genotype 1A3A of IL1RN rs2234663 VNTR seem to increase the risk of getting Trypanosoma brucei gambiense infections and develop sleeping sickness in southern Cameroon .
Human African Trypanosomiasis ( HAT ) , or sleeping sickness , is a parasitic infection caused by flagellated parasites of the genus Trypanosoma . The parasites belong to Trypanosoma brucei complex which is subdivided into three subspecies: Trypanosoma brucei gambiense ( Dutton , 1902 ) is responsible for the chronic form of the disease in West and Central Africa , T . b . rhodesiense ( Stephen and Fantham , 1910 ) causes the acute form of HAT in East and South Africa whilst T . b . brucei is only infective to animals . These trypanosomes are transmitted through the bites of haematophagous flies of the genus Glossina commonly known as tsetse flies [1 , 2] . HAT was considered to be under control during the 1960s , but the disease has re-emerged in the last decades as a public health problem in many sub-Saharan African countries due to the abandonment of control measures after independence and also to socio-political and environmental upheavals [2] . HAT is often fatal unless treated and is endemic in 36 sub-Saharan Africa countries with about 65 million people in more than 250 foci exposed to the risks of infections [3] . Currently , more than 98% of the reported cases are due to T . b . gambiense infection [3] . Control efforts undertaken by the national sleeping sickness control programs have succeeded in considerably reducing the number of cases , and less than 2200 new cases were officially reported in 2016 [4] . Sleeping sickness has been included in the WHO roadmap for neglected tropical diseases with elimination as a public health problem targeted for 2020 , and the interruption of transmission to humans for 2030 . To achieve the elimination and interruption goals , it is important to identify and gain a better understanding of the clinical evolution of the disease and the factors that may hamper this goal . Addressing the contribution of human genetics to the response to T . b . gambiense infections is important for the development of new control strategies because a range of clinical presentations of HAT including asymptomatic carriers and spontaneous cure without treatment have been reported in West Africa [5] . Understanding the genetic bases of these new disease profiles may help to identify more susceptible populations for more effective control operation . Previous studies have identified polymorphisms in APOL1 , IL6 , HLA-G and HP/HPR that regulate the human susceptibility to trypanosome infections [6 , 7 , 8 , 9 , 10 , 11 , 12 , 13] . Most of these genes seem to play important roles during T . b . gambiense infection [14] . For instance , HLA-G has been reported to be involved in HAT progression . In addition , IL1 participates in macrophage activation during early T . b . gambiense infection in mice [15] . It also plays a key role in the recruitment of leukocytes into the CNS during T . b . gambiense infections [16 , 17] . However , contrasting results on the association between gene polymorphisms and the risk to be infected by T . b . gambiense and develop HAT have been reported between countries and therefore , efforts are needed to better understand the genetic bases of human susceptibility to T . b . gambiense infections . In this current study , polymorphisms in seven genes were genotyped to identify any association with HAT . Our data suggest that the association between host genetic determinants and the susceptibility to be infected by T . b . gambiense and develop sleeping sickness could vary according to the population studied .
This study was conducted in three active sleeping sickness foci in the forest region of Southern Cameroon . The three HAT foci were Bipindi and Campo in the Southern region and Fontem in the South-west region of Cameroon . The Campo focus ( 2°82'00"N , 9°85'20"E ) is located in the equatorial forest and extends from the Atlantic coast along the Ntem river which delimits the Cameroon–Equatorial Guinea border . It is a hypo-endemic focus where no epidemic outbreak has been observed for many decades [18] . It is a cosmopolitan area with several ethnic groups ( mainly the Iyassa , Kwasse , Maabi , Mvae and Ngoumba ) with most of them speaking Bantu family languages . Other minor ethnic groups are semi Bantus , Sao-Sudanese and Baka [19] . The Bipindi HAT focus ( 3°82'00"N , 10°82'20"E ) is located at about 75 km from the Atlantic coast in the South of Cameroon . Bipindi has been known as a HAT focus since 1920 . During the last two decades , it was among the most active HAT foci of Cameroon with about 83 HAT cases diagnosed from 1999 to 2011 [19] . About 95% of the inhabitants of the Bipindi HAT focus are Bantu speakers and the majority belong to the Ngoumba , Nti and Fan . The remaining 5% of inhabitants are Baka , semi Bantus and Sao-Sudanese speakers . The Fontem focus ( 5°40’00”N , 9°55’00”E ) is located in the South-West Region of Cameroon where HAT has been known to occur since 1949 [20] . It was previously among the most active HAT foci of Cameroon [21] , but in recent decades , it has become hypo-endemic with about 8 patients detected among 16 , 000 persons examined between 1998 and 2007 [22] . In this focus , the Mundani and Banyangi are the major ethnic groups . Other minor ethnic groups such as Bangwa and Bamileke are also found . The Cameroonian population is made up of more than 250 ethno-linguistic subgroups from three major ethnic groups: Bantu ( e . g . : Bulu , Bassa , Bakundu , Maka , Douala ) , Semi Bantu ( e . g . : Bamileke , Gbaya , Bamoun , Tikar ) and Sudano-Sao ( e . g . : Fulbe , Mafa , Toupouri , Shoa-Arabs , Moundang , Massa , Mousgoum ) [11] ( S1 Table ) . Beside these three groups , some minor groups exist such as the Baka who generally speak the Bantu languages but who are not closely related to any of these three major groups [23] . The ethnic composition varies considerably between regions , HAT foci and even within the same HAT focus . The protocol of this study was approved by the Ethical Committee of the Ministry of Public Health of Cameroon on 21 November 2013 with a reference number N°2013/11/364/L/CNERSH/SP . The local administrative and traditional authorities of each HAT focus were also informed and gave their approval . Subsequently , the review board of the Laboratory of Microbiology and Anti-microbial Substances ( LAMAS ) of the Department of Biochemistry of the Faculty of Science of the University of Dschang gave its approval . All adult subjects provided informed consent , and a parent or guardian of any child participant below 18 years old provided informed consent on their behalf . Each informed consent was written because all individuals enrolled in this study gave their approval by signing an informed consent form and a Certificate of Confidentiality . In addition , an assent form was also signed by children below 18 years old . During analyses , data for each subject were anonymized . Blood samples were collected during medical surveys performed jointly with the National Sleeping Sickness Control Program of Cameroon and the research team of the molecular parasitology and entomology unit of the University of Dschang . The sampling was performed in Campo in 2014 and 2017 , in Bipindi in 2015 and 2017 , and in Fontem in 2015 . During these surveys , all participants at risk were tested using the Card Agglutination Test for Trypanosomiasis ( CATT ) . It was performed on blood collected by finger prick [24] . This immunological test was carried out to screen people who have been in contact with T . b . gambiense . It was initially performed on whole blood as described by Magnus et al . [24] . For all participants with a positive CATT on whole blood , blood sample was collected in EDTA tubes and a two-fold plasma dilution series in CATT buffer was tested to assess the end titer , i . e . the highest dilution still positive on plasma ( CATT-P ) . All individuals with CATT dilution on plasma≥1/8 underwent parasitological examinations by direct examination using the capillary tube centrifugation ( CTC ) [25] and mini-anion exchange centrifugation technique ( mAECT ) [26] . Beside the CTC and mAECT , lymph node aspiration followed by a microscopic examination was performed to search for trypanosomes in all individuals showing enlarged lymph nodes . All controls and participants with a CATT dilution ≥1/8 and negative for parasitological tests were subjected to the trypanolysis test in order to confirm their status [27] . Ninety micro-liters of plasma sample from each control and each individual with CATT dilution ≥1/8 and negative for parasitological tests were spotted on a Whatman paper disc ( divided in three equal parts with each bearing a spot of 30μl ) that was sent to the “Centre International de Recherche-Développement sur l’Élevage en Zones Sub-humides ( CIRDES , Bobo-Dioulasso , Burkina Faso ) ” . Each plasma sample was tested by the immune trypanolysis test as described by Jamonneau et al . [27] . It is the highly specific test for T . b . gambiense and constitutes a routine test for the surveillance of HAT . This test was performed on plasma as previously described by Van Meirvenne et al . [28] with LiTat 1 . 3 , 1 . 5 , and 1 . 6 variable antigen types ( VAT ) . During medical surveys , each new HAT case was defined as an individual in whom trypanosomes were seen by at least one parasitological method . Old HAT cases were also sampled . They were residents in whom trypanosomes had been previously seen by at least one parasitological test after passive or active case detection . Old HAT cases were included only if the information regarding the clinical status , the CATT and all parasitological tests were available in hospital records and in the National control program register . Each HAT case was matched to at least three controls . This matching was done by age , sex , occupation and when possible by ethno-linguistic subgroup . A control was considered as any individual who was negative for the CATT and trypanolysis tests and all parasitological tests including CTC , mAECT and lymph node examination [11] . These controls were enrolled during medical surveys . Five millilitres of blood were centrifuged at 3500g for 3 minutes and the buffy coat was collected . Genomic DNA was extracted from the Buffy-coat with the QIAamp DNA Blood Midi/Maxi kit ( Qiagen ) according to the manufacturer's instructions . The DNA was eluted with 200μl of sterile water and stored at -20°C until use . For this study , seven genes containing three SNPs , three VNTRs and one INDEL ( Table 1 ) were identified and selected based on literature searches . The selected genes and loci were associated to HAT and other diseases . The selection of HLA-G , HP and HPR genes as well as two different cytokines genes ( IL6 and IL1A ) was based on their previously reported association with HAT [6 , 7 , 9 , 10] . HPR and haptoglobin ( HP ) are involved in the lysis of trypanosomes and the scavenging of haem during trypanosome infections [8] . The IL1 gene has been shown to enhance immune-modulating and stimulating effects on the TLF components and inflammatory immune response activities during HAT infection [29 , 30 , 31] . Associations between some polymorphic variants within these genes and the outcome of HAT have also been previously outlined [6 , 32 , 33] . Loci on these genes were selected after literature searches as follows: the SNPs rs1800794 of IL1A and rs1554606 of IL6 and the INDEL rs371194629 in the 3’ UTR of HLA-G gene were selected due to their previously reported association with HAT in the DRC although IL1A was not associated with HAT [6 , 7] . The SNP rs1679370 of HPR gene was selected from a study on CNV of associated with HAT [9] . Other genes such as IL1RN , IL4R and HP were also selected not only for their association with other diseases , but especially because HAT seems to trigger inflammatory and immunological responses with biological pathways associating the selected genes [34 , 35 , 36] . The polymorphic locus rs2234663 within IL1RN was selected for its association with H . Pylori gastric infections in Brazil [36] while rs79071878-IL4RN within IL4R gene was due to its association with type II diabetes in India [37] . HP1/2 VNTR allele of the HP gene was selected based on its associations with malaria [36] . In this study , the SNPs in IL6 , IL1A and HPR were investigated by PCR-RFLP where a DNA fragment of each of these genes was amplified and subsequently digested by a specific restriction enzyme . The following primer pairs were used: IL6-PF ( GTCAAATGTTTAAAACTCCCACAGGTT ) and IL6–PR ( GCAGCCAGAGAGGGAAAAGG ) for IL6 [6] , IL1-P-PF ( GGCCACAGGAATTATAAAAGCTGAGA ) and IL1-P-PR ( GGGAGAAAGGAAGGCATGGATTTT ) for IL1A [6] and Hpr-F ( GAGCCACAAATTCTGACGAG ) and Hpr-R ( TTGAGGTTCTTGAGGGCATT ) for HPR . The primers Hpr-F and Hpr-R for HPR were designed with the Primer3 vs 4 . 1 software [39 , 40] . For each of these three genes , the amplification reactions were performed in a final volume of 25 μl containing 1X of PCR buffer , 1 . 5 mM MgCl2 , 20 pmol of each primer , 0 . 5 units of Taq DNA polymerase ( Qiagen ) and 5–10 ng of genomic DNA . The amplification program contained a denaturing step at 95°C for 5 min followed by 35 amplification cycles of 95°C for 45 s , 63°C ( IL6 and IL1A ) or 60°C ( HPR ) for 60 s and 72°C for 60 s . A final extension step was performed at 72°C for 5 min . PCR products were visualised by electrophoresis on 2% agarose gel containing ethidium bromide . Ten micro-litters of IL6 , IL1A and HPR PCR products were digested with Hind III , Nco I and Bci VI respectively ( all enzymes from Thermo Fisher Scientific ) . The digestion was done overnight at 37°C in the buffer 3 . 1 provided by the manufacturer . The digested products of IL6 and IL1A were separated by electrophoresis on a 2% agarose gel at 100 volts for 1 h 30 min . For HPR , the digested products were resolved by electrophoresis on 3 . 5% agarose gel at 100 volts for 2 hours . For rs1554606 of IL6 and rs1800794 of IL1A , three different profiles were expected ( Table 2 ) : the homozygote wild type genotype with two DNA fragments of 236 and 489 bp for IL1A , 315 and 543 bp for IL6 , the heterozygote genotype showing three DNA fragments of 236 , 489 and 725 bp for IL1A , and 315 , 543 and 858 bp for IL6 , and the homozygote genotype with one DNA fragment of 725 bp for IL1A and 858 bp for IL6 . For rs1697370 of HPR , three different profiles were expected ( Table 2 ) : the homozygote wild type genotype with two DNA fragments of 88 and 147 bp , the heterozygote genotype showing three DNA fragments of 88 , 147 and 235 bp , and the homozygote mutant genotype with one DNA fragment of 235 bp . To minimize misinterpretation of heterozygote frequency that could result from partial digestion , the amplified product of each sample ( control and HAT case ) was quantified and the same amount of DNA was subjected to restriction enzyme digestion . Between different amplification and digestion series , an internal control made of sample with known genotype was added . This sample was used to control the reproducibility and digestion efficiency between different amplification and digestion series . The 70 bp tandem repeat ( rs79071878 ) region of IL4RN gene was amplified with IL4-70 bp-F ( AGGCTGAAAGGGGGAAAGC ) and IL4-70 bp-R ( CTGTTCACCTCAACTGCTCC ) primers [37] while the 86bp tandem repeat ( rs2234663 ) of IL1RN gene was amplified with IL1RN-F ( CTCAGCAACACTCCTAT ) and IL1RN-R ( TCCTGGTCTGCAGGTAA ) primers as described by Santos et al . [36] . For these two genes , the PCR reactions were performed in a final volume of 25 μl contained 5–10 ng of DNA , 2 . 5 mM and 2 mM MgCl2 for IL4 and IL1RN respectively , 0 . 2 mM of each dNTP , 20 pmol of each primer and 0 . 5 units of Taq polymerase ( Qiagen ) . The amplification program was 95°C for 5 min followed by 35 cycles of 95°C for 45 s , 61°C for 45 s and 72°C for 60 s . A final extension was performed at 72°C for 5 min . PCR products were separated by electrophoresis on a 2% agarose gel at 100 volts for 1 h 30 min . The size and number of tandem repeats were evaluated for each sample . For IL4RN , the PCR products of 183bp ( two repeats of 70b p ) and 253 bp ( three repeats of 70 bp ) correspond to homozygote wild type ( genotype R1R1 ) and homozygote mutant ( genotype R2R2 ) respectively ( Table 2 ) . Sample with two DNA fragments of 183 bp and 253 bp was considered as a heterozygote with genotype R1R2 . For IL1RN , different alleles with specific sizes could be generated after electrophoresis as described by Santos et al . [36]: alleles 1–4 ( 410 bp ) , 2–2 ( 240 bp ) , 3–5 ( 500 bp ) , 4–3 ( 335 bp ) and 5–6 ( 595 bp ) . Samples showing one DNA fragment or one allele of 410 bp were considered as homozygote wild type and those with one DNA fragment at 240 , 335 , 500 or 595 pb were homozygote mutants . Samples presenting two DNA fragments with 410 bp and another one were considered as heterozygote ( Table 2 ) . Genotyping the HP polymorphism was performed using two approaches: a PCR approach described by Koch et al . [38] and PCR-RFLP using two restriction enzymes to confirm results obtained by PCR [38] . The direct PCR approach consists of two separate PCR reactions with specific DNA fragment characterizing each genotype . Primers A/B ( GAGGGGAGCTTGCCTTTCCATTG and GAGATTTTTGAGCCCTGGCTGGT ) amplified DNA fragments of 1 , 757 bp and 3 , 481 bp for homozygote wild type ( genotype Hp1/1 ) and homozygote mutant ( genotype Hp2/2 ) respectively . Samples showing two DNA fragments at 1 , 757 bp and 3 , 481 bp were considered as heterozygote with genotype Hp1/2 . Since the 3 , 481 bp fragment might not amplify due to lower efficiency of PCR for large fragments or sheared genomic DNA , the results were subsequently validated by a second amplification with primers C ( CCTGCCTCGTATTAACTGCACCAT ) and D ( CCTGCCTCGTATTAACTGCACCAT ) , which amplify a specific DNA fragment of 349 bp for the Hp2 allele [38] . For each of these pairs of primers , the PCR reactions were carried out in a final volume of 25 μl containing 5–10 ng of DNA , 2 . 5 mM MgCl2 , 0 . 2 mM of each dNTP , 20 pmol of each primer and 0 . 5 units of Taq polymerase ( Qiagen ) . The amplification program was 95°C for 5 min followed by 35 cycles of 95°C for 60 s , 69°C for 90 s ( primers A/B ) or 60 s ( primers C/D ) and 72°C for 2 min . A final extension was done at 72° C for 5 min . The amplified products were separated by electrophoresis on a 2% agarose gel at 100 volts for 1 h30 min . To confirm results ( alleles of Hp1 and Hp2 ) obtained by PCR , the DNA fragments of 1757 bp and 3481 bp of primers A/B were digested with MlsI , while the fragment of 349 bp of primers C/D was digested with DraI . Briefly , 10 μl of amplified DNA fragments of each of the primers set was digested with MlsI or DraI as recommended by the supplier ( Thermo Fisher ) . The digestion was done overnight at 37°C in the buffer 3 . 1 provided by the manufacturer . The digested products were separated by electrophoresis on a 2% agarose gel at 100 volts for 2 h 30 min . The polymorphism at 3’UTR ( rs371194629 ) of HLA-G was evaluated by PCR as described by Castelli et al . [41] . PCR reactions were performed in a final volume of 25 μl containing 0 . 2 mM of each dNTP , 1 . 5 mM MgCl2 , 20 pmol of each primer ( HLA-G8F: TGTGAAACAGCTGCCCTGTGT and HLA-G8R: GTCTTCCATTTATTTTGTCTCT ) , 0 . 5 unit of Taq polymerase ( Qiagen ) and 5–10 ng of genomic DNA . The amplification program was 95°C for 5 min followed by 35 cycles . Each of these cycles was made up of 95°C for 45 s , 56°C for 45 s and 72°C for 1 min . A final extension was performed at 72° C for 5 min . The amplified products were resolved by electrophoresis on 4% agarose gel for 4 hours at 100 volts . After this resolution , homozygote mutant and homozygote wild type genotypes were identified through DNA fragments of 345 bp and 359 bp for deletion ( Del ) and insertion ( Ins ) alleles respectively . For heterozygote genotype , two DNA fragments of 345 bp and 359 bp were expected . For this study we assumed an additive genetic model where two risk alleles of a SNP ( homozygous ) have twice the effect of one risk allele ( heterozygous ) [42] . Power calculation was undertaken using the PGA modeller package in MATLAB software [42] . For this package , the power was calculated by considering an odd ratio ( OR ) or relative risk ( RR ) >2 for loci with disease allele frequencies of 0 . 052–0 . 500 with 7 loci genotyped . Other factors taken into consideration include the disease prevalence estimated at <0 . 01 [43] , the standard linkage parameter ( r2 ) for Linkage disequilibrium ( LD ) of 0 . 7 [42] , a type 1 error of 5% risk and sampling size . This later was estimated as described by Kasiulevicius et al . [44] using the independent case-control sampling size formula [44] . For this estimation , we assumed an expected exposure proportions in control of 0 . 20 , a disease prevalence of < 0 . 01 [43] and a case-control ratio of 1:3 . With the independent case-control sampling size formula , the sampling size to detect a real odds ratio or case exposure rate with power and two-sided type I error of 5% risk was 480 including 120 HAT cases and 360 controls . Due to the heterogeneity of the study population formed by 19 ethno-linguistic subgroups ( S1 Table ) and its effect on the Hardy-Weinberg equilibrium and the risk that associations results might be bias by the stratified population rather than infections due to T . b . gambiense , the data were firstly stratified and analysed by three major ethno-linguistic groups ( Bantu , Semi-Bantu and Baka ) . A second analysis was performed when 10 ethno-linguistic subgroups were pooled into two groups on the basis of similarities in language spoken and their geographical proximity [45 , 46] . These two groups include the Beti-Fang ( Bulu , Eton , Fan , Iyassa , Kwasse , Maabi , Mvae and Ngoumba ethno-linguistic subgroups ) and Wovea ( Douala and Bassa ethno-linguistic subgroups ) ( S2 Table ) . To confirm results generated on the population that was stratified into major ethno-linguistic groups and two pooled ethno-linguistic subgroups , 11 ethno-linguistic subgroups derived from this stratified population including the Bamilike , Bassa , Douala , Eton , Fan , Iyassa , Kwasse , Maabi , Mvae , Mundani and Baka ( S2 Table ) were further separately analysed with the fisher exact test at midpoint . Hardy-Weinberg analysis was run not only on the entire population , but also on each individual ethno-linguistic group or subgroup in order to observe the effect the population heterogeneity on HWE , the power of our study and association results . Ethno-linguistic groups or subgroups with HWE p-value deviation and less than 10 individuals or no informative data at a locus were removed for subsequent analyses . The Cochran-Mantel-Haenszel ( CMH ) test implemented in PLINKv1 . 9 package [47] was performed with the allelic frequencies because this test can only be done with binary vars . Used as an extension of the chi-square test , the CMH test enabled to estimate the odds ratio and 95% confidence interval across the stratified populations represented here by ethno-linguistic subgroups . Using these later as covariates , it enabled to test for associations between alleles and the probability to be infected by T . b . gambiense and develop HAT within each ethno-linguistic subgroup . However , the CMH2 test , also implemented in PLINKv1 . 9 package , was used to determine if there were significant differences in the allele frequencies between different ethno-linguistic groups or subgroups . Data were visualised with R/Rstudio version 3 . 3 . 2 ( 2016-10-31 ) . Results of multiple tests were adjusted by the Bonferroni correction which assumes that each of the statistical tests is independent . The significance of genotype and allele frequency differences between cases and controls within each ethno-linguistic group or subgroup were obtained and confirmed with the Fisher exact test for 2x2 contingency table . A meta-analysis was performed on samples from ethno-linguistic subgroups that were in HWE and that showed significant association with the Fisher exact test . This was done not only on each major ethno-linguistic group , but also on the Beti-Fang and Wovea ethno-linguistic groups and the 10 ethno-linguistics subgroups mentioned above .
For this study , a total of 323 individuals including 73 ( 22 . 60% ) HAT cases and 250 ( 77 . 40% ) controls were analysed . The 323 individuals belonged to 19 different ethno-linguistic subgroups ( S1 Table ) . Of these 323 individuals , 211 ( 65 . 33% ) were Bantu , 84 ( 26 . 01% ) semi-Bantu , 21 ( 6 . 50 ) Baka and 7 ( 2 . 17% ) Sudano-Sao ( S1 Table ) . The mean age ( range ) was 45 . 75±5 ( 14–91 ) for HAT cases and 37 . 58±5 ( 9–88 ) for controls . No significant difference ( t = -0 . 206 , P = 0 . 837 ) was observed between the age of controls and HAT cases . The overall sex ratio ( male/female ) was 1 . 006 with 49 . 85% ( 161/323 ) of female and 50 . 15% ( 162/323 ) of male . For this study , we genotyped one polymorphism in each of the seven genes ( IL1A , IL1RN , IL4RN , IL6 , HP , HPR , and HLA-G ) in 73 cases and 250 controls collected from 19 ethno-linguistic subgroups from three Cameroonian HAT foci . With LD r2 of 0 . 7 , a disease prevalence of <0 . 01 , the disease allele frequencies of 0 . 052–0 . 500 for 7 loci genotyped , and a sampling size of 323 individuals including 73 HAT cases and 250 controls , the power of this study was estimated at 82% . Seven loci containing 3 SNPs , 3 VNTRs and one indel were tested from 7 candidate genes . The polymorphism at each of these loci was investigated on 323 samples containing 73 HAT cases and 250 controls from three HAT foci of southern Cameroon . From 323 samples that were analyses at different loci , more than 94% were successfully genotyped at each of the 7 loci . At all loci except HLA-G , the reference allele was at higher frequency than the alternate allele . The genotypes 1A1A ( allele 1–4: 410 bp ) , 1A4A ( allele 4–3: 335 bp ) and 1A3A ( allele 3–5: 500 bp ) were identified for IL1RN gene while the genotypes 2A2A ( allele 2–2: 240 bp ) and 5A5A ( allele 5–6: 595 bp ) or their heterozygote genotypes combinations were absent in our studied population . For the 318 samples that were successfully genotyped at the SNPs rs1800794 of IL1A , 97 ( 30 . 5% ) , 179 ( 56 . 3% ) and 42 ( 13 . 2% ) were respectively heterozygote , homozygote wild-type and homozygote mutant . At SNP rs1554606 of IL6 , 98 . 8% ( 319/323 ) of samples were successfully genotyped: 41 . 4% ( 132/319 ) were heterozygote while 49 . 2% ( 157/319 ) and 9 . 4% ( 30/319 ) were homozygote wild-type and mutant respectively . At SNP rs1697370 of HPR , 99 . 4% ( 321/323 ) of samples were genotyped: 33 . 3% ( 107/321 ) were heterozygote whereas 57 . 0% ( 183/321 ) and 9 . 7% ( 31/321 ) were homozygote wild-type and mutant respectively . Regarding the VNTR , 322 ( 99 . 7%: 322 /323 ) samples were successfully genotyped for the genes HP and IL4RN . For HP , 180 ( 55 . 9%: 180/322 ) samples were heterozygote while 82 ( 25 . 5%: 82/322 ) and 60 ( 18 . 6%: 60/322 ) were homozygote wild-type and mutant respectively . For IL4RN at locus rs79071878 , 176 ( 54 . 7%: 176/322 ) , 77 ( 23 . 9%: 77/322 ) and 69 ( 21 . 4%: 69/322 ) were heterozygote , homozygote wild-type and homozygote mutant respectively . At locus rs2234663 of IL1RN , 99 . 1% ( 320/323 ) of samples were genotyped: 89 . 1% ( 285/320 ) were homozygote wild-type and the remaining was heterozygote . For the indel HLA-G at locus rs371194629 , 99 . 1% ( 320/323 ) of samples were genotyped and 55 . 9% ( 179/323 ) , 18 . 1% ( 58/320 ) and 25 . 9% ( 83/320 ) were heterozygote , homozygote wild-type and homozygote mutant respectively . Allele and genotype frequencies of all cases were compared with those of all controls at all loci using chi-squared tests . No significant difference was observed for the 14 bp indel located at rs371194629 of HLAG , the SNPs rs1554606 and rs1697370 of IL6 and HPR respectively and the VNTRs of IL4RN and HP ( Table 3 ) . However , a significant increased risk to be infected by T . b . gambiense and develop HAT was observed with the TT genotype in IL1A gene with an OR of 2 . 938 ( CI95 [1 . 56–3 . 89] ) and a P value of 0 . 0010 . In addition , the genotype 1A/3A located at locus rs2234663 of IL1RN VNTR with an OR of 2 . 71 ( CI95 [0 . 97–7 . 58] ) and a P value of 0 . 0012 was also associated with an increased risk of getting T . b . gambiense infections and develop HAT . However , the frequencies of this genotype were low in both cases ( 8 . 3% ) and controls ( 3 . 6% ) ( Table 3 ) and this observation should be considered provisional until replicated in larger studies because only 7 cases and 9 controls were enrolled in the analyses . The observed differences in the allelic frequencies distribution ( S3 Table ) and their corresponding p values for the 7 loci within IL1A , IL6 , HP , HPR , IL1RN , IL4RN and HLA-G were deduced from genotypes data contained in Table 3 . Although IL1A seems to be associated with an increased risk of getting T . b . gambiense infections and develop HAT , the allele frequencies were not in Hardy-Weinberg equilibrium ( HWE ) ( 0 . 007 ) . However , when the population was stratified into ethno-linguistic subgroups or major ethno-linguistic groups , the allele frequencies were in HWE for most loci genotyped as shown in S4 Table . These results indicate that the heterogeneous nature of the studied population , formed by several ethno-linguistic subgroups , has an impact on the HWE . Due to these variations and the deviation of HWE in the entire population , additional analyses were performed with the Cochran-Mantel-Haentszel test ( CMH ) that takes into account the population stratification . For these analyses , the population was stratified on the basis of ethno-linguistic groups and subgroups . After stratification of our study population into three major ethno-linguistic groups ( Bantu , Semi-Bantu and Baka ) , the observed allelic frequencies were all in Hardy–Weinberg equilibrium within each ethno-linguistic group; suggesting random genetic exchange within each of the major ethno-linguistic groups . Data of S4 Table shows detailed results of HWE values when the population was structured into ethno-linguistic groups and in pooled ethno-linguistic subgroups . The Cochran-Mantel-Haentszel test ( CMH ) was used to test the associations between the allele frequencies and the probability to be infected by T . b . gambiense and develop HAT . This test estimates an odds ratio and 95% confidence interval across the population using ethno-linguistic subgroups as covariant . Data of CMH test reported in Table 4 considered only 305 individuals ( 69 HAT cases and 236 controls ) of three major ethno-linguistic groups . The null hypothesis of the Cochran-Mantel-Haenszel ( CMH ) test is that allele frequencies are the same in cases and controls and do not differ between populations . With the CMH test , the minor allele T of rs1800794 in IL1A which is located in the promoter region was significantly associated ( unadjusted P = 0 . 0012 , X2 = 30 . 01 , adjusted P = 0 . 009 ) with an increased risk to be infected by T . b . gambiense and develop this infection ( Table 4 ) . Its OR of 2 . 066 ( CI95 [1 . 33–3 . 20] ) and P value of 0 . 009 indicate higher frequencies in cases compared to controls . The null hypothesis of the CMH2 test is that allele frequencies are the same in each population . The CMH2 test indicated that there was no significant difference in allele frequencies between populations ( P = 0 . 368 ) . The Bantu major ethno-linguistic subgroups were pooled ( Beti-Fang: Bulu , Eton , Fan , Iyassa , Kwasse , Maabi , Mvae , and Ngoumba; and Wovea: Bassa and Douala ethno-linguistic subgroups ) into two groups ( S4 Table ) in order to trace and spot which of these subgroups was at the centre of this effect . With CMH test , the minor allele T of rs1800794 in IL1A remains significantly ( unadjusted P = 0 . 0005 , X2 = 11 . 99 , adjusted P = 0 . 004 ) associated with an increased risk of getting T . b . gambiense and develop this infection in the Bantu major ethno-linguistic group . Its OR of 2 . 32 ( CI95 [1 . 44–3 . 37] ) and a P value of 0 . 0005 ( S2 Table ) indicates higher frequencies of the allele T in cases compared to controls . After pooling some ethno-linguistic subgroups ( S2 Table ) , the minor allele T of rs1800794 in IL1A with an OR of 2 . 40 ( CI95 [1 . 41–4 . 10] ) and an adjusted P value of 0 . 009 remains significantly associated with an increased risk of getting T . b . gambiense infections and develop HAT within the Beti-Fang ethno-linguistic groups . The HP2 minor allele of HP seems to be also significantly ( unadjusted P = 0 . 0015 , X2 = 5 . 90 , adjusted P = 0 . 011; OR: 3 . 68 ( CI95 [1 . 23–8 . 33] ) ) associated with an increasing risk of getting T . b . gambiense infections and develop HAT within the Bassa and Douala ethno-linguistic subgroups ( S2 Table ) . For the other genes , no significant difference was observed in the association studies as reported on whole population ( Table 4 ) . To confirm results obtained on the stratified populations and see the impact of heterogeneous population or different ethno-linguistic groups and subgroups on the association between gene polymorphism and the risk to be infected by T . b . gambiense and develop HAT , meta analyses were performed on the basis of the three major ethno-linguistic groups and 11 ethno-linguistic subgroups . Of the 323 individuals belonging to the 19 different ethno-linguistic subgroups used in this study ( S1 Table ) , 75 of them were excluded due to small population sample size ( i . e less than 10 individuals ) , small HWE P values ( S5 Table ) and or loci that were not informative ( low genotypes and allelic frequencies ) . For subsequent analyses , 249 individuals belonging to the three major ethno-linguistic groups and 11 ethno-linguistic subgroups ( Bamilike , Bassa , Douala , Eton , Fan , Iyassa , Kwasse , Maabi , Mvae , Mundani and Baka ) were considered for association analysis ( S5 Table ) . The observed allelic frequencies were all in Hardy–Weinberg equilibrium within the ethno-linguistic subgroups; suggesting random genetic exchange within these ethno-linguistic groups and subgroups . Results of meta-analysis confirmed the significant ( P = 0 . 0017 , OR = 2 . 305 ) association previously reported for SNP rs1800794 of IL1A ( Table 5 ) . Its OR of 2 . 305 ( CI95 [1 . 29–3 . 25] ) and a P value of 0 . 0017 confirms the higher frequencies of allele T in cases compared to controls . The absence of significant association at different loci of other genes was also confirmed by the meta-analysis . Results generated by meta analyses on the 11 ethno-linguistic subgroups were consistent with those of the CMH test on the populations that were stratified into three major ethno-linguistic groups and pooled ethno-linguistic subgroups .
This study revealed that one SNP ( rs1800794 ) of IL1A and one VNTR ( rs2234663 ) of IL1RN were associated with an increased risk to be infected by T . b . gambiense and develop HAT in inhabitants of sleeping sickness foci of southern Cameroon . The minor allele ( T ) of SNP rs1800794 of IL1A gene and the genotype 1A3A of IL1RN rs2234663 VNTR seem to increase the risk of getting T . b . gambiense infections and develop HAT in southern Cameroon . Results of this study show that the association between host genetic determinants or gene polymorphisms and the risk to be infected by T . b . gambiense and develop HAT may vary with the heterogeneity of the studied populations .
|
Human African Trypanosomiasis ( HAT ) , or sleeping sickness , is a parasitic disease caused by flagellated parasites of the genus Trypanosoma . This disease has been included into the WHO roadmap for neglected tropical diseases with elimination as a public health problem targeted for 2020 and the interruption of transmission to humans for 2030 . To achieve these elimination and interruption goals , it is important to identify and understand the factors that may hamper these goals . Understanding the contribution of human genetics to the response of trypanosome infections is important for the development of new control strategies . In this study , polymorphism in seven genes was investigated between controls and sleeping sickness patients of three sleeping sickness foci of Southern Cameroon in order to see if there is any association with the development of disease . Results of this study have shown that the genotype ( TT ) and minor allele ( T ) of IL1A gene and the genotype 1A3A VNTR of IL1RN are associated with an increased risk of getting T . b . gambiense infections and develop sleeping sickness in major ethno-linguistic groups of the Cameroonian population . They suggest that the association between host genetic determinants and the susceptibility to T . b . gambiense infections could vary according to the population studied . These results will improve our knowledge on the role of human genetics determinants and the risk to be infected by T . b . gambiense and develop sleeping sickness . They could thus lead to the identification of novel biomarkers which could open a frame work for the development of new diagnostics , treatments and intervention strategies .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"medicine",
"and",
"health",
"sciences",
"african",
"trypanosomiasis",
"variant",
"genotypes",
"tropical",
"diseases",
"geographical",
"locations",
"parasitic",
"diseases",
"parasitic",
"protozoans",
"alleles",
"genetic",
"mapping",
"protozoans",
"neglected",
"tropical",
"diseases",
"molecular",
"genetics",
"molecular",
"biology",
"techniques",
"africa",
"research",
"and",
"analysis",
"methods",
"infectious",
"diseases",
"cameroon",
"zoonoses",
"artificial",
"gene",
"amplification",
"and",
"extension",
"protozoan",
"infections",
"trypanosomiasis",
"molecular",
"biology",
"genetic",
"loci",
"people",
"and",
"places",
"trypanosoma",
"eukaryota",
"polymerase",
"chain",
"reaction",
"heredity",
"genetics",
"biology",
"and",
"life",
"sciences",
"organisms"
] |
2019
|
Association between IL1 gene polymorphism and human African trypanosomiasis in populations of sleeping sickness foci of southern Cameroon
|
The ability to respond to stress is at the core of an organism's survival . The hormones epinephrine and norepinephrine play a central role in stress responses in mammals , which require the synchronized interaction of the whole neuroendocrine system . Mammalian adrenergic receptors are G-coupled protein receptors ( GPCRs ) ; bacteria , however , sense these hormones through histidine sensor kinases ( HKs ) . HKs autophosphorylate in response to signals and transfer this phosphate to response regulators ( RRs ) . Two bacterial adrenergic receptors have been identified in EHEC , QseC and QseE , with QseE being downstream of QseC in this signaling cascade . Here we mapped the QseC signaling cascade in the deadly pathogen enterohemorrhagic E . coli ( EHEC ) , which exploits this signaling system to promote disease . Through QseC , EHEC activates expression of metabolic , virulence and stress response genes , synchronizing the cell response to these stress hormones . Coordination of these responses is achieved by QseC phosphorylating three of the thirty-two EHEC RRs . The QseB RR , which is QseC's cognate RR , activates the flagella regulon which controls bacteria motility and chemotaxis . The QseF RR , which is also phosphorylated by the QseE adrenergic sensor , coordinates expression of virulence genes involved in formation of lesions in the intestinal epithelia by EHEC , and the bacterial SOS stress response . The third RR , KdpE , controls potassium uptake , osmolarity , and also the formation of lesions in the intestine . Adrenergic regulation of bacterial gene expression shares several parallels with mammalian adrenergic signaling having profound effects in the whole organism . Understanding adrenergic regulation of a bacterial cell is a powerful approach for studying the underlying mechanisms of stress and cellular survival .
The survival of an organism lies within its intrinsic ability to detect and efficiently respond to stress cues . Stress responses play a key role in adaptation to environmental , psychosocial , and physical insults . Hence it comes as no surprise that stress responses require synchronization and coordination of an organism's resources to ensure that metabolic substrates are available to meet the increasing energy demands of an effective stress response . Stress responses are generally termed “fight or flight” responses in higher animals , because they rely in the ability of an organism's to assess whether its better chance of survival relies on facing or avoiding an environmental insult . The hormones epinephrine and norepinephrine are at the core of stress responses [1] . In mammalian cells epinephrine and norepinephrine are recognized by GPCRs , which are membrane receptors coupled to heterotrimeric guanine-binding proteins ( G-proteins ) . These proteins consist of three subunits α , β and γ . The binding of these signals to GPCRs result in a conformational change that activates the G-protein through the exchange of GDP for GTP . The activated G-protein dissociates from the receptor , the α , β , and γ subunits then dissociate and activate their intracellular targets . The GPCR specificity is controlled by the type of G-protein associated with the receptor . G-proteins are divided in four families according to their association with effector proteins . Three of these signaling pathways , Gαs , Gαi and Gαq , have been extensively studied , with Gαs activating adenylate cyclase , Gαi inhibiting adenylate cyclase , and Gαq activating phospholipoase C [1] . Most of the knowledge of epinephrine/norepinephrine-mediated signaling has been derived from studies in mammalian systems . However , although bacterial cells sense and respond to epinephrine and norepinephrine , the signaling pathways regulated by these mammalian hormones in bacteria have not been mapped [2] , [3] . Bacteria do not express homologues of mammalian adrenergic receptors . These signals are sensed through histidine sensor kinases ( HKs ) [4] , [5] . HKs constitute the predominant family of signaling proteins in bacteria . HKs usually act in concert with a response regulator ( RR ) protein constituting a two-component system . Upon sensing a defined environmental cue the HK autophosphorylates a conserved histidine residue , and then transfers this phosphate to an aspartate residue in the receiver domain of a cognate RR . The majority of the RRs are transcription factors , which are activated upon phosphorylation [6] . Two HKs , QseC and QseE , characterized in E . coli have been reported to sense epinephrine and norepinephrine [4] , [5] . QseC binds to and increases its autophosphorylation in response to epinephrine , norepinephrine , and a bacterial signaling molecule termed autoinducer-3 ( AI-3 ) [4] . QseE increases its autophosphorylation in response to epinephrine , phosphate and sulfate [5] . QseC acts upstream of QseE , given that transcription of qseE is activated by QseC [7] . The cognate RR for QseC is QseB [4] , and the genes encoding this two-component system are co-transcribed constituting an operon [8] . The cognate RR for QseE is QseF , with the qseF gene also being co-transcribed with qseE within the same operon [8] . QseF , however , is also phosphorylated by four other non-cognate HKs: UhpB , BaeS , EnvZ and RstB [9] . QseC homologues exist in at least 25 bacterial species [10] , while QseE homologues can only be found in enterics . This distribution of receptors may play a role in colonization or virulence with increased levels of epinephrine/norepinephrine . The majority of the studies assessing adrenergic regulation of bacterial gene expression , have been conducted in bacteria that inhabit the human gastrointestinal ( GI ) tract [2] , [4] , [11] , [12] , [13] , [14] , [15] . Norepinephrine is present in the GI tract , being synthesized by adrenergic neurons of the enteric nervous system ( ENS ) [16] . Epinephrine is synthesized in the central nervous system and the adrenal medulla , and reaches the intestine in a systemic manner after being released into the bloodstream [17] . Norepinephrine is found at a nanomolar range in sera , while it is at a micromolar range in the intestine [18] . Both hormones have important roles in intestinal homeostasis regulating peristalsis , blood flow , chloride and potassium secretion [17] , [19] . Both epinephrine and norepinephrine are recognized by the same adrenergic GPCRs in mammalian cells , and the ligand-binding site for these hormones is largely similar [20] . Enterohemorrhagic Escherichia coli ( EHEC ) O157:H7 is a GI pathogen that exploits adrenergic signaling to regulate virulence gene expression [2] . EHEC colonizes the human intestine and leads to the development of hemorrhagic colitis and hemolytic uremic syndrome ( HUS ) . In the colon , EHEC forms attachment and effacement ( AE ) lesions on the intestinal epithelial cells , which cause extensive rearrangement of the host cell cytoskeleton resulting in the formation of a pedestal-like structure underneath the bacterial cell [21] . The genes required for AE lesion formation are located in the chromosomal pathogenicity island termed the locus of enterocyte effacement ( LEE ) [22] . The first operon in the island ( named LEE1 ) , encodes Ler , the master regulator of the LEE genes [23] . The remaining genes encode the type-three secretion system ( TTSS ) [24] , which forms a syringe-like apparatus that the bacteria use to translocate effector molecules to the host cells . Many of these effectors mimic mammalian signaling proteins having profound effects in the host cell signal transduction culminating in diarrheal disease [25] . Seven of these effectors are encoded within the LEE region [25] , while many others are scattered throughout the genome [26] , [27] . The first secreted effector discovered outside of the LEE was NleA [28] . NleA is known to inhibit cellular protein secretion by disrupting mammalian COPII function and mutation of the nleA gene resulted in attenuation in mouse model of infection [28] , [29] . EHEC also produces a potent Shiga toxin ( Stx ) that is responsible for the major symptoms of hemorrhagic colitis and HUS [30] . Expression of LEE , Shiga toxin and the flagella and motility genes in EHEC are regulated by the signals AI-3 , epinephrine and norepinephrine through QseC [4] , [10] . This regulation is important for EHEC virulence , given that qseC mutants are attenuated for infection in animal models of disease [4] , [10] . QseC activates transcription of the flhDC genes , which encode the master regulators of the flagellar regulon , directly through QseB binding to the flhDC promoter . Importantly , this interaction is dependent on QseB's phosphorylation state [31] , whereas , expression of the LEE and Shiga toxin genes are not regulated by QseB . Here we report a global analysis of EHEC gene expression in response to adrenergic signals , and map the QseC signaling cascade . In this study we unravel the adrenergic response of a bacterial cell at the genetic and biochemical levels , and demonstrate that adrenergic signaling has a profound effect on cell homeostasis , cell-to-cell signaling , and bacterial pathogenesis .
We had previously reported that inactivation of the qseC gene results in reduced flagella expression and motility , and reduced auto-activation [8] , [31] . To further characterize the role of QseC in EHEC , Affymetrix E . coli 2 . 0 microarrays were used to compare expression profiles of the WT and ΔqseC strains in the presence and absence of the signals AI-3 and epinephrine in Dulbecco's modified eagle media ( DMEM ) , which is optimal for expression of the LEE genes , and LB , which is optimal for expression of the flagella regulon . These arrays contain ∼10 , 000 probe sets ( array genes ) , covering all genes in the genomes of the two sequenced EHEC strains ( EDL933 and Sakai ) , K-12 strain MG1655 , uropathogenic E . coli ( UPEC ) strain CFT073 , and 700 probes to intergenic regions ( which can encode non-annotated small ORFs , or small regulatory RNAs ) . Expression data can be accessed using accession number ( GSE15050 ) at the NCBI GEO database . During growth in LB , 126 probe sets were down-regulated ( 28 specific to EHEC ) , and 708 were up-regulated ( 232 EHEC specific ) in the qseC mutant ( Table 1 ) . The majority of the genes with an altered profile were derived from the E . coli K-12 strain MG1655 ( 68% ) , which represent a common E . coli backbone conserved among all E . coli pathovars [32] . Many of these genes are associated with metabolism , and they also include the flagella regulon ( Figure 1B and Figure 2D and 2E ) . The EHEC specific genes ( 32% ) include several prophage-encoded genes and stxAB encoding Shiga toxin . These studies revealed that QseC not only activates transcription of the flagella regulon , but also of the genes encoding Shiga toxin . Transcriptome comparisons between WT and the qseC mutant grown in DMEM , a condition conducive to LEE and virulence gene expression , in the presence of AI-3 alone ( both WT and the qseC mutant produce AI-3 when grown to late exponential phase in DMEM ) or AI-3 plus epinephrine also revealed a global role for QseC regulation of virulence genes ( Table 2 ) . In the presence of AI-3 alone , expression of 106 genes was increased and 273 decreased in the qseC mutant compared to WT . In the presence of AI-3 plus epinephrine expression of 70 genes was increased and 311 decreased in the qseC mutant compared to WT . AI-3 and epinephrine have been reported to act as agonistic signals [33] . This agonistic relationship in signaling can be further illustrated by the observation that while AI-3 is only sensed through QseC , epinephrine is sensed by both QseC and QseE [4] , [5] . However , it is worth mentioning that QseC acts upstream of QseE , given that transcription of qseE is activated by QseC [7] . These data suggest that both signals tend to activate global gene expression in a qseC-dependent fashion more frequently than repress expression . Among the genes activated in a qseC-dependent manner are the LEE ( through activation of ler transcription , within the LEE1 operon , encoding the Ler activator of all other LEE genes ) and stxAB ( Shiga toxin ) genes ( Figure 1B , 1C and 1D ) . The genes encoding Stx are located within the late genes of a λ- bacteriophage and are transcribed when the phage enters its lytic cycle upon induction of an SOS response in the bacterial cell [34] . Upon the induction of an SOS response , recA is upregulated and cleaves the λ cI repressor allowing transcription of the middle and late genes to proceed , and together with them the stxAB genes . QseC-induction of stxAB transcription occurs through induction of recA expression ( Figure 1D ) , suggesting that QseC mediates SOS induction in bacterial cells . In addition to activating expression of the LEE-encoded TTSS , the majority of the genes encoding effectors translocated through this TTSS are also regulated by QseC ( Figure 1B ) . Of note , transcription of the gene encoding the NleA effector is strongly repressed by QseC in LB , while its expression is slightly ( non-statistically significant ) decreased in the qseC mutant in DMEM ( Figure 1E and 1F ) . These analyses confirmed QseC's activation of the flagellar genes and revealed several new regulatory targets , including: LEE ( through ler ) , nleA , genes of the SOS response and Shiga toxin . Altogether , these data suggest that QseC is at the top of the signaling cascade activated by AI-3 , epinephrine and norepinephrine , initiating regulation of all EHEC virulence genes . Through QseC , EHEC senses AI-3 , epinephrine and norepinephrine to activate flagella and motility , AE lesion formation and Shiga toxin expression . Given that these are expensive biological processes that have to occur in concert , the kinetics of expression of these genes has to be exquisitely fine-tuned . We have previously reported that a ΔqseC EHEC had reduced motility , expressed less flagella , and presented reduced transcription of the flagella regulon [35] . The cognate RR of the QseC HK is QseB , which is phosphorylated at a conserved aspartate residue by QseC [4] ( Figure 2A ) . In this study we deleted the cognate response regulator qseB . Since we had previously shown that QseC regulated the flagellar genes through a direct interaction of QseB and the flhDC promoter ( FlhDC are the master activators of the flagella regulon ) [31] , we hypothesized that mutation of qseB would result in decreased motility . However , a ΔqseB mutant has no motility defect ( Figure 2B ) , and expresses flagella at the same levels as the WT strain ( Figure 2C ) . To confirm these results , we assessed transcription of flhD by real-time RT-PCR in WT , ΔqseC , and ΔqseB mutants . Relative expression levels of flhD in these three strains indicated that transcription of flhD is decreased in ΔqseC but is unaltered in ΔqseB ( Figure 2D ) . We then performed β-galactosidase assays with the −900 to +50 bp region of the flhDC promoter fused to a promoterless lacZ gene as a reporter . We found that in ΔqseC there was five-fold less β-galactosidase activity as compared to WT ( Figure 2E ) , but there was no difference in β-galactosidase activity between the WT and ΔqseB . Because QseB and QseC constitute a cognate two-component system , we expected that the qseC and qseB mutants would have similar phenotypes . However , while the qseC mutant has decreased motility and expression of the flagellar regulon , the qseB mutant shows similar levels of flhDC expression and motility as the WT strain . These results led us to develop two potential hypotheses for the differential effects of knocking an HK ( QseC ) and its cognate RR ( QseB ) on flhDC transcription . First , QseB can bind to different DNA sequences according to its phosphorylation state , acting as a repressor or activator depending on which site it is bound to . Second , QseC could be a promiscuous HK and can phosphorylate non-cognate RRs that acts on the flhDC promoter . To test the first hypothesis we overexpressed QseB in a ΔqseC background . We assumed that this strain would have an overabundance of unphosphorylated QseB . We found that this strain was less motile than ΔqseC , indicating that unphosphorylated QseB can act as a repressor of the flagellar gene expression ( Figure 3A ) . We also complemented the ΔqseB strain with a plasmid expressing QseB , and observed that the complemented strain had decreased motility; again suggesting that overabundance of unphosphorylated QseB has a repressive role in motility ( Figure 3B ) . However , when we complemented the ΔqseB strain with a plasmid expressing qseBC ( Figure 2 ) , we did not observe any differences in motility , probably because the levels of QseB and QseC were balanced in this strain . Next , we overexpressed qseB , in a strain containing the −900 to +50 bp region of the flhDC promoter upstream of a promoterless lacZ . We found that in the strain overexpressing qseB there was a five-fold decrease in β-galactosidase activity ( Figure 3C ) . We also observed decreased flhDC transcription in a strain overexpressing a QseB site-directed mutant ( QseB D51A ) that cannot be phosphorylated ( the conserved aspartate phosphorylated residue has been changed to an alanine ) ( Figure 3C ) , further indicating that an abundance of unphosphorylated QseB represses expression of flhDC . We had previously shown that QseB can bind to two regions of the flhDC promoter , −300 to +50 bp and −900 to −650 bp [31] . We demonstrated that this binding required QseB to be phosphorylated [31] ( Figure 3C ) , which can be achieved by providing a small phosphate donor , acetyl phosphate , to QseB in vitro . QseB will only bind to the −300 to +50 bp flhDC region in the presence of acetyl phosphate ( Figure 3D ) , and the QseB D51A mutant is also unable to bind to this region of flhDC ( Figure 3D ) . We have discovered a new QseB binding site in the flhDC promoter from −650 to −300 bp to which QseB can bind in the absence of phosphorylation . QseB binds to this −650 to −300 bp site in the absence of acetyl phosphate , and QseB D51A can also bind to this site ( Figure 3E and 3F ) . The presence of this new binding site provides further evidence for a dual role of QseB in the regulation of the flhDC promoter . At low signal concentration there is low QseC activation and thus low QseB phosphorylation . In this case only the −650 to −300 bp site of the flhDC promoter will be occupied by non-phosphorylated-QseB and this binding may lead to repression . When the signal is high the opposite is true . The −300 to +50 bp and −900 to −650 bp sites will be occupied by phosphorylated QseB and flhDC will be activated ( Figure 3H ) . In further support of this model , a nested deletion analyses of the flhDC promoter fused to lacZ shows that the full length fusion ( −900 to +50 bp ) is activated by QseC ( Figure 3G ) . This fusion contains all three QseB binding sites , and in the presence of QseC , phosphorylated QseB will occupy the activating sites from −950 to −650 bp and −300 to +50 bp , increasing transcription . In the −650 to +50 bp fusion , transcription of flhDC is repressed in the absence or presence of QseC , probably because of non-phosphorylated QseB binding to the −650 to −300 bp site , which represses flhDC transcription . Non-phospho-QseB binding to the −650 to −300 bp region is probably “locked” in the absence of the upstream ( −900 to −650 ) site . When both upstream sites are removed ( −300 to +50 bp fusion ) , phospho-QseB bound to this proximal site will activate flhDC transcription ( Figure 3F ) . In the complete absence of QseB , as in a qseB null strain , there will be QseC-independent expression of flhDC transcription , without any repression or activation ( de-repression ) by QseB ( Figure 2 ) . These data indicate that regulation of flhDC transcription by QseC occurs through its cognate RR QseB , and that QseB plays a dual role in this regulation according to its phosphorylated state . QseB , however , does not seem to play a role in QseC-dependent activation of LEE and stxAB transcription ( Figure 4 ) , suggesting that this regulation may occur through phosphorylation of other RRs . In addition to QseB there are at least 31 other RR in E . coli that could be activated via QseC [9] . There is minimal cross-talk ( cross-phosphorylation ) between different two-component systems ensuring faithful transmission of information through distinct signaling pathways [36] , [37] . Indeed , the incidence of cross-phosphorylation between non-cognate HKs and RRs is low in E . coli , Yamamoto et al . showed that phosphorylation of non-cognate response regulators by HKs is rare and occurs in only 22 of 692 possible combinations [9] . However , in this same study , Yamamoto noticed that a distinct few HKs are more prone to also signal through non-congate RRs . We have previously reported that QseC autophosphorylates in response to AI-3 , epinephrine and norepinephrine in an in vitro liposome assay and can phosphotransfer onto its cognate RR , QseB [4] . In order to test QseC's ability to phosphotransfer onto non-cognate RRs , we purified 31 E . coli RRs and performed phosphotransfer assays with QseC in liposomes . Of note all of these RRs were soluble and correctly folded upon purification , and have been previously shown by Yamamoto et al . to be active in phosphotransfer reactions with their cognate HKs [9] . Through this assay , we found only two additional QseC phosphorylation targets: KdpE and QseF ( Table 3 , Figure 5A and 5B ) . KdpE has been shown to regulate potassium uptake and medium osmolarity [38] . We found that kdpA , one of the genes regulated by KdpE , is also down-regulated in the ΔqseC ( Figure 6A ) , indicating that cross-phosphorylation between QseC and KdpE results in QseC regulation of KdpE-dependent targets . To assess the contribution of KdpE to QseC's signaling transduction pathway , we deleted kdpE but found no motility defect ( Figure 6C ) or decreased flhDC expression ( Figure 6B ) in the kdpE mutant , indicating that KdpE is not regulating flhDC . When we assessed transcription of ler ( LEE ) and stx , we observed that KdpE activates transcription of the LEE genes , but not stx , suggesting that through the KdpE RR , QseC activates expression of the LEE genes ( Figure 6D ) . The second non-cognate RR phosphorylated by QseC , QseF , is responsible for aiding in AE lesion formation by activating expression of the phage-encoded gene espFu [7] . EspFu is a secreted effector , translocated to epithelial cells by the LEE-encoded TTSS , and it is involved in host actin nucleation and polymerization for AE lesion formation [39] , [40] . QseF , however is not involved in regulation of LEE gene expression ( Figure 6E ) [7] , nor in flagella and motility regulation [7] . However , a qseF knockout presented diminished expression of the stx gene ( Figure 6E ) , suggesting that QseC activation of Shiga toxin expression occurs through the QseF RR . The QseF cognate HK is QseE [9] , which is a second bacterial adrenergic receptor that senses epinephrine , phosphate and sulfate [11] . The addition of epinephrine to EHEC activates expression of qseEF , and this regulation is eliminated in the ΔqseC mutant , indicating that QseC activates transcription of qseEF [7] . Transcriptional regulation of qseEF by QseC , in addition to cross-phosphorylation of QseF by QseC and QseE may fine tune the timing for switching from motility , to AE lesion formation to Shiga toxin production during infection . QseC phosphorylates three RRs: QseB , KdpE and QseF ( Figure 7A ) . Through QseB the flagella regulon is regulated . KdpE activates expression of ler , and consequently of all LEE genes . QseF plays a role in inducing an SOS response and Shiga toxin production , as well as activating expression of espFu [7] , which encodes an effector essential for AE lesion formation . To search globally which sets of QseC-dependent genes are regulated through each RR we performed transcriptome assays ( GEO series GSE15050 ) . These comparisons were performed with gene arrays hybridized with cDNA from RNA extracted from WT , ΔqseC , ΔqseB , ΔkdpE and ΔqseF strains grown in DMEM to an OD600 of 1 . 0 , conditions known to yield maximal endogenous AI-3 production in these strains [41] . Given that AI-3 is only sensed through QseC , and QseC will phosphorylate in the presence of either AI-3 or epinephrine [4] , [11] , by working under these conditions we would detect only QseC-dependent genes . We avoided using epinephrine in these comparisons , because epinephrine is also sensed by the QseE HK [4] , [11] . Transcription of 324 genes was increased , and 344 decreased in the ΔqseC mutant compared to WT ( Figure 7B ) . Of the 324 genes increased in the ΔqseC , 15 were also increased in ΔqseB , 13 in ΔqseF , and 63 in ΔkdpE ( Figure 7B ) . These data suggest that 91 of these 324 genes repressed by QseC are under the control of the QseB , KdpE and QseF RRs . These leaves 233 genes repressed through QseC unaccounted for . A possible explanation could be that these genes may be activated and repressed by QseB in a similar fashion to flhDC ( Figure 3 ) , and these genes would not appear as transcriptionally regulated through QseB using gene arrays . QseC activates transcription of 344 genes , with 205 being activated through QseB , 44 through QseF and 87 through KdpE ( Figure 7B ) . These three RRs activate transcription of 336 of the 344 QseC-dependent genes , giving almost 100% coverage of QseC-activated genes .
Chemical signaling between cells underlies the basis of multi-cellularity . Although bacteria are unicellular , bacterial populations also utilize chemical signaling , through hormone-like compounds named autoinducers , to achieve cell-cell communication and coordination of behavior [42] . Chemical signaling is also essential for an organism to survive , successfully adapt to ever changing environments and protect themselves from insults , which can be collectively considered stress . Successful stress responses require energy input , and the coordination of many complex signaling pathways within the cell . Co-evolution of prokaryotic species and their respective eukaryotic host have exposed bacteria to hormones and eukaryotic cells to autoinducers . Therefore , it is not surprising that bacteria can respond to host hormones , and that some pathogenic species have high-jacked these signaling systems to promote disease states [43] . One example of a pathogen that senses host hormones to regulate virulence is EHEC [2] . Upon reaching the human colon , EHEC senses the autoinducer-3 ( AI-3 ) produced by the microbial gastrointestinal flora , and epinephrine and norepinephrine produced by the host through the HK QseC [2] , [4] . This signal transduction activates transcription of virulence genes in a coordinated fashion leading to the formation of AE lesions on intestinal cells by the locus of enterocyte effacement ( LEE ) genes , the flagella regulon for enhanced motility , and Shiga toxin production which is responsible for HUS . EHEC probably first encounters the AI-3 signal produced by the microbial flora that inhabits the intestinal lumen [2] . Because the infectious dose of EHEC is very low ( estimated to be 50 CFUs ) [21] , it is unlikely that it responds to self-produced signal to initiate infection . Upon sensing AI-3 , QseC initiates the signaling cascade that will activate the flagella regulon leading to swimming motility , which may aid EHEC to come closer to the intestinal epithelial layer . As EHEC approaches the epithelium and starts forming AE lesions it is probably then exposed to epinephrine and/or norepinephrine . Norepinephrine is synthesized within the adrenergic neurons of the enteric nervous system ( ENS ) that innervates the basolateral layer of the intestine [16] . Epinephrine is synthesized in the central nervous system ( CNS ) and in the adrenal medulla; it acts systemically after being released into the bloodstream , when it can reach the intestine [17] . AE lesion formation and the commencement of bloody diarrhea may increase EHEC exposure to epinephrine and norepinephrine , further upregulating expression of virulence genes in EHEC . This coordinated regulation involves a number of two-component regulatory systems composed of HKs and RRs that result in cascades of gene expression . Recognition of AI-3/epinephrine/NE by QseC can be specifically blocked by the administration of the α-adrenergic antagonist phentolamine [4] , and a synthetic compound called LED209 [10] . Using two different rabbit infection models it has been demonstrated that QseC plays an important role in pathogenesis in vivo , since qseC mutants were attenuated for virulence in these animals [4] , [10] . Recently , a novel two-component system , the QseEF system [7] , where QseE is the HK and QseF is the RR was shown to also regulate virulence in EHEC . QseE can also respond to the host hormone epinephrine like QseC , but in contrast , does not sense the bacterial signal AI-3 . QseE is downstream from QseC in this signaling cascade , given that qseEF transcription is activated by epinephrine via QseC . The QseEF system is not involved in regulation of flagella and motility , but plays an important role in activating genes necessary for AE lesion formation [7] and also activates expression of Shiga toxin ( Figure 6 ) . The AI-3/epinephrine/NE signaling system is not restricted to EHEC . In silico analysis showed homologues of QseC in other bacterial species such as Salmonella sp , Shigella flexneri , Francisella tularensis , Haemophilus influenzae , Erwinia carotovora , and many others [10] . In vivo studies provided evidence that the QseC HK is important in Salmonella typhimurium [10] , [44] and Francisella tularensis [45] pathogenesis , since qseC mutants of these strains are attenuated in animal models of infection and in vivo inhibition of QseC by LED209 results in attenuation of infection by these organisms [10] . Because QseC is central for sensing adrenergic signals , and the effect these signals have in basic biological processes , a complete understanding of the QseC signaling transduction pathway in bacteria will offer clues on how eukaryotic stress responses affect a prokaryotic cell . We demonstrate that QseC acts promiscuously through three RRs ( Figures 5 and 7 ) to initiate a complex signaling cascade that affects both metabolism and pathogenesis ( Figure 8 ) . QseC controls the expression of all of these features , either directly or indirectly and must be considered to be at or near the top of the signaling cascade . The fact that more that one kinase can activate multiple response regulators suggests that there is a hierarchy of signaling , beginning with QseC . It is currently unclear if the regulation by the associated HK and RR overrides the signal employed by a non-cognate HK or if they work in synergy to amplify the initial signal . This additional level of control may be the fine-tuning that is observed in EHEC where the motility , formation of lesions and secretion of toxin must be exquisitely choreographed to have an effective infection occur . An additional level of complexity included in this signaling cascade is that QseB , binds to different sites in the target promoters according to its phosphorylation state ( Figure 3 ) . This allows further modulation of gene expression by the spatial arrangement of these sites in the regulatory region of genes , allowing the same RR to both repress and activate transcription of the same gene . In the non-activated form ( non-phosphorylated ) QseB forms an additional regulatory barrier to the expression of flhDC . Only under conditions where QseB is both phosphorylated and in sufficient concentration is there full activation of the flagella regulon . Thus this two-step process provides additional levels of control for this energetically expensive appendage . These types of mechanisms ensure that only under conditions which are favorable the resources are devoted to this response . The DNA binding domain of QseB shares similarities with the DNA binding domain of the OmpR RR , which also recognizes different sites on DNA according to its phosphorylation state [46] , [47] . Because epinephrine and norepinephrine exert a profound effect in the host physiology and immune system , the ability to sense these hormones by bacteria may facilitate gauging the fitness of the host . Inter-kingdom chemical signaling plays an important role in the relationships forged between bacteria and animals . Chemical communication within kingdoms has been studied for many decades , however , the interception of these languages between different kingdoms has been appreciated only more recently . As this field expands , more and more examples will be described , and many questions answered .
All bacterial strains and plasmids utilized in this study are listed in Table S1 . E . coli strains were grown aerobically in LB or DMEM ( Invitrogen ) medium at 37°C unless otherwise stated . Antibiotics were added at the following concentrations: 100 µg ml−1 ampicillin and 30 µg ml−1 chloramphenicol . Standard methods were used to perform plasmid purification , PCR , ligation , restriction digests , transformation and gel electrophoresis [48] . Construction of isogenic kdpE ( DH11 ) and qseB ( MC474 ) mutants was carried out as previously described [49] . Briefly , 86-24 cells containing pKD46 were prepared for electroporation . A kdpE PCR product was generated using primers kdpEλRed-F and kdpEλRed-R ( Table S2 ) and pKD3 as a template and PCR-purified ( Qiagen ) . A qseB PCR product was generated using primers qseBλRed-F and qseBλRed-R ( Table S2 ) and pKD3 as a template and PCR-purified ( Qiagen ) . Electroporation of the PCR products into these cells was performed; cells were incubated at 22°C for 16 h in SOC , and plated on media containing 30 µg ml−1 chloramphenicol overnight at 42°C . Resulting colonies were patched for chloramphenicol resistance and ampicillin sensitivity , and PCR-verified for the absence of the gene . The chloramphenicol cassette was then resolved from the mutants in order to create non-polar , isogenic kdpE and qseB mutants . Plasmid pCP20 , encoding a resolvase , was electroporated into the mutant strains , and resulting colonies were patched for chloramphenicol sensitivity . Construction of qseC and qseF mutants has been previously published [7] , [35] . Site-directed mutagenesis was carried out using the Quick Change II site-directed mutagenesis kit ( Stratagene ) . Mutagenesis PCR primers were constructed using the Primer X software ( http://www . bioinformatics . org/primerx/ ) and are listed in Table 1 ( qseBD51AF and qseBD51AR ) . The plasmid pVS154 was PCR amplified with the mutagenesis primers according to Stratagene's PCR protocol , generating the plasmid pDH12 ( 86-24 qseB D51A in pBADMycHis ) . The PCR product was digested with DpnI for 3 h at 37°C in order to remove the template plasmid . After digestion , the PCR product was transformed into XL-1 Blue supercompetent cells ( Stratagene ) and plated on selective media . The next day , plasmid DNA was isolated and sequenced to determine if the mutation was present . Cultures were grown aerobically in LB medium at 37°C overnight , diluted 1∶100 in LB or DMEM ( in the presence of self produced AI-3 and in the absence or presence of 10 µM epinephrine ) and grown aerobically at 37°C . 0 . 2% arabinose was added to the media when induction was required . RNA from three biological replicate cultures of each strain was extracted at the late exponential growth phase ( OD600 of 1 . 0 ) using the RiboPure Bacteria RNA isolation kit ( Ambion ) according to the manufacturer's guidelines . The primers used in the real-time assays were designed using Primer Express v1 . 5 ( Applied Biosystems ) ( Table S2 ) . Real-time reverse transcription-PCR ( RT-PCR ) was performed in a one-step reaction using an ABI 7500 sequence detection system ( Applied Biosystems ) . For each 20-µl reaction mixture , 10 µl 2× SYBR master mix , 0 . 1 µl Multi-Scribe reverse transcriptase ( Applied Biosystems ) , and 0 . 1 µl RNase inhibitor ( Applied Biosystems ) were added . Amplification efficiency of each of the primer pairs was verified using standard curves of known RNA concentrations . Melting-curve analysis was used to ensure template specificity by heating products to 95°C for 15 s , followed by cooling to 60°C and heating to 95°C while monitoring fluorescence . Once the amplification efficiency and template specificity were determined for each primer pair , relative quantification analysis was used to analyze the unknown samples using the following conditions for cDNA generation and amplification: 1 cycle at 48°C for 30 min , 1 cycle at 95°C for 10 min , and 40 cycles at 95°C for 15 s and 60°C for 1 min . The rpoA ( RNA polymerase subunit A ) gene was used as the endogenous control . Real-time RT-PCR primers for the LEE genes and rpoA have been previously described [33] . In order to study the binding of QseB to the flhDC promoter EMSAs were performed using the purified QseB protein and the flhDC promoter . DNA probes were then end-labeled with [γ-32P]-ATP ( NEB ) using T4 polynucleotide kinase using standard procedures [48] . End-labeled fragments were run on a 5% polyacrylamide gel , excised and purified using the Qiagen PCR purification kit . Electrophoretic mobility shift assays were performed by adding increasing amounts of purified QseB or QseBD51A protein ( 0–20 µM ) to end-labeled probe ( 10 ng ) in binding buffer [500 µg ml−1 BSA ( NEB ) , 50 ng µl−1 poly-dIdC , 60 mM HEPES pH 7 . 5 , 5 mM EDTA , 3 mM DTT , 300 mM KCl , 25 mM MgCl2] with or without 0 . 1 M acetyl phosphate for 20 min at 4°C . Immediately before loading , a 5% ficol solution was added to the mixtures . The reactions were electrophoresed for approximately 14 h at 65 V on a 5% polyacrylamide gel , dried and exposed to KODAK X-OMAT film . Assays were performed as previously described [31] . Briefly , motility assays were performed at 37°C on 0 . 3% agar plates containing Tryptone media ( 1% tryptone and 0 . 25% NaCl ) . The motility halos were measured at 4 h and 8 h . One liter of LB media was inoculated at 1∶100 and grown to O . D . 0 . 6 at 30°C . The culture temperatures were reduced to 25°C , induced with 400 µM IPTG ( Sigma ) or 0 . 2% arabinose , and grown for either 3 h or 18 h . Cells were harvested , suspended in lysis buffer ( 50 mM phosphate buffer pH 8 , 300 mM NaCl , and 20 mM imidazole ) and lysed by homogenization . The lysed cells were centrifuged and the lysates were loaded onto to a Ni2+- NTA-agarose gravity column ( Qiagen ) . The column was washed with lysis buffer and protein was eluted with elution buffer ( 50 mM phosphate buffer pH 8 , 300 mM NaCl , 250 mM imidazole ) . Fractions containing purified protein were confirmed by SDS-PAGE and concentrated for further use . Liposomes were reconstituted as described previously [4] , [51] . Briefly , 50 mg of E . coli phospholipids ( 20 mg/ml in chloroform; Avanti Polar Lipids ) were evaporated and then dissolved into 5 ml of potassium phosphate buffer containing 80 mg of N-octyl-β-d-glucopyranoside . The solution was dialyzed overnight against potassium phosphate buffer . The resulting liposome suspension was subjected to freeze–thaw in liquid N2 . Liposomes were then destabilized by the addition of 26 . 1 mg of dodecylmaltoside , and 0 . 625 mg of QseC-MycHis was added , followed by stirring at room temperature for 10 min . Two hundred-sixty milligrams of Biobeads ( Biorad ) were then added to remove the detergent , and the resulting solution was allowed to incubate at 4°C for 16 h . The supernatant was then incubated with fresh Biobeads for 1 h at 22°C the next day . The resulting liposomes containing reconstituted QseC-MycHis were frozen in liquid N2 and stored at −80°C until used . Assays were performed as previously described [4] . Briefly , twenty microliters of the liposomes containing QseC-MycHis were adjusted to 10 mM MgCl2 and 1 mM DTT , and 10 µM epinephrine , frozen and thawed rapidly in liquid N2 , and kept at room temperature for 1 h ( this allows for the signals to be loaded within the liposomes ) . [γ32P]dATP ( 0 . 625 µl ) ( 110 TBq/mmol ) was added to each reaction . To some reactions , 12 . 5 µg of response regulator was added . At each time point ( 0 , 10 , 30 min ) , 10 µl of SDS loading buffer ( with 20% SDS , to completely denature the liposome ) was added . For all experiments involving QseC alone , a time point of 10 min was used . The samples were run on SDS/PAGE without boiling and visualized via PhosphorImager . The bands were quantitated by using imagequant version 5 . 0 software ( Amersham Pharmacia ) . Assays were performed as previously described [31] . Briefly , bacteria containing lacZ fusions were grown overnight at 37°C in LB containing the appropriate selective antibiotic . Cultures were diluted 1∶100 and grown in LB , and when necessary supplemented with 0 . 2% arabinose , to an OD600 of 1 . 0 at 37°C . These cultures were then assayed for β-galactosidase activity using o-nitrophenyl-beta-d-galactopyranoside ( ONPG ) as a substrate as described previously [52] .
|
Bacterial cells respond to the human stress hormones epinephrine ( adrenaline ) and norepinephrine ( noradrenaline ) . These hormones are sensed by a bacterial receptor named QseC , which is a sensor kinase in the membrane that increases its autophosphorylation upon binding to these host signals . In addition to recognizing these signals , QseC also responds to a bacterial hormone-like molecule named autoinducer-3 ( AI-3 ) that is produced by the human intestinal microbial flora . In this manuscript we have mapped genetically and biochemically the QseC signaling cascade in the deadly pathogen enterohemorrhagic E . coli ( EHEC ) O157:H7 . EHEC uses this signaling system to activate expression of virulence genes . We show that the QseC signaling cascade is very complex so it can precisely modulate when different virulence traits are expressed . Because these sensor kinases are being evaluated as drug targets , a profound understanding of this signaling pathway is important for the development of novel therapeutic strategies to combat bacterial infections .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"microbiology/microbial",
"evolution",
"and",
"genomics",
"microbiology/cellular",
"microbiology",
"and",
"pathogenesis",
"microbiology/medical",
"microbiology",
"microbiology"
] |
2009
|
The QseC Adrenergic Signaling Cascade in Enterohemorrhagic E. coli (EHEC)
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The ability to taste bitterness evolved to safeguard most animals , including humans , against potentially toxic substances , thereby leading to food rejection . Nonetheless , bitter perception is subject to individual variations due to the presence of genetic functional polymorphisms in bitter taste receptor ( TAS2R ) genes , such as the long-known association between genetic polymorphisms in TAS2R38 and bitter taste perception of phenylthiocarbamide . Yet , due to overlaps in specificities across receptors , such associations with a single TAS2R locus are uncommon . Therefore , to investigate more complex associations , we examined taste responses to six structurally diverse compounds ( absinthin , amarogentin , cascarillin , grosheimin , quassin , and quinine ) in a sample of the Caucasian population . By sequencing all bitter receptor loci , inferring long-range haplotypes , mapping their effects on phenotype variation , and characterizing functionally causal allelic variants , we deciphered at the molecular level how a subjects’ genotype for the whole-family of TAS2R genes shapes variation in bitter taste perception . Within each haplotype block implicated in phenotypic variation , we provided evidence for at least one locus harboring functional polymorphic alleles , e . g . one locus for sensitivity to amarogentin , one of the most bitter natural compounds known , and two loci for sensitivity to grosheimin , one of the bitter compounds of artichoke . Our analyses revealed also , besides simple associations , complex associations of bitterness sensitivity across TAS2R loci . Indeed , even if several putative loci harbored both high- and low-sensitivity alleles , phenotypic variation depended on linkage between these alleles . When sensitive alleles for bitter compounds were maintained in the same linkage phase , genetically driven perceptual differences were obvious , e . g . for grosheimin . On the contrary , when sensitive alleles were in opposite phase , only weak genotype-phenotype associations were seen , e . g . for absinthin , the bitter principle of the beverage absinth . These findings illustrate the extent to which genetic influences on taste are complex , yet arise from both receptor activation patterns and linkage structure among receptor genes .
Bitter taste perception plays a fundamental role in dietary preferences and behaviours , by shaping aversions to foods and drinks . Indeed , averse responses to bitterness are instinctive and drive rejection and avoidance behaviours widely observed in animal models , but also in human infants [1–5] . They are hypothesized to originate with bitter perception’s role as a warning sensor against potentially harmful substances contained in the diet , such as toxins released by plants to deter herbivores , and they belong to diverse chemical classes including acetogenins , alkaloids , flavonoids , phenylpropanes , terpenoids , and thiol compounds [6–9] . These rejection behaviours mediated by bitter perception show evolutionary trends , with responses depending on the occurrence of bitter substances in animal typical diets [10] . Occasionally , bitter substances known to possess desirable pharmacological activities are also deliberately ingested ( e . g . , [11 , 12] ) , nevertheless acceptation of bitter phytonutrient in food remains challenging ( for review see [13] ) . Despite the importance of bitter taste in shaping nutritional behaviours and guarding against toxin ingestion , bitter responses in humans vary profoundly . The classic example of phenotypic diversity in humans is threshold sensitivity to phenylthiocarbamide ( PTC ) , which differs by up to 10 , 000-fold among individuals . Such variation is due to a constellation of interacting factors including environmental effects , age , gender , experience and genetics ( for reviews see [13–15] ) . Particularly strong effects have been found to arise from polymorphism in TAS2R genes , which encode a series of ~25 G protein-coupled receptors expressed in taste buds [16–20] . In the case of PTC perception , polymorphism in TAS2R38 accounts for more than 55% of observed phenotypic variance [17 , 21] . Moreover , genetic polymorphisms occurring at TAS2R loci are common , with numerous high-frequency alleles [22] , suggesting the presence of functionally important receptor variants . Major changes in receptor activity due to such variants have been observed in a few other cases , i . e . , TAS2R9 , TAS2R16 , TAS2R43 , and TAS2R31 [23–27] . In addition , gene association studies suggested functional polymorphic alleles at other TAS2R loci , e . g . TAS2R4 or TAS2R13 [28–30] . An essential aspect of interactions between TAS2Rs and bitter compounds relates to the overlapping agonist profiles , with most TAS2Rs responding to multiple agonists and many agonists stimulating multiple receptors [31] . This combinatorial activation pattern , together with the distribution of TAS2R genes among only four cytogenic locations , which can lead to false-positive genotype-phenotype associations arising from sites in linkage with the causal variants , have so far prevented the full elucidation of bitter perception’s molecular underpinnings [26 , 32–34] . To establish a genetic basis for the observed perceptual differences in the population , we used in this study an integrative approach , sequencing all known TAS2R loci in humans , inferring long-rang haplotypes , mapping their effects on perception of several chemically diverse compounds , and functionally characterizing all allelic variants associated with shifts in perception .
Genetic diversity was assessed by determining whole-gene genotypes of the 25 members of the TAS2R gene family and corresponding copy number variations ( Figs 1 and 2 , S1 Table ) . Across the 48 Caucasian subjects , a total of 93 coding SNPs ( cSNPs ) , including 65 missense SNPs and 2 nonsense SNPs , were identified . Three indels , including 1 rare three-nucleotide in-frame deletion and 2 major deletions spanning TAS2R43 or TAS2R45 locus , were also detected . Genes harboured a mean of 4 cSNPs with a mean of ~1 synonymous and ~3 non-synonymous SNPs per gene . The mean number of haplotypes within genes was 3 . 5 with a range of 1 to 6 , which recombined to form a mean number of 5 . 6 genotypes within genes with a range of 1 to 13 . When only common cSNPs were considered ( i . e . , with frequency ≥ 0 . 05 ) , a total of 67 SNPs , including 45 missense SNPs and 2 nonsense SNPs , and 2 indels were identified , all of which have been reported previously [22 , 26 , 36–40] . Sequenced genes harboured a mean of ~1 synonymous and ~2 non-synonymous common SNPs per gene . While some genes harboured no SNPs ( e . g . , TAS2R10 and TAS2R39 ) , others harboured many . Genes located in the proximal region of the cluster at 12p13 harboured also highest number of SNPs , with 8 at TAS2R31 and -42 , and 9 at TAS2R20 . Of these 45 common missense cSNPs , 27 corresponded to amino acid positions localised in TAS2R transmembrane ( TM ) domains , with 9 SNPs affecting amino acids in TM VI and 6 in TM V ( Fig 3 ) . The remaining SNPs were distributed in sequence areas coding for extracellular domains , intracellular domains , and COOH terminal region , with 8 , 5 , and 5 SNPs , respectively . In addition , 2 nonsense cSNPs result in a premature stop codon in the reading frame and therefore to a putatively non-functional , truncated receptor variant . These common cSNPs recombined across genes to form a total of 59 coding haplotypes , with a mean of 2 . 2 per gene and a range of 1 to 4 . Again , genes localised to the proximal region of 12p13 were most diverse , with 4 haplotypes at TAS2R20 , -31 , and -50 . As with common SNPs , most within-gene haplotypes have been reported previously [22 , 26 , 36–40] . Two common haplotypes were newly identified: one at TAS2R14 ( frequency = 0 . 34 ) , and one at TAS2R42 ( frequency = 0 . 30 ) . High levels of genetic diversity were observed although our population sample , only Caucasian subjects , was relatively homogeneous with respect to ethnic and geographic origin . Thus , chromosomal spatial relations , linkage and block structures among genes might be important contributors to TAS2R-mediated phenotypes . Indeed , the 25 members of the TAS2R gene family are restricted to just three cytogenetic locations 5p15 , 7q31-7q35 , and 12p13 ( Fig 1 ) . Position 5p15 contains a single gene , TAS2R1 , 7q31-35 contains 9 genes distributed across a ~20 . 5 Mb region , and 12p13 contains 15 genes distributed across a ~400 kb region . Further , most of the TAS2Rs at 7q31-7q35 ( TAS2R3 , -4 , -5 , -38 , -39 , -40 , -60 , and -41 ) reside in a 1 . 8 Mb sub-region . Estimates of pairwise D′ and r2 revealed extensive linkage in both the 7q31-7q35 and 12p13 regions . Mean values of D′ and r2 between common cSNPs were 0 . 66 and 0 . 52 across 12p13 , and associated with low p-values ( Fig 4 ) . Nearly identical trends were observed between TAS2R loci , with mean D′ and r2 values of 0 . 66 and 0 . 37 . Similarly , across the 1 . 8 Mb TAS2R3-38 cluster , mean values were 0 . 76 and 0 . 74 for common cSNPs and 0 . 60 and 0 . 63 between TAS2R loci . These trends indicate that TAS2Rs are tightly connected in long-range haplotypes spanning multiple genes . Haplotype block partitions and corresponding long-range haplotypes were then determined for the 25 TAS2R genes ( Fig 5 ) . Analyses inferring haplotype blocks identified six blocks distributed across the TAS2R clusters on chromosomes 7 and 12 . These corresponded to blocks found in the region by previous studies [34 , 43 , 44] . Two were found on chromosome 7 , encompassing the TAS2R3-5 and TAS2R39-60 regions , each of which harboured two long-range haplotypes with frequencies at or above 0 . 05 . Four blocks were found on chromosome 12 , encompassing the TAS2R7-10 , TAS2R13-14 , TAS2R50-19 , and TAS2R31-42 regions , which harboured 1 , 3 , and 5 long-range haplotypes respectively . In addition , whereas blocks on chromosome 7 were flanked by recombination hot spots , we identified no hot spots in the TAS2R13-42 region on chromosome 12 , which seems to indicate that these latter haplotype blocks are determined by linkage disequilibrium decay [45] . Genotype-phenotype association analyses were conducted to elucidate genetic liability for taste phenotypes; phenotype data consisting of individual detection and recognition thresholds for the bitter tastants , as well as concentrations for perceived weak , moderate , strong , and very strong intensities inferred from intensity ratings . Subsequent functional assays provided further insights into the identification of causal TAS2Rs .
Bitter taste perception has long been known to have major heritable components . Common dominant and recessive alleles shaping sensitivity to specific chemical compounds were identified as early as the 1930s ( for review see [47] ) . It is now known that much of this heritability is due to coding variation in TAS2R genes altering receptor affinity , which shapes perception phenotypes . In the classic case , patterns of bitter sensitivity are driven by strong , single-gene effects [17 , 21 , 25 , 26] . However , such associations with only one TAS2R locus appear to be rare . Relationships between TAS2R variation and perception are likely most often complex due to high levels of genetic diversity , linkage between loci and overlap in receptor-agonist interactions , with some agonists stimulating multiple receptors and some receptors responding to multiple agonists [26 , 31] . This hinders elucidation of bitter perception’s molecular underpinnings and , consequently , their downstream effects on aversion and ingestive behaviours [34] . Therefore , until now only a limited number of TAS2R genes have been implicated in the modification of ingestive behavior ( for a review see [48] ) . Our findings reveal the extent to which linkage constrains both , variation in TAS2R genes and patterns of overlap in receptor-agonist affinity , and the impact of these factors on bitter taste phenotypes . Human TAS2Rs are highly diverse , with per nucleotide heterozygosity significantly higher than genome-wide averages , elevated rates of non-synonymous substitution , and fixation indices ( FST values ) indicative of substantial population differentiation [22] . This suggests that combinatorial variation across loci could , in principle , be extremely high . However , patterns of linkage disequilibrium in our sample of the Caucasian population demonstrate that such diversity is limited . While a total of 93 SNPs were present , which could in principle recombine to form more than 7 quintillion ( 7 . 71 x 1030 ) different combinations , most variation resided in just six blocks , each harbouring just 1 to 4 haplotypes . This finding has two implications . First , it suggests that while humans harbour 25 functional TAS2R loci , each of which encodes a receptor with alleles responsive to different ranges of agonists , phenotypic responses are likely correlated across compounds regardless of whether they are mediated by the same receptor . Second , linkage disequilibrium and block structures spanning loci are likely major sources of spurious genotype-phenotype associations . Because blocks often span several loci , yet few long-range haplotypes are present , true genotype-phenotype associations will most often be accompanied by false positives arising from sites in LD with the causal variants . This problem is compounded by the prevalence of non-synonymous variants in TAS2Rs , which stand out as potential functional receptor candidates , making them difficult to rule out as causal . These issues were evident in our association analyses , which were able to localize signals for amarogentin , grosheimin , and quassin at the block level but not with respect to specific SNPs ( Figs 7 , 8 and S1–S3 ) . Functional assays characterizing the kinetic properties of individual TAS2R variants in our sample were successful in resolving the positions of sites shaping phenotypes , revealing complex variation in response across loci and alleles ( Figs 6–8; S2 Table ) . Within each haplotype block implicated in associations , we found at least one locus harboring functionally polymorphic alleles corresponding to receptor variants activated in the concentration range perceived as bitter by subjects , thus pinpointing the sites underlying variable perception of four tastants . However , the mechanisms underlying variation in sensitivity varied from locus to locus . At TAS2R30 , the high- and low-sensitivity receptor variants , which differed drastically in response to amarogentin and quassin , were distinguished by a single amino acid position ( L252F ) in the third extracellular domain of the receptor , which is hypothesized to interact directly with agonists . High- and low-sensitivity TAS2R46 variants also differed at a single amino acid position ( L228M ) ; however , this site , located in the sixth transmembrane domain of the receptor , is highly conserved among TAS2Rs and thought to be essential to the basic functionality of the receptor , which likely explains the strong effects of TAS2R46-L228M on phenotype . TAS2R46 also harbored a common allele coding a premature stop codon ( W250X ) , resulting in the production of a severely truncated , dysfunctional receptor [22] . At TAS2R43 , the high- and low-sensitivity receptor variants differed at position W35S in the first intracellular domain and H212R in the fifth transmembrane domain; by considering the high degree of sequence similarity between TAS2R43 and TAS2R31 , the sole presence of amino acid substitution W35S , corresponding to the deleterious substitution TAS2R31-R35W , likely explains the severe impaired functionality of the receptor [26] . Beyond these substitutions , TAS2R43 harboured a high-frequency whole-gene deletion allele completely lacking an open reading frame , and unable to produce protein at all [25 , 26] . In addition to identifying simple phenotypic associations with alleles at single loci , our analyses revealed associations arising from linkage disequilibrium across loci , demonstrating the complexity of relationships between TAS2R variation and phenotypic response . In the case of amarogentin and quassin , several loci ( TAS2R30 , -43 , and -46 ) harboured both high- and low-sensitivity alleles , suggesting that loci could individually contribute up- or downward shifts in phenotype . However , only TAS2R30 harboured receptor variants responsive across the threshold ranges of subjects , indicating that it alone accounts for most variability in perception . This relationship is similar to long known patterns of bitter sensitivity driven by strong , single-gene effects . In the case of grosheimin , two loci ( TAS2R43 and -46 ) harboured both high- and low-sensitivity alleles . However , these were maintained in the same linkage phase such that the sensitive allele of TAS2R43 was linked with the sensitive allele of TAS2R46 and the insensitive allele of TAS2R43 was linked with the insensitive allele of TAS2R46 . Thus , while both loci harboured variation able to explain observed phenotypes , their contributions were strongly correlated . In the case of absinthin and cascarillin , again two loci ( TAS2R30 and -46 ) harboured both high- and low-sensitivity alleles . However , linkage disequilibrium maintained these in opposite phase such that the sensitive allele of TAS2R30 was linked with the insensitive allele of TAS2R46 , and the insensitive allele of TAS2R30 was linked with the sensitive allele of TAS2R46 . Thus , most subjects carried at least one allele sensitive to absinthin and cascarillin , explaining both the low mean threshold response to these compounds in subjects and the weak statistical associations for individual loci . These findings , together with prior evidence of extensive overlap in sensitivity across loci and agonists , suggest that while strong associations between a single TAS2R locus and phenotype may occur , they are likely uncommon . Moreover , linkage between TAS2R loci can cause confounds resulting in both false positive and false negative results in association analyses . Thus , dissecting genetic effects on bitter taste sensitivity through association analysis alone is likely to be inaccurate in most situations . An essential aspect of TAS2R diversity in our sample of the Caucasian population , which has been broadly observed in population genetic studies , was that diversity is extremely high . In total we identified 93 SNPs , of which 67 SNPs were common , with frequencies above 5% ( Fig 3 ) . Moreover , every subject harboured a different allele combination at the SNP positions . Thus , inherited variation in taste responses was not a rarity as is the case for many phenotypes , such as diseases , but the norm . Further , our European sample , though ethnically homogeneous , captured most TAS2R variation found to date in worldwide populations [22 , 40] . For example , beyond the 93 SNPs found in our subjects , Kim et al . ( 2005 ) reported only 10 additional common SNPs ( 5 synonymous and 5 non-synonymous ) across a panel of 55 Africans , Asians , Europeans , and Native Americans . Hence , differences at TAS2R loci between individuals from ethnically diverse populations are modest in comparison to differences among individuals from the same population , consistent with more general observations on large-scale data sets [49 , 50] . These patterns suggest that the association trends in our data are likely not restricted to Europeans , but relevant in most populations . Yet , even if receptor polymorphism and genomic structure dominantly shape bitter taste perception , further studies need to be performed to enable a complete comprehension of variation in bitter taste perception , taking into account that other relevant factors may also play a significant role . Indeed , besides receptor-agonist interactions , differences in taste receptor gene expression levels could also contribute to individual differences in bitter taste perception . The importance of polymorphisms in the putative promoter regions of taste genes further indicates overlapping genetic influences on receptor expression and functionality [51 , 52] . In addition , differences at peripheral level , e . g . in taste signaling cascade components [53] , may also influence taste perception , as well as differences in signal transmission by afferent taste nerves and signal processing at central level . Hormones may also , at the level of the individual , impact bitter taste perception , e . g . hunger-satiety hormones as well as sex hormones ( for review see [54 , 55] ) . Nonetheless , deciphering receptor activation patterns and linkage structure among TAS2R genes is an important prerequisite to establish a solid basis to assess bitter taste variations in the population . This may pave the way to evaluate the consequences of these variations in food rejection and ultimately help to improve public health .
This work was conducted in accordance to the Declaration of Helsinki on Biomedical Research Involving Human Subjects and approved by the Ethics Committee of the University of Potsdam ( Germany ) through decision 11 / 27 . Session / 2009 . All participants gave written informed consent . The subject panel was composed of 48 unrelated Caucasian subjects ( 39 women , 9 men; age range 21 to 59 years , mean age 30 . 6 years ) , recruited at the German Institute of Human Nutrition Potsdam-Rehbruecke ( Germany ) . All were pre-screened to avoid inclusion of individuals with health problems and overt taste pathologies; pregnant and breast-feeding women were also excluded . Each subject participated in the entire course of the study , which included one training session and nine experimental sessions . Visits consisted of DNA collection and psychophysical tests for genotyping and phenotypic analyses , respectively . General taste abilities were also assessed for the bitter , salty , sour , and sweet taste during the first session . Six structurally diverse bitter substances , found at low concentrations in various beverages , and known to exhibit pharmacological properties at high concentrations , were used to probe phenotypic and molecular responses ( S1 Fig ) . These included absinthin ( a dimeric sesquiterpene lactone ) , amarogentin ( a secoiridoid glycoside ) , cascarillin ( a diterpene lactone ) , grosheimin ( a sesquiterpene lactone ) , quassin ( a triterpene lactone ) , and quinine ( a quinoline alkaloid ) . Absinthin , cascarillin , and grosheimin were isolated from crude vegetable material as detailed in previous studies [31 , 56] . Amarogentin and quassin were purchased from Chromadex Inc . ( Irvine , CA , USA ) , quinine hydrochloride from Sigma-Aldrich Co . ( St . Louis , MO , USA ) . Salicin , sodium chloride , citric acid , and sucrose ( Sigma-Aldrich Co . ) were used as reference tastants for assessing bitter , salty , sour , and sweet perception , respectively . Gene locations and coding sequences of the 25 TAS2R genes were obtained from genomic scaffolds 1103279188109 , 1103279188381 , 1103279188228 , and 1103279188408 of the whole genome assembly released by the Venter Institute human reference genome as well as from all subjects in the present study [57] ( Fig 1 ) . Corresponding amino acid sequences were aligned according the modified version of the Feng-Doolittle progressive alignment algorithm ( Align X , Vector NTI; Life Technologies , Carlsbad , CA , USA ) [58] . Alignment was then manually adjusted on the basis of previous in silico and in vitro experiments , in order to conserve structural and functional key domains , e . g . , transmembrane domains and the conserved glycosylation site [41 , 42 , 59] . A neighbour-joining tree with bootstrap values was then constructed from aligned sequences using Clustal X [60] . Genomic DNA was obtained from saliva samples collected using Oragene DNA self-collection kits ( Oragene DNA; DNA Genotek Inc . , Kanata , Canada ) , and purified using prepIT-L2P kits ( prepIT-L2P; DNA Genotek Inc . ) . Complete nucleotide sequences of every TAS2R coding region were then obtained for all subjects . Locus-specific primers localized in the flanking regions of each gene , ~100 bp upstream of the start codon and ~100 bp downstream of the stop codon , were designed using the Primer-Blast tool or obtained from previous studies [22 , 26 , 40 , 61] . Corresponding DNA fragments of at least ~1 kbp were amplified by PCR using a high-throughput polymerase ( Advantage 2 polymerase mix; Takara Bio Inc . , Otsu , Japan ) . Amplified DNA fragments were sequenced by capillary electrophoresis of both forward and reverse strands ( Eurofins MWG Operon , Ebersberg , Germany ) . Reads were assembled and trimmed to remove low-quality sequence ( Vector NTI; Life Technologies ) . All single-nucleotide polymorphisms ( SNPs ) were then identified and individual genotypes were determined . Departures from the Hardy-Weinberg equilibrium were tested to rule out genotyping problems . Previously reported major deletions at TAS2R43 and -45 loci , ~39k b and ~32 kb in length , respectively , were characterised by multiplex PCR reactions . These were performed using primer sets targeted within , outside , and spanning the deleted regions such that amplifications produced alternate products in deleted and non-deleted alleles ( S4 Fig ) . Gel separation and sequencing of the resulting fragments ( Advantage 2 polymerase; Takara Bio Inc . ) revealed whether a subject carried zero , one or two copies of each gene . DNA sequence and copy-number data were jointly used to call genotypes . Haplotypes were then either directly ascertained for homozygous individuals or inferred using PHASE , which utilizes Bayesian algorithms to resolve haplotypes in heterozygous individuals [62 , 63] . In cases of uncertain phase , haplotypes were confirmed by comparison with previously published data or identified by cDNA cloning and sequence analysis [26] . Linkage disequilibrium measures were then obtained by calculating D’ , r2 and corresponding p-values between multi-allelic loci for both SNPs and genes [64 , 65] . Haplotype block partitions were generated according to the four gamete rule with a 5% cut-off score , and manually adjusted for TAS2R19 and TAS2R42 , which SNPs spanned several blocks [66 , 67] . Corresponding long-range haplotypes were then inferred [62 , 63] . Algorithms for visual representation were specifically implemented in Matlab , based on the population genetics and evolution toolbox ( Matlab; The MathWorks Inc . , Natick , MA , USA ) [68] . Experiments were conducted at the sensory analysis laboratory of the German Institute of Human Nutrition Potsdam-Rehbruecke , according to good practice guidelines [69 , 70] . Detection and recognition thresholds were assessed using a procedure adapted from the norm ISO 13301:2002 of the International Organization for Standardization: a four-alternative ascending forced-choice procedure , followed by yes-no questions about the bitter taste quality of the quoted samples [71] . Perceived bitter taste intensities were rated on the general Labelled Magnitude Scale ( gLMS; [72–74] ) . Concentration series consisted of geometric sequences of twelve steps , with a 1 . 5 common ratio and the following concentration ranges: 2 . 3x10-8–2 . 0x10-6M , 3 . 5x10-9–3 . 0x10-7 M , 4 . 6x10-7–4 . 0x10-5 M , 5 . 8x10-7–5 . 0x10-5 M , 1 . 2x10-8–1 . 0x10-6 M , 4 . 6x10-7–4 . 0x10-5 M , for absinthin , amarogentin , cascarillin , grosheimin , quassin , and quinine , respectively . For each 4-AFC test , four coded samples containing 10 ml solution were presented simultaneously; one containing the bitter tastant diluted in mineral water ( Evian; Danone , Paris , France ) and three containing mineral water only . At each concentration , subjects were challenged to identify the different sample , specify whether the quoted sample tasted bitter , and rate the perceived bitter intensity . Tests were performed with nose clips and oral rinsing , with a 45 s pause between concentrations . Training sessions were first used to familiarize subjects with the experimental procedures , and secondly , to assess general taste abilities . Concentration series consisted of geometric sequences of six steps , with a 1 . 5 common ratio and the following concentration ranges: 3 . 5x10-5–2 . 0x10-3M , 6 . 9x10-4–4 . 0x10-2 M , 2 . 6x10-4–1 . 5x10-2 M , 6 . 9x10-4–4 . 0x10-2 M , for salicin , sodium chloride , citric acid , and sucrose used as reference tastants for bitter , salty , sour , and sweet taste , respectively . Following training , subjects tested each tastant in triplicate over nine sessions . Latin square designs extended for first-order carry-over effects were used to counterbalance presentation order of the test compounds over the test sessions , across subjects and for each test compound , as well as presentation order of the samples at each concentration across both repetitions and subjects . Sensory sessions were monitored and data automatically collected ( Fizz; Biosystèmes , Couternon , France ) . Detection and recognition probabilities of the bitter samples were analysed per repetition and subject . Relationships between probabilities ( detection or recognition probabilities ) and concentrations were fitted by a logistic regression model using the maximum-likelihood method . Threshold value and slope of the logistic curves were then obtained per repetition and subject , using a self-implemented toolbox ( Matlab; The MathWorks Inc . ) . No repetition effect was observed . Where required , outliers were discarded according to the Peirce’s criterion [75 , 76] . Perceived intensities , expressed in percentage of the scale length , were analysed similarly . Concentrations were subsequently inferred for weak , moderate , strong , and very strong intensities , corresponding respectively to 6 , 17 , 34 . 7 , and 52 . 5% of the scale length . General linear mixed model analyses were performed at SNP , gene , and LD block level ( SAS Institute Inc . , Cary , NC , USA ) . Concentrations corresponding to detection thresholds , recognition thresholds , or perceived intensities were treated as dependent variables following a log-normal distribution . Genotype or haplotype with frequencies above 0 . 05 were used as independent variables and subjects as random variables . For analyses at the SNP level , probability values were assessed at an uncorrected significance level of 0 . 05 , and at an experiment-wide significance threshold required to keep a significance level of 0 . 05 , thus correcting for multiple comparisons [77] . For analyses at gene-specific level and LD block level , a Bonferroni correction for multiple corrections was applied . Allelic responses to agonists were quantified using in vitro heterologous expression assays designed in previous studies of TAS2R receptor function , which successfully mimic responses in vivo with respect to both magnitude and concentration range [17 , 23 , 25 , 26 , 46] . DNA fragments containing TAS2R coding sequences were first amplified from genomic DNA by PCR using a proofreading polymerase ( PfuUltra II Fusion HotStart DNA Polymerase; Agilent Technologies , Santa Clara , CA , USA ) and cloned into a plasmid vector according to the manufacturer’s protocol ( Zero Blunt TOPO PCR Cloning Kit; Life Technologies ) . A second PCR was performed using specific cloning primers to facilitate subcloning into the expression vector , which was then modified to add an N-terminal signal for cell surface localisation and a C-terminal epitope for immunocytochemical detection to the receptor sequence ( Fast Link DNA Ligation Kit; Epicentre , Illumina Inc . , Madison , WI , USA ) ( pcDNA5/FRT Mammalian Expression Vector; Life Technologies ) . Empty vector was used as a negative control [23 , 31] . Functional assays were carried out in HEK 293T cells stably expressing the G protein chimera Gα16gust44 and transiently transfected with TAS2R alleles subcloned into the expression vector [78] . Calcium imaging was performed using an automated fluorometric imaging plate reader by exposing transfected cells to test compounds dissolved in assay buffer or to assay buffer alone ( FLIPR Tetra; Molecular Devices , LLC , Sunnyvale , CA , USA ) . Changes in cytosolic calcium levels were monitored by measuring fluorescence intensity of a calcium-sensitive dye previously added ( Fluo-4 AM; Life Technologies ) . Six replicates were carried out for each bitter stimulus , on separate experimental days , with each replicate consisting of concentration series of each bitter tastant . Prior to final analysis , fluorescence data from functional assays , expressed in relative fluorescence units ( RFU ) , underwent three corrections . First , a correction calculated from baseline values was applied to compensate for well-to-well fluctuations . A second correction calculated from negative control values was applied to correct for receptor independent artefacts and signal drift . A third correction calculated from positive control values was applied to facilitate comparison of data obtained from different experimental days . Fluorescence ratios ( ( F-F0 ) /F0 ) , obtained by subtracting the background fluorescence from fluorescence peak height and then dividing the difference by the background fluorescence , were then used for data analysis . Variance analyses were performed , followed by Bonferroni multiple comparisons tests ( SPSS 20; IBM Corporation , Armonk , NY , USA ) . Threshold response values were then defined as the first concentration eliciting a significant activation of the receptor , with empty vector acting as a negative control . Finally , dose-response curves were fitted to the Hill equation by nonlinear regression in order to determine half maximal effective concentrations ( EC50 ) and maximal amplitude [79] ( SigmaPlot; Systat Software Inc . , Chicago , IL , USA ) .
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Human bitter taste is believed to protect us from the ingestion of poisonous substances , thereby shaping food rejections . Bitter perception differs , however , across individuals , due to genetic variations in the ~25 bitter taste receptor ( TAS2R ) genes . A famous example known since the 1930s is the inherited bitter taste sensitivity to phenylthiocarbamide , which is associated with genetic polymorphisms in a single TAS2R gene . Yet , such simple receptor-substance associations do not reflect the full complexity of bitter perception , since individual bitter substances frequently activate several TAS2Rs . Here , we provide an in-depth analysis of the genetic variability influencing human bitter taste . While each study subject carried a different set of genetic polymorphisms , we found that most variations reside in just six blocks , each harboring only one to five haplotypes . Thus , besides simple associations between taste and TAS2R gene polymorphisms , we revealed complex associations dependent on linkage between several high- and low-sensitivity alleles . Indeed , subjects carried either sensitive or insensitive alleles for receptors sensitive to grosheimin , a bitter compound in artichoke , or at least one sensitive allele for receptors specific for absinthin , the bitter principle of absinth . In short , simple associations and complex genomic linkage determine sensitivity to selected dietary bitter compounds .
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[
"Abstract",
"Introduction",
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"Discussion",
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[] |
2015
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Receptor Polymorphism and Genomic Structure Interact to Shape Bitter Taste Perception
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Tuberous sclerosis complex ( TSC ) is a multisystem genetic disease that manifests with mental retardation , tumor formation , autism , and epilepsy . Heightened signaling through the mammalian target of rapamycin ( mTOR ) pathway is involved in TSC pathology , however it remains unclear how other signaling pathways are perturbed and contribute to disease symptoms . Reduced long-term depression ( LTD ) was recently reported in TSC mutant mice . We find that although reduced LTD is a feature of the juvenile mutant hippocampus , heightened expression of metabotropic glutamate receptor 5 and constitutively activated Erk signaling in the adult hippocampus drives wild-type levels of LTD . Increased mGluR5 and Erk results in a novel mTOR-independent LTD in CA1 hippocampus of adult mice , and contributes to the development of epileptiform bursting activity in the TSC2+/− CA3 region of the hippocampus . Inhibition of mGluR5 or Erk signaling restores appropriate mTOR-dependence to LTD , and significantly reduces epileptiform bursting in TSC2+/− hippocampal slices . We also report that adult TSC2+/− mice exhibit a subtle perseverative behavioral phenotype that is eliminated by mGluR5 antagonism . These findings highlight the potential of modulating the mGluR5-Erk pathway in a developmental stage-specific manner to treat TSC .
Tuberous sclerosis complex ( TSC ) is a multisystem autosomal dominant disorder that is characterized by the development of systemic benign hamartomas and cortical tubers , mental disability , autism , and epilepsy [1] , [2] . Affecting approximately 1 in 6 , 000 people , TSC is caused by mutations in either of the tumor suppressor genes TSC1 or TSC2 , which result in altered signaling through multiple cellular pathways that impact neurological processes such as nervous system development , neuronal migration , and synaptic function [1] , [3] , [4] . Epilepsy occurs in approximately 90% of patients and often during the first year of life [1] , [2] , [5] , [6] . TSC1 and TSC2 form a heterodimeric complex ( TSC1/2 ) that receives signals from protein kinase B ( Akt ) [7]–[9] , extracellular signal-regulated kinase ( Erk1/2 ) [10] , [11] , 5′ adenosine monophosphate activated protein kinase ( AMPK ) [12] , TNFα-IκB kinase β signaling [13] , and glycogen synthase kinase-3β ( GSK3β ) [14] . In this manner , TSC1/2 functions as a signaling node that modulates the activity of the mammalian target of rapamycin signaling complex-1 ( mTORC1 ) [15] , [16] . mTORC1 regulates postsynaptic protein translation , and thereby controls activity-dependent plasticity; specifically , long-term potentiation ( LTP ) [17] and a form of long-term depression ( LTD ) induced by the group 1 metabotropic glutamate receptor ( mGluR1 and mGluR5 ) agonist , ( S ) -3 , 5-Dihydroxyphenylglycine ( DHPG ) [18] . Given its role in synaptic plasticity , work has sought to elucidate a role for mTOR in epileptogenesis and the activity-dependent strengthening of neuronal networks following seizure [19]–[21] . The specific mTOR inhibitor , rapamycin , blocks the development of spontaneous seizures across multiple models of epileptogenesis [20] , [22] , [23] ( but see [24] ) . Since inhibition of mTORC1 may have therapeutic value in treating TSC [21] , [25] , pathways that signal to mTORC1 could represent viable avenues for treating TSC . Recent work by a number of groups shows that juvenile mice ( 21 d ) heterozygous for TSC2 show reduced hippocampal mGluR-LTD magnitude [26] , [27] . We find that although juvenile TSC2+/− mutant mice do indeed manifest reduced LTD magnitude , adult mice ( 2 mo ) show no difference in LTD magnitude from wild-type mice . However , this adult mGluR-LTD in TSC2+/− mutant mice is mechanistically distinct from wild-type LTD; adult mGluR-LTD in the TSC2+/− hippocampus is insensitive to mTOR inhibition . Thus , the TSC2 mutant hippocampus utilizes a compensatory pathway to restore LTD magnitude . We report that whereas WT mice show a developmental down-regulation of mGluR5 expression and Erk phosphorylation , TSC2+/− mice maintain a heightened juvenile level of mGluR5 expression through adulthood . Inhibition of mGluR5 or Erk signaling , but not PI3k-Akt signaling , is sufficient to restore mTOR dependence in adult mGluR-LTD in TSC2+/− hippocampus . Additionally , we report an epileptiform bursting phenotype in TSC2+/− CA3 region of the hippocampus induced by prolonged incubation with DHPG . TSC2+/− slices were more likely to develop long synchronous bursts , compared to WT slices—a phenotype that was eliminated by antagonism of mGluR5-Erk signaling .
In WT hippocampal slices , LTD induced with the group 1 mGluR agonist , DHPG ( 50 µM , 10 min ) , requires mTORC1-dependent signaling and protein translation [18] , [28] . Similar to recently published reports [26] , [27] , [29] , we found that DHPG induced a lower magnitude of LTD in 21-d-old juvenile TSC2+/− mice compared to WT mice of the same age ( Figure 1a ) . Consistent with the findings of Auerbach et al . [27] , the reduced LTD magnitude in TSC2+/− was restored to WT levels with rapamycin . However , we noticed that at 2 mo of age , LTD in mutant mice was nearly indistinguishable in magnitude from WT ( Figure 1c ) . We sought to characterize this unexplored LTD evident in adult 2-mo-old TSC2+/− mutant mice . To assess the role of mTORC1 activity in adult TSC2+/− LTD , we applied rapamycin to TSC2+/− and WT slices . Consistent with the work of Hou and Klann ( 2004 ) [18] , rapamycin reduced mGluR-LTD in WT slices ( Figure 1d ) . Surprisingly , rapamycin had no effect on mGluR-LTD in adult TSC2+/− slices ( Figure 1e ) . We recently showed that pharmacological activators of AMPK could mimic rapamycin by inhibiting hippocampal mTOR [30] . Thus , we asked whether the AMPK activator metformin could inhibit mGluR-LTD in TSC2+/− slices . Figure 1f shows that , as with rapamycin , metformin also failed to inhibit mGluR-LTD in adult TSC2+/− slices , but was able to inhibit LTD in WT slices ( Figure 1g ) . This inhibition was AMPK-dependent because it could be blocked by the AMPK antagonist , Ara-A ( Figure 1g ) . Since mTORC1 governs postsynaptic protein translation , we tested the possibility that mGluR-LTD in TSC2+/− hippocampus may also be protein synthesis-independent . Treatment with the general translational inhibitor , anisomycin , eliminated LTD ( Figure 1h ) , demonstrating a continued requirement for protein synthesis for LTD expression in adult TSC2+/− . Rapamycin works , in part , by reducing the association of mTOR with its obligate partner protein , Regulatory Associated Partner of TOR ( RAPTOR ) , to reduce activation of downstream targets , such as rpS6 [31] . Since rapamycin failed to impact mGluR-LTD in TSC2+/− slices , we tested whether rapamycin was still capable of reducing RAPTOR-mTOR association in TSC2+/− hippocampus . We immunoprecipitated mTORC1 from slices incubated with DHPG for 10 min in the presence and absence of rapamycin . In the presence of DHPG , rapamycin treatment significantly reduced RAPTOR-mTORC1 binding equally well in WT and TSC2+/− slices ( Figure 2a and 2b ) . Additionally , rapamycin significantly reduced p-S6 levels in WT and TSC2+/− slices in the presence of DHPG ( Figure 2c and 2d ) . These data show that in TSC2+/− slices rapamycin is able to disrupt the mTORC1 complex and inhibit downstream signaling to rpS6 . Together , these data demonstrate that the adult TSC2+/− hippocampus maintains a requirement for protein translation for the expression of mGluR-LTD yet appears to have altered signaling that circumvents mTORC1 activity . In Fragile X Syndrome ( FXS ) , LTD is rendered mTOR-independent by hyperactive mGluR signaling [32] . This observation along with a report of heightened mGluR5 expression in cortical tubers resected from TSC patients [33] prompted us to investigate this receptor in the TSC2+/− mouse . Western blot analysis of acutely harvested hippocampal lysates shows an age-associated decrease in mGluR5 levels in WT lysates . In contrast , mGluR5 expression in older TSC2+/− mice remains at the high juvenile level ( Figure 3a and 3b ) . Thus , adult TSC2+/− hippocampus maintained higher levels of mGluR5 expression over WT , whereas there was no difference in receptor expression in 21-d-old mice . Group 1 mGluR receptors ( mGluR1 and mGluR5 ) activate Gq-coupled second messenger cascades , which increase PI3K-Akt and Mek-Erk signaling [18] , [34] . We therefore compared the activation status of Akt and Erk in acutely harvested WT and TSC2+/− hippocampi ( Figure 3a and 3b ) . As with mGluR5 , phosphorylated Erk1/2 ( T202/Y204 ) levels were similar in young WT and mutant hippocampi , but whereas phospho-Erk levels were reduced in adult WT mice , they remained at the high juvenile level in TSC2+/− tissue . Phosphorylated Akt ( T308 ) levels showed an age-dependent decrease in both mutant and WT hippocampi such that there were no differences between genotypes ( Figure 3a and 3b ) . To determine whether heightened mGluR5 signaling contributes to the observed rapamycin-insensitive LTD in adult TSC2+/− hippocampus , we preincubated TSC2+/− hippocampal slices with the noncompetitive mGluR5 antagonist , 2-Methyl-6- ( phenylethynyl ) pyridine hydrochloride ( MPEP ) . Despite heightened mGluR5 levels in adult TSC2+/− , preincubation with MPEP ( 40 µM for 20 min , followed by a 20-min washout period ) had no effect on mGluR-LTD magnitude ( Figure 3c ) . However , when rapamycin was added during the MPEP washout period , we observed a striking restoration of rapamycin-sensitivity such that rapamycin reduced LTD magnitude ( Figure 3d ) . Metformin showed the same inhibition as rapamycin ( Figure 3d ) . Importantly , the level of reduction of mGluR-LTD with MPEP and rapamycin closely resembled the effect of rapamycin alone in WT mGluR-LTD ( compare Figures 3d and 1d ) . Consistent with the work of Hou and Klann ( 2004 ) [18] in WT slices , MPEP treatment without washout completely eliminated mGluR-LTD in TSC2+/− slices , demonstrating that mGluR5 signaling is required for the induction of LTD by DHPG ( Figure 3e ) . We observed that pre-incubation with MPEP prevented p-Erk activation in the presence of DHPG in mutants , whereas the same treatment of WT slices did not impact Erk activation ( Figure 3f and 3g ) . MPEP treatment also caused a reduction in Akt activation in TSC2 mutants ( Figure 3f and 3g ) . In the absence of stimulation with DHPG , mGluR5 antagonism with MPEP had no effect on Erk , Akt , or S6 phosphorylation levels in WT or TSC2+/− ( Figure 4h ) . To determine how PI3K-Akt and Mek-Erk signaling might contribute to the mTOR-independent LTD observed in TSC2+/− slices , we applied pharmacological antagonists of PI3K signaling ( wortmannin and LY294002 ) , and Mek-Erk signaling ( U0126 ) during LTD induction with DHPG . In accordance with previous studies [18] , the expression of LTD was significantly reduced with LY294002 and wortmannin in WT slices ( Figure 4a ) . In contrast to WT , antagonism of PI3K-Akt signaling in adult TSC2+/− slices had no effect on the expression of LTD , nor did it restore rapamycin sensitivity ( Figure 4b and 4c ) . This demonstrates that PI3K inhibition does not reproduce the effects of mGluR5 inhibition in TSC2+/− . We hypothesized that the hyperactive Erk signaling was bypassing or short-circuiting the mTOR pathway to drive LTD and render it mTOR-independent and rapamycin insensitive . To address this , we first performed a dose response of U0126 to find a concentration that would “dial down” Erk signaling to untreated WT levels and then assessed rapamycin sensitivity in TSC2+/− slices . From the concentration series of U0126 in TSC2+/− slices , we determined that a relatively low-dose ( 200 nM ) U0126 reduced p-Erk in TSC2+/− slices to untreated WT levels ( Figure 4d ) . If reducing Erk activity is sufficient to restore rapamycin sensitivity in TSC2+/− slices , then reduction of p-Erk to WT levels would be expected to leave mGluR-LTD unaffected , yet render slices responsive to rapamycin . Application of 200 nM U0126 alone did not affect mGluR-LTD magnitude in WT ( Figure 4e ) or TSC2+/− slices ( Figure 4f ) . However , addition of rapamycin was now capable of reducing mGluR-LTD in TSC2+/− slices ( Figure 4f ) . These data indicate that the subtle reduction of Mek-Erk signaling was sufficient to restore a WT-like response to rapamycin and recapitulate the effects of preincubated MPEP on mGluR-LTD in TSC2+/− slices ( compare Figure 3d and Figure 4f ) . Western blot analysis shows that low-dose 200 nM U0126 alone did not directly impact mTOR signaling downstream to rpS6 ( Figure 4g ) . In the presence of DHPG , however , U0126 prevented activation of rpS6 , an effect that was enhanced with rapamycin ( Figure 4h ) . These observations , along with the elevated levels of mGluR5 and phospho-Erk in TSC2+/− slices , support the hypothesis that the aberrant plasticity in TSC2+/− slices arises from heightened mGluR5 and Erk signaling . Epilepsy occurs in approximately 80%–90% of individuals with TSC often presenting in the first year of life [3] , [35] . Epileptiform bursting activity can be induced in hippocampal slices with prolonged activation of group 1 mGluRs with DHPG . This alteration in excitability persists for hours after the removal of DHPG , is protein synthesis-dependent , and represents an enduring change in network excitability that mimics seizures [36]–[38] . Due to our observation that mGluR5 expression is heightened in the TSC2+/− hippocampus , we reasoned that TSC2+/− slices should be more susceptible to the development of DHPG-induced epileptiform bursting . To test this , we measured field activity in CA3 stratum pyramidale in TSC2+/− and WT slices following DHPG treatment ( 50 µM , 30 min ) and quantified burst number and duration in slices that showed spontaneously occurring synchronous activity . Ictal epileptiform activity was defined as synchronous activity of greater than 2 s with intraburst frequencies of 2 Hz or greater . Interictal epileptiform activity was defined as spontaneously occurring synchronous activity with a duration of less than 2 s . One hour after removal of DHPG , TSC2+/− slices produced significantly longer burst durations ( Figure 5a and 5b ) and displayed more long-duration ictal events compared to WT ( Figure 5c ) . In WT slices , MPEP or rapamycin treatment during the DHPG incubation did not significantly impact ictal burst duration ( Figure 5b ) , nor did they affect the development of epileptiform activity ( Figure 5d–f ) . However , in TSC2+/− slices MPEP caused a significant reduction in both the duration of ictal bursts ( Figure 5b ) as well as the proportion of slices that developed ictal activity ( TSC2+/−: 58 . 1% DHPG versus 30 . 0% DHPG+MPEP ) ( Figure 5d ) . Incubation of WT or TSC2+/− slices with 20 µM U0126 produced an even greater reduction in average bursting duration than MPEP ( Figure 5b ) . MPEP and U0126 produced a similar and significant reduction in the proportion of ictal slices ( Figure 5d ) and each caused a dramatic shift in the bursting profile in TSC2+/− slices toward shorter duration bursts ( Figure 5g and 5h , respectively ) . Overall , rapamycin was less effective at reducing CA3 bursting . Although rapamycin did reduce the average burst duration in TSC2+/− slices ( Figure 5b ) , rapamycin had no statistical effect on the proportion of interictal and ictal slices ( Figure 5d ) , nor did it alter the bursting profile ( Figure 5i ) . The CA3 bursting data demonstrate that mGluR5 and Erk signaling is involved in the development of epileptiform activity in TSC2+/− CA3 hippocampus in response to DHPG , and that the enhanced epileptogenic potential of TSC2+/− slices can be blocked with mGluR5 or Erk antagonism . In summary , the cumulative probability curve shows that addition of MPEP or U0126 to mutant slices reduces the 50th percentile burst duration from 4–5 s to 3 s or 2 s , respectively ( Figure 5j ) . In a previous report , Ehninger et al . ( 2008 ) analyzed cognitive and stress-related behaviors associated with tuberous sclerosis in TSC2+/− mice . They reported that TSC2+/− mice display cognitive and stress-related deficits that were corrected by rapamycin [39] . We sought to extend the behavioral analysis to other characteristic behaviors found in tuberous sclerosis , namely autistic perseverative behavior , and to determine if these behaviors in TSC2+/− mice could be due to heightened mGluR5 signaling . We used the radial arm water maze ( RAWM ) followed by a reversal training protocol to analyze the behavioral phenotype of these mice . After WT and TSC2+/− mice that were administered MPEP or vehicle acquired the hidden platform ( Figure S1 ) , the platform was moved to test reversal learning . In the first and second reversal trials , TSC2+/− mice visited the target arm where the hidden platform had been previously placed in trials 1–30 significantly more frequently than WT mice ( p = 0 . 0064 ) . This preservative behavior was corrected in TSC2+/− mice injected with MPEP ( Figure 6a—Reversal Trial 2; main effect of group: F ( 1 , 21 ) = 1 . 98 , p = 0 . 1747 ) . By the third trial , all groups behaved the same . This suggests that mGluR5 contributes to the behavioral phenotype in TSC2+/− mice . Additional behavioral testing revealed no deficits in sensory , exploratory , or motor performance . There were no differences in the performance in the open pool task between any of the experimental groups ( Figure 6b; F ( 3 , 27 ) = 0 . 7313 , p>0 . 05 ) . Locomotor activity was unaffected by both genotype and treatment as measured in the Open Field task . There were no differences in anxiety and exploration between the experimental groups , as measured by the percentage of time spent in the center ( Figure 6b , inset; one way ANOVA F ( 3 , 28 ) = 0 . 47 , p>0 . 05 ) .
While the role of dysregulated mTORC1 signaling in the pathophysiology of TSC has been demonstrated previously [27] , [39]–[41] , our work implicates heightened mGluR5 and Erk signaling as a key component of the irregular plasticity and pathological phenotypes in a model of TSC . Consistent with findings by others , we find that juvenile TSC2+/− mice ( 21 d old ) have reduced mGluR-LTD compared to littermate wild-types [26] , [27] . However we show that adult TSC2+/− mice ( 2 mo ) have similar LTD magnitude to age-matched WT mice . This TSC2+/− adult mGluR-LTD is mTOR-independent and thus distinct from WT mGluR-LTD . We show that adult TSC2+/− mice have increased levels of hippocampal mGluR5 expression as well as overactivation of Mek-Erk signaling . Inhibition of mGluR5 signaling with MPEP blocked adult mGluR-LTD in TSC2+/− CA1 hippocampus ( Figure 3e ) . We illustrate , for the first time , that the TSC2+/− hippocampus displays an increased expression of epileptiform activity following prolonged group I mGluR activation , and that this bursting activity can be suppressed via mGluR5 inhibition with MPEP or inhibition of Mek-Erk signaling with U0126 ( Figure 5 ) . Finally , MPEP corrected a perseverative behavioral phenotype in TSC2+/− mice , which may be a correlate of an autistic-like behavioral aspect in TSC2+/− mice ( Figure 6 ) . These findings suggest that modulation of mGluR5 signaling can correct two major pathological aspects of TSC , namely epilepsy and cognitive dysfunction . Our work is the first to show a developmental change in mGluR-LTD in a mouse model of TSC . We find LTD magnitude increases in TSC2 mutants from 21 d to 2 mo of age . In contrast , the magnitude of LTD is invariant between juvenile and adult WT mice . Thus it appears that a developmental compensation occurs in mutants to restore a wild type-like LTD . Although mGluR-LTD magnitude is indistinguishable between WT and TSC2 mutant adult mice , we find that the adult LTD in TSC2+/− mice is mechanistically distinct from that of wild-type littermates: mutant adult LTD is rapamycin insensitive and independent of mTOR signaling . Rapamycin insensitivity is not due to a loss of mTOR signaling per se or loss of the rapamycin sensing protein FKBP12 because TSC2+/− slices still exhibit rapamycin-dependent loss of RAPTOR/mTOR binding ( Figure 2 ) and inhibition of 1XTheta Burst LTP ( Ehninger et al . [39] ) , suggesting rapamycin sensing is still intact . Loss of mTOR dependence in TSC2+/− renders LTD nonresponsive to cues , signaling cascades , and inputs that modulate plasticity via mTOR . AMPK is a modulator of mTOR signaling that couples metabolism to plasticity [30] . We have previously shown that AMPK modulates hippocampal LTP and others have demonstrated a role for AMPK in learning and memory through mTOR [42] . Here we show for the first time that AMPK negatively regulates mGluR-LTD in WT mice , suggesting that energy availability controls not just LTP and learning and memory but also LTD in WT mice . Consistent with TSC2+/− adult mGluR LTD being mTOR independent , we find that unlike in wild-type slices , mutant slices display an LTD that is insensitive to metformin and 2DG , well-characterized AMPK activators ( Figure 1 and Figure S2 ) . Thus a pathway that regulates plasticity via mTOR in wild-type mice is unable to control this type of plasticity in TSC2+/− mice . Immunity of mutant LTD to mTOR-dependent inputs may underlie some of the pathological phenotypes seen in TSC patients . The lack of mTOR dependence prompted us to assess whether mGluR-LTD in adult mutant mice still required de novo protein synthesis , as is the case for wild-type mice [28] . Our observed mutant LTD is clearly protein synthesis-dependent at 2 mo of age ( Figure 1 ) , whereas Auerbach et al . describe a protein synthesis-independent LTD [27] in these mice at 1 mo . Together , these findings suggest that TSC2 mutants transition from a protein synthesis independent to dependent mGluR-LTD as they age . Interestingly , we find that whereas adult WT mice display a rapamycin-sensitive mGluR-LTD in line with work of many others [18] , [28] , juvenile WT mice display a rapamycin-insensitive mGluR LTD ( unpublished data ) . Auerbach et al . observed a similar rapamycin-insensitive LTD in juvenile WT slices . Thus , there appears to be a developmental switch from a rapamycin insensitive to sensitive LTD and so reconciles the disparate findings between multiple groups regarding the role of mTOR in hippocampal mGluR LTD . This finding correlates with observations of protein synthesis-independent LTP in juvenile rats [43] , which becomes protein-synthesis-dependent in adulthood [44] . Compared to adult wild type , TSC2 mutant hippocampus shows constitutively high p-Erk and increased expression of mGluR5 that are necessary for adult LTD ( Figures 3 and 4 ) . Chevere-Torres et al . demonstrated that mGluR-LTD in ΔRG TSC2 mutant mice is also driven by aberrant Erk signaling [26] . Auerbach et al . saw no increase in Erk signaling in young TSC2+/− mice . Similarly , we find that there is no difference in Erk activity between mutant and WT hippocampi at 21 d of age ( an age analyzed by Auerbach et al . ) . Heightened Erk activity in mutant mice is only evident in adult hippocampus and appears to be due to failure of mutants to reduce p-Erk from juvenile levels ( Figure 3 ) . These findings would appear to reconcile differences in findings from multiple groups and highlights the importance of developmental stage in neuronal signaling . We hypothesize that heightened mGluR5 and Erk signaling bypasses mTOR signaling and so renders LTD insensitive to signals that converge on mTOR . Brief preincubation of MPEP , followed by washout , did not by itself inhibit mGluR-LTD magnitude in TSC2+/− hippocampus , but instead restored rapamycin sensitivity to mGluR-LTD ( Figure 3d ) . This suggests that the adult TSC2+/− hippocampus is capable of “wild-type”-like responses if signaling downstream of mGluR5 or attenuation of Erk signaling can be attenuated , and thus opens up a novel therapeutic avenue . The mechanisms driving up-regulation of mGluR5 are not known , and we did not detect a difference in mGluR5 transcript between WT and TSC2+/− hippocampus ( unpublished data ) . This suggests a posttranscriptional mechanism for mGluR5 up-regulation in TSC2+/− . We find that attenuation of Mek-Erk signaling down to WT levels recapitulates the effects of MPEP in restoring rapamycin sensitivity to mGluR-LTD , and does so in a dose-dependent fashion ( Figure 4 ) . Independently of the mTOR pathway , Erk can promote protein synthesis through phosphorylation of Mnk [45] , [46] as well as through signaling to p90 ribosomal S6 protein kinase ( RSK ) to increase S6 phosphorylation [47] . Reduction of these pathways could explain the effect of U0126 in restoring rapamycin sensitivity . We find that MPEP prevents DHPG from activating Erk signaling in TSC2+/− slices , whereas MPEP cannot prevent DHPG-mediated Erk activation in WT slices . Thus , mGluR5 is required for Erk activation by DHPG in mutant but not WT hippocampus ( Figure 3 ) . It should be noted that in the absence of DHPG , MPEP had no effect on p-Erk or p-S6 levels ( Figure 3h ) . MPEP is an mGluR5 inverse agonist and so is able to inhibit ligand-independent activation of the overexpressed receptor [48] , [49] . Therefore , we propose that the most parsimonious explanation would be that two distinct mechanisms are at play in the TSC2+/− hippocampus . One mechanism drives high basal Erk phosphorylation in mutants that is not dependent on the higher expression of mGluR5 . A second mechanism allows for Erk activation in the presence of DHPG that is mGluR5 dependent in TSC2+/− hippocampi but not in WT . So heightened mGluR5 levels in mutants are necessary for the LTD aberrations in adult mice because MPEP restores WT like LTD . Likewise , raised Erk activity is also necessary since UO126 restores WT-like plasticity . Finally , Erk activation by ligand requires mGluR5 in mutants but not WT , since this can be suppressed by MPEP . However , the raised basal Erk phosphorylation in mutants appears to be mGluR5 independent . We find that slices from adult TSC2+/− mice have longer epileptiform discharges induced by prolonged DHPG exposure ( Figure 5b ) . This TSC2+/− epileptiform activity is reduced by pre-incubation with MPEP , rapamycin , or U0126 . Interestingly , neither rapamycin nor MPEP were able to diminish ictal duration in wild-type slices , suggesting a preferential role for mGluR5-mTOR in maintaining synchronous firing duration in TSC2 mutant slices . MPEP and UO126 were able to reduce the propensity for mutant slices to display ictal burst as measured by the number of slices that showed bursting ( Figure 5d ) , whereas rapamycin did not . The mGluR5 positive allosteric modulator CDPPB had no effect on bursting propensity or duration in adult WT or TSC2 mutant mice . Nor did it influence burst duration or ratio of ictal to interictal events ( unpublished data ) . These observations underscore the complex nature of synchronous firing in the seizing hippocampus: mTOR is not necessary for the increased propensity for firing in TSC whereas mGluR5 and Erk signaling are , however mTOR , mGluR5 , and Erk are necessary for the increased duration of synchronous firing seen in mutants . It will be of great interest to see whether slices from juvenile mutant mice also manifest greater seizure-like activity and whether mGluR5 agonists reduce or enhance this activity given the findings of Auerbach et al . and the role of mGluR5 in younger mice [27] . Behavioral deficits and perseveration are often seen in TSC patients . In the radial arm watermaze , adult mutant mice acquired the target arm at the same rate as wild-type mouse . However TSC2+/− mice showed a preference for the conditioned arm upon moving the platform . This phenotype was eliminated with administration of MPEP . This result has similarities with the work of Ehninger et al . , who used the same TSC2+/− mice and found they displayed extended freezing after foot shock even in a novel context . Using juvenile mice , Auerbach et al . showed that learning deficits were eliminated with mGluR5 positive allosteric modulators . These findings underscore the need to study multiple behavioral phenotypes in juvenile and adult mice with both positive and negative regulators of mGluR5 . It is interesting to note that FXS , another condition associated with overactive mGluR5 function , shares many aspects of physiology and behavior with TSC . FMR1 knockout hippocampal slices that were disinhibited with bicuculline to induce synchronous discharges had more prolonged bursting activity and this phenotype was counteracted by MPEP [38] . Additional studies in FMR1 knockout hippocampus demonstrate that basal levels of mGluR5 are unchanged; however , Erk1 is hyperactivated in response to DHPG [50] . The Erk hyperactivation promotes overtranslation of mRNA transcripts and can be reduced via antagonism of mGluR5 or Erk signaling , yet is immune to mTORC1 inhibition with rapamycin [50] . It has been reported that FMR1 knockout mice exhibit rapamycin-insensitive and protein synthesis-independent mGluR-LTD [51] . We observed a similar rapamycin-insensitivity after DHPG treatment , though mGluR-LTD in TSC2+/− remains dependent upon protein synthesis ( Figure 1e ) . Though subtle differences exist , the similarities suggest that TSC and fragile X mental retardation share some common underlying mechanisms . Moreover , our results , along with the FMR1 studies mentioned , suggest a prominent and perhaps general role for mGluR5 signaling in diseases where dysregulated postsynaptic protein translation is implicated . The current study implicates heightened mGluR5 and Erk function in TSC pathology , thereby suggesting that available mGluR5 antagonists or Erk inhibitors may serve as therapeutic agents for treating people with TSC . The findings of Auerbach et al . suggest that mGluR5 agonists can restore appropriate LTD and behavioral phenotypes when administered to juvenile mice . In contrast we find that adult LTD , epileptiform activity , and behavioral deficits are repaired with mGluR5 antagonists . In agreement with our findings that Erk inhibition also restores appropriate LTD and suppresses epileptiform activity in TSC2 mutant slices , Chevere-Torres et al . describe normalization of LTD using U0126 . In aggregate , these findings suggest that there may be an age-dependent effect of mGluR5 antagonists and agonists in the potential treatment of TSC patients . In summary we show that modulation of mGluR5 and Erk signaling can restore appropriate signaling in a disease model originating from a congenital defect , which implies that symptomatic alleviation in human TSC is possible with drugs that target these pathways .
DHPG , MPEP , and anisomycin were purchased from Tocris Bioscience and were solublized in MilliQ water . 1 , 4-diamino-2 , 3-dicyano-1 , 4-bis[2-aminophenylthio]butadiene ( U0126 ) and rapamycin were purchased from Sigma-Aldrich and dissolved in DMSO . Metformin and adenine 9-β-D-arabinofuranoside ( ara-A ) were purchased from Sigma-Aldrich and dissolved in MilliQ water . Methods were previously described in detail [30] . All electrophysiology was performed on male 21-d-old or 2-mo-old TSC2+/− and wild-type littermate mice ( C57BL/6 background ) . Individual field EPSPs were recorded with a sampling rate of 100 kHz from CA1 stratum radiatum , with ACSF-filled recording electrodes ( 1 . 4–2 MΩ ) . Baseline synaptic transmission was assessed for each individual slice by applying gradually increasing stimuli ( 0 . 5–20 V , 25 nA–2 . 0 µA , A-M Systems model 2200 stimulus isolator , Carlsborg , WA ) to determine the input–output relationship . All subsequent experimental stimuli were set to an intensity that evoked 50% of maximum fEPSP slope . Methods were previously described [30] . Briefly , following drug application and/or stimulation , slices were flash frozen in eppendorf tubes on dry ice . Acutely harvested slices were flash frozen immediately after slicing . Following purification , protein extracts were loaded at 20–30 µg/lane in gradient ( 4–20% ) SDS-PAGE gels ( BioRad ) and resolved with standard electrophoresis in tris-glycine running buffer ( 100 mM Tris , 1 . 5 M glycine , 0 . 1% SDS ) and transferred at 4°C onto PVDF membranes and blocked in 5% milkfat TBST . All primary antibodies were applied overnight at 4°C and were obtained from Cell Signaling ( Danvers , MA ) , except for βIII tubulin , which was obtained from Promega ( Madison , WI ) . Membranes were the washed and incubated for 1 h in horseradish peroxidase-conjugated goat anti-rabbit IgG or goat anti-mouse IgG secondary antibodies ( 1∶10 , 000 ) ( Santa Cruz Biotech ) . Protein bands were detected using SuperSignal West Femto ECL reagent ( Pierce Biochem ) and visualized using a UVP ChemiDoc-it Imaging System with VisionWorks software , which was also used to quantify protein bands . Hippocampal tissue was homogenized in ice-cold CHAPS lysis buffer ( in mM ) ( 150 NaCl , 40 HEPES , 2 EDTA , 10 pyrophosphate , 10 glycerophosphate , 4 orthovanadate , 0 . 3% CHAPS ) . Following quantification , equal amounts of cell extract were used for immunoprecipitation with 0 . 5 µg anti-mTOR antibody . For sham , an antibody ( 0 . 5 µg ) specific to the unrelated protein LIN28b ( Cell Signaling ) was used . Samples were incubated on a rotator at 4°C for 2 h . We used 20 µg of whole cell extract for quantitative comparisons . We added 20 µg of washed Sepharose G beads to each sample and spun on the rotator for an additional hour at 4°C . Samples were spun down briefly , washed , and combined with SDS gel loading buffer . The protocol has been described in detail [52] . Briefly , the RAWM consisted of a 2-d training protocol with 15 trials per day . Animals were injected intraperitoneally with MPEP or PBS at 30 µg/g body weight 30 min prior to training . On day 1 , the animals were trained in the visible platform task first ( Trials 1–9 ) , then trained on the hidden platform version of the maze ( Trials 10–15 ) . All trials on day 2 utilized the submerged/hidden platform ( Trials 16–30 ) . The number of errors ( arm entries that did not result in finding the platform ) was recorded . Data were collected with VideoTrack v2 . 5 ( ViewPoint Life Sciences Inc . , Montreal , Canada ) . For electrophysiological experiments , two-way ANOVA with repeated measures ( mixed model ) and Bonferroni posttests were used for statistical analysis . For Western blot analysis with two sets of data , two-tailed Student t tests were used . Western blot analysis where multiple groups were acquired and analyzed together and one-way ANOVA with Tukey-Krameŕ posttest correction for multiple analyses were used to address significant differences between groups . Chi-square test for trend was used to analyze the contingency data obtained from the epileptiform bursting experiments . For all tests , p<0 . 05 was considered statistically significant . For behavior , two-way repeated-measures ANOVA with three-trial bins as the repeated measure was used to compare the time course for errors in RAWM . In examining individual time points , one-way ANOVA was used . Data were analyzed using Prism 5 ( Graphpad Software Inc . , La Jolla , CA ) and all data are expressed as means ± SEM .
|
Tuberous sclerosis complex ( TSC ) is a genetic disorder that afflicts around 1 in 6 , 000 people and results from a mutation in one of two genes , TSC1 or TSC2 . TSC patients suffer a number of neuronal symptoms including various degrees of autism , mental retardation , and epilepsy , the latter found in more than 80% of cases within the first year of life . In the TSC mutant mice that are used to model the disease , a region of the brain called the hippocampus fails to undergo long-term depression ( LTD ) , a neuronal process that is important for learning and memory . We find that while this is the case in juvenile mutant mice , adult mice appear to have fixed this deficit . The “fix” involves the ramping up of signaling pathways involving mGluR5 and Erk . Although increased mGluR5 and Erk signaling outwardly fixes the problem of diminished LTD in adulthood , it renders the brain insensitive to the cues and inputs that normally work to control LTD . Moreover , the hippocampus in adult TSC mice is prone to seizures and impaired in learning and memory tasks . We find that drugs that target mGluR5 or Erk signaling repair the problems with excitability and learning deficits .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"medicine",
"developmental",
"biology",
"developmental",
"neuroscience",
"synaptic",
"plasticity",
"molecular",
"neuroscience",
"learning",
"and",
"memory",
"neurobiology",
"of",
"disease",
"and",
"regeneration",
"epilepsy",
"synapses",
"signaling",
"molecular",
"development",
"neurology",
"signaling",
"pathways",
"developmental",
"and",
"pediatric",
"neurology",
"biology",
"neuroscience",
"neurophysiology"
] |
2013
|
Reduced Juvenile Long-Term Depression in Tuberous Sclerosis Complex Is Mitigated in Adults by Compensatory Recruitment of mGluR5 and Erk Signaling
|
In 2015 , the mosquito Aedes albopictus was detected in Rabat , Morocco . This invasive species can be involved in the transmission of more than 25 arboviruses . It is known that each combination of mosquito population and virus genotype leads to a specific interaction that can shape the outcome of infection . Testing the vector competence of local mosquitoes is therefore a prerequisite to assess the risks of emergence . A field-collected strain of Ae . albopictus from Morocco was experimentally infected with dengue ( DENV ) , chikungunya ( CHIKV ) , zika ( ZIKV ) and yellow fever ( YFV ) viruses . We found that this species can highly transmit CHIKV and to a lesser extent , DENV , ZIKV and YFV . Viruses can be detected in mosquito saliva at day 3 ( CHIKV ) , day 14 ( DENV and YFV ) , and day 21 ( ZIKV ) post-infection . These results suggest that the local transmission of these four arboviruses by Ae . albopictus newly introduced in Morocco is a likely scenario . Trial registration: ClinicalTrials . gov APAFIS#6573-201606l412077987v2 .
Over the past decades , arboviruses caused acute emergences leading to global pandemics . Dengue viruses ( DENV; family Flaviviridae , genus Flavivirus ) are responsible for 390 million infections per year including 96 million symptomatic cases [1] . In 2005 , chikungunya virus ( CHIKV; family Togaviridae , genus Alphavirus ) emerged outside Africa producing devastated outbreaks in all continents [2] . While its importance was underestimated , zika virus ( ZIKV; family Flaviviridae , genus Flavivirus ) hit Brazil in 2015 causing several million cases in the Americas [3] and severe unusual symptoms such as Guillain-Barré syndrome and congenital microcephaly . Despite the availability of an efficient vaccine 17D , yellow fever virus ( YFV; family Flaviviridae , genus Flavivirus ) continues to cause human fatalities in South America and Sub-Saharan Africa . All four arboviruses share the same mosquito vectors: Aedes aegypti and Aedes albopictus . Ae . aegypti is an urban mosquito feeding exclusively on humans [4] and Ae . albopictus colonizes a larger range of sites and feeds on both animals and humans [5] . While Ae . aegypti took several centuries to invade most countries in the world [6] , Ae . albopictus took only a few decades to establish stable colonies worldwide [7] . Native to Southeast Asia , Ae . albopictus has invaded America , Africa and Europe during the last 40 years [8] . In Europe , it was introduced in 1979 in Albania and then in Italy in 1990 . It is now present in 20 European countries [9] . In Africa , Ae . albopictus was first reported in the early 1990s in South Africa [10] and Nigeria [11] . Thereafter , it was described in several West and Central African countries: Cameroon in 2000 [12] , Equatorial Guinea in 2003 [13] , Gabon in 2007 [14] , Central African Republic in 2009 [15] , and Republic of Congo in 2011 [16] . More recently , it was detected in Mali [17] , Mozambique [18] and São Tomé and Príncipe [19] . In North Africa , Ae . albopictus was detected in Algeria in 2010 [20] then in Morocco in 2015 [21] . Morocco is considered a low prevalent country for mosquito-borne diseases [22] . However , since 1996 , the country has faced West Nile virus ( WNV ) with three epizootic episodes: 1996 , 2003 and 2010 [23 , 24] . In 2008 , a serosurvey of wild birds confirmed the circulation of WNV in native birds [25] . Other arboviruses like Usutu virus and Rift valley fever virus ( RVFV ) have never been reported despite serological evidence of RVFV antibodies in camels at the border between Morocco and Mauritania [25–27] . Morocco is considered by several reports of the Intergovernmental Panel on Climate Change ( IPCC ) as a hotspot for climate change with its significant impact for several infectious diseases [28] . The introduction of an invasive species such as Ae . albopictus will likely cause a new public health problem . Moreover , Morocco is a tourist destination with more than 11 million visitors reported in 2017 {http://www . tourisme . gov . ma/fr/tourisme-en-chiffres/chiffres-cles} , increasing the risk of importing arboviral pathogens . In this work , we evaluate the ability of Ae . albopictus recently introduced in Morocco to transmit CHIKV , DENV , ZIKV and YFV , where the outcome of vector infection depends on specific genotype-by-genotype ( G x G ) interactions between a vector population and a pathogen lineage [29] . This measure of the vector competence of field-collected mosquitoes helps to assess the risk of arbovirus emergence .
Animals were housed in the Institut Pasteur animal facilities accredited by the French Ministry of Agriculture for performing experiments on live rodents . Work on animals was performed in compliance with French and European regulations on care and protection of laboratory animals ( EC Directive 2010/63 , French Law 2013–118 , February 6th , 2013 ) . All experiments were approved by the Ethics Committee #89 and registered under the reference APAFIS#6573-201606l412077987 v2 . During the national surveillance plan implemented in 2016 to establish the geographical distribution of Ae . albopictus in Morocco , five ovitraps less than 500 m apart were placed on a street of the Agdal neighborhood in Rabat ( 33°59'20 . 9′′ N , 6°51′07 . 9′′W ) . Ovitraps were checked for eggs once a week from May to November 2016 and were brought back to the laboratory to be stored in humid chambers ( relative humidity of 80% ) before being sent to Institut Pasteur in Paris to perform the vector competence studies . After hatching , larvae were split into pans of 200 individuals and supplied every 2 days with a yeast tablet dissolved in 1L of dechlorinated tap water . All immature stages were reared at 26±1°C . Emerging adults were maintained at 28±1°C with a 16L:8D cycle , 80% relative humidity and supplied with a 10% sucrose solution . Females were fed twice a week on anaesthetized mice ( OF1 mice , Charles River laboratories , France ) . Resulting F2 adults were used for vector competence assays . It should be noted that variations of oral susceptibility to an arbovirus can be considered negligible in fewer than five laboratory generations [30] . CHIKV strain ( 06 . 21 ) was isolated from a patient on La Reunion Island in 2005 [31] . After isolation on Ae . albopictus C6/36 cells , this strain was passaged twice on C6/36 cells and the viral stocks produced were stored at -80°C prior to their use for mosquito oral infections . DENV-2 strain provided by Prof . Leon Rosen , was isolated from a human serum collected in Bangkok ( Thailand ) in 1974 [32] and had been passed only in different mosquito species ( 2 times in Ae . albopictus , 2 times in Toxorhynchites amboinensis , and one time in Ae . aegypti ) by intrathoracic inoculation . Viral stocks were obtained by inoculating C6/36 cells . ZIKV strain ( NC-2014-5132 ) originally isolated from a patient in April 2014 in New Caledonia was passaged five times on Vero cells; this strain belongs to the same genotype than the ZIKV strains circulating in Brazil in 2015 [33] . Lastly , a YFV strain ( S79 ) belonging to the West African lineage , was isolated from a human case in Senegal in 1979 [34] . YFV-S79 was passaged twice on newborn mice and two times on C6/36 cells . Six to eight batches of 60 7–10 day old females were exposed to an infectious blood meal containing 1 . 4 mL of washed rabbit erythrocytes and 700 μL of viral suspension . The blood meal was supplemented with ATP as a phagostimulant at a final concentration of 1 mM and provided to mosquitoes at a titer of 107 . 2 plaque-forming unit ( pfu ) /mL for ZIKV , 106 . 5 focus-forming unit ( ffu ) /mL for YFV and 107 ffu/mL for CHIKV and DENV , using a Hemotek membrane feeding system . Mosquitoes were allowed to feed for 15 min through a piece of pork intestine covering the base of a Hemotek feeder maintained at 37°C . Fully engorged females were transferred in cardboard containers and maintained with 10% sucrose under controlled conditions ( 28±1°C , relative humidity of 80% , light:dark cycle of 16 h:8 h ) for up to 21 days with mosquito analysis at 3 , 7 , 14 and 21 days post-infection ( dpi ) . For each virus , 21–30 mosquitoes were examined at each dpi . For each mosquito examined , body ( abdomen and thorax ) and head were tested respectively for infection and dissemination rates at 3 , 7 , 14 and 21 dpi . For this , each part was ground in 250 μL of Leibovitz L15 medium ( Invitrogen , CA , USA ) supplemented with 3% FBS , and centrifuged at 10 , 000×g for 5 min at +4°C . The supernatant was processed for viral titration . Mosquitoes examined previously were also tested for viral transmission by collecting saliva using the forced salivation technique [35] . Mosquitoes were anesthetized on ice and legs and wings were removed . The proboscis was then inserted into a pipette tip containing 5 μL of fetal bovine serum ( FBS ) . After 30 min , the tip content was transferred in 45 μL of L15 medium . Saliva was then titrated to estimate the transmission rate . CHIKV , DENV and YFV were titrated by focus fluorescent assay and ZIKV by plaque forming assay as ZIKV cannot produce distinct viral foci on mosquito cells . For mosquitoes challenged with CHIKV , DENV or YFV , saliva , head and body homogenates were titrated by focus fluorescent assay on Ae . albopictus C6/36 cells [36] . Samples were serially diluted and inoculated onto C6/36 cells in 96-well plates . After an incubation of 3 days for CHIKV , and 5 days for YFV and DENV-2 at 28°C , cells were stained using hyper-immune ascetic fluid specific to each virus as the primary antibody ( CHIKV: provided by the French National Reference Center for Arbovirus at the Institut Pasteur , YFV: OG5 NB100-64510; Novusbio , CO , USA , and DENV: Ms X Dengue complex MAB 8705 , Millipore , MA , USA ) and Alexa Fluor 488 goat anti-mouse IgG ( Life Technologies , CA , USA ) as the secondary antibody . Saliva titers were expressed as ffu/saliva . For ZIKV , body and head suspensions were serially diluted and inoculated onto monolayers of Vero cells in 96-well plates . Cells were incubated for 7 days at 37°C then stained with a solution of crystal violet ( 0 . 2% in 10% formaldehyde and 20% ethanol ) . Presence of viral particles was assessed by CPE detection . Saliva was titrated on monolayers of Vero cells in 6-well plates incubated 7 days under an agarose overlay . Saliva titers were expressed as pfu/saliva . Means , standard deviations , 95% confidence interval were calculated and statistical analyses were performed using the Stata software ( StataCorp LP , Texas , and USA ) . The effect of virus and dpi on infection , dissemination and transmission rates was evaluated using Fisher’s exact test . The titer of viral particles in mosquito saliva was compared across groups using a Kruskall-Wallis non parametric test . P-values<0 . 05 were considered statistically significant . Heatmaps were built under R ( v 3 . 3 . 1 ) ( https://www . R-project . org ) .
Mosquito females were exposed to four separate infectious blood meals containing CHIKV , DENV , ZIKV or YFV . The first step after the ingestion of the infectious blood meal is the infection of the midgut which is appraised by calculating the infection rate ( IR ) corresponding to the proportion of mosquitoes with an infected midgut . At 3 dpi , Ae . albopictus Morocco were more infected with CHIKV ( Fig 1; Fisher’s exact test: p<10−4 , df = 3 ) with an IR reaching 93% ( N = 30 ) whereas with the 3 other viruses , IRs were lower than 20% ( N = 30 ) . At 7 dpi , the IR with CHIKV reached 100% ( N = 30 ) and remained significantly lower with DENV ( 60%; N = 30 ) , ZIKV ( 60%; N = 30 ) and YFV ( 26 . 7; N = 30 ) ( Fisher’s exact test: p<10−4 , df = 3 ) . At 14 dpi , mosquitoes become more infected with DENV reaching 90% ( N = 30 ) close to CHIKV ( 86 . 7% , N = 30 ) ( Fisher’s exact test: p = 0 . 69 , df = 3 ) but significantly higher than with ZIKV ( 66 . 7% , N = 30 ) , and YFV ( 20% , N = 30 ) ( Fisher’s exact test: p<10−4 , df = 30 ) . At 21 dpi , the same pattern was observed: IRs were higher with CHIKV ( 90% , N = 30 ) and DENV ( 100% , N = 21 ) than with ZIKV ( 69 . 6% , N = 23 ) and YFV ( 53 . 3% , N = 30 ) ( Fisher’s exact test: p<10−4 , df = 3 ) . IRs with all viruses increased along with dpi except with CHIKV which remained high ( >86% ) very early from 3 dpi . The lowest IRs were obtained with YFV fluctuating from 6 . 7% at 3 dpi to 53 . 3% at 21 dpi . Once the midgut is infected , viral particles can disseminate from the midgut to internal organs and tissues . The dissemination rate ( DR ) gives the number of mosquitoes with infected heads among mosquitoes with infected midgut . At 3 dpi , only CHIKV was detected in mosquito heads ( Fig 2; 28 . 6% , N = 28 ) . At 7 dpi , DR with CHIKV reached 53 . 3% ( N = 30 ) and only 5 . 5% ( N = 18 ) with DENV ( Fisher’s exact test: p<10−4 , df = 3 ) . At 14 dpi , DRs with CHIKV ( 65 . 4% , N = 26 ) and DENV ( 59 . 2% , N = 27 ) were higher and similar ( Fisher’s exact test: p = 0 . 65 , df = 1 ) compared to YFV ( 33 . 3% , N = 6 ) and ZIKV ( 25% , N = 20 ) which were both lower and comparable ( Fisher’s exact test: p = 0 . 69 , df = 1 ) . At 21 dpi , DRs for each virus were significantly different ( Fisher’s exact test: p<10−4 , df = 3 ) and slightly higher than the DRs at 14 dpi . Viral dissemination started earlier with CHIKV at 3 dpi while it was only at 7 dpi with DENV and 14 dpi with YFV and ZIKV . The lowest DRs were obtained with ZIKV maintained at 25% at 14 and 21 dpi . After the virus has spread into the general cavity of the mosquito and infected the salivary glands , the virus must be excreted in saliva for subsequent transmission . The transmission rate ( TR ) is defined as the proportion of mosquitoes delivering infectious saliva among mosquitoes having disseminated the virus ( Fig 3A ) . At 3 and 7 dpi , viral particles could be detected in saliva of mosquitoes infected with CHIKV , with TRs of 37 . 5% ( N = 8 ) and 68 . 7% ( N = 16 ) respectively . At 14 dpi , TR with YFV ( 50% , N = 2 ) predominated over TRs with CHIKV ( 35 . 3% , N = 17 ) and DENV ( 11 . 1% , N = 18 ) , TR with ZIKV remaining at 0%; no significant difference was observed among all TRs ( Fisher’s exact test: p = 0 . 14 , df = 3 ) . At 21 dpi , transmission with ZIKV became detectable with a TR of 50% ( N = 4 ) , not significantly different from TRs with DENV ( 26 . 3% , N = 19 ) , CHIKV ( 17 . 4% , N = 23 ) , and YFV ( 10% , N = 10 ) ( Fisher’s exact test: p = 0 . 36 , df = 3 ) . Transmission started early at 3 dpi with CHIKV , at 14 dpi with DENV and YFV , and at 21 dpi with ZIKV with respectively , a mean of 2 . 06±0 . 60 Log10 ffu/saliva ( N = 3 ) , 0 . 87±0 . 38 Log10 ffu/saliva ( N = 2 ) , 1 . 53 Log10 ffu/saliva ( N = 1 ) , and 2 . 71±0 . 01 Log10 pfu/saliva ( N = 2 ) ( Fig 3B ) . No significant difference was detected between all viruses at 14 dpi ( Kruskal-Wallis test: p = 0 . 47 , df = 2 ) and 21 dpi ( Kruskal-Wallis test: p = 0 . 10 , df = 3 ) . The highest number of viral particles was detected in saliva of mosquitoes infected with YFV and examined at 21 dpi: TR of 50% ( 2 among 4 mosquitoes with viral dissemination ) , 2 females delivering 2 . 70 Log10 pfu ( 500 ) and 2 . 72 Log10 pfu ( 530 ) infectious particles . Whereas IR , DR and TR measure the efficiency of the midgut and salivary glands barriers to modulate , respectively , viral dissemination and transmission , the transmission efficiency ( TE ) gives an overview of transmission potential of mosquitoes tested; it corresponds to the proportion of mosquitoes with infectious saliva among all mosquitoes examined ( presenting or not a viral dissemination with infected heads ) . Fig 4 shows that , the highest TE was detected at 7 dpi with CHIKV , at 21 dpi with DENV , at 14/21 dpi with YFV , and at 21 dpi with ZIKV . Collectively , Ae . albopictus Morocco were more susceptible to CHIKV and secondarily , to DENV , ZIKV and YFV . To summarize the vector competence corresponding to the overall ability of a mosquito population to be infected , to ensure the viral dissemination and to transmit the virus , heatmaps were built ( Fig 5 ) . Ae . albopictus Morocco were better infected with CHIKV from 3 dpi than with DENV and ZIKV ( Fig 5A ) . Mosquitoes ensured an early dissemination ( Fig 5B ) and transmission ( Fig 5C ) with CHIKV ( from 3 dpi ) than with DENV and ZIKV . The species was less susceptible to YFV . Altogether , vector competence of Ae . albopictus Morocco depends on the virus and the dpi: it is more susceptible to CHIKV and susceptibility increases along with the dpi .
Using experimental infections , we show that the recently-introduced Ae . albopictus in Morocco were susceptible to all four viruses tested , CHIKV , DENV , YFV and ZIKV . Viral transmission was detected at 3 dpi with CHIKV , 14 dpi with DENV and YFV , and only 21 dpi with ZIKV . Even if DENV , YFV and ZIKV belong to the same genus , they behave differently in Ae . albopictus mosquitoes . Infection of the midgut increases gradually from 3 dpi: DENV infects more efficiently mosquitoes than YFV and ZIKV , YFV remaining the less successful . Dissemination of DENV from the midgut to the mosquito general cavity started at 7 dpi as observed with most populations of Ae . albopictus [37]; it takes a shorter time with Ae . aegypti , i . e . from 5 dpi [38] . DENV dissemination is more strongly inhibited at early dpi than later meaning that the role of midgut as a barrier is diminished with dpi . Transmission of DENV was observed from 14 dpi suggesting an intrinsic incubation period higher than 7 dpi , likely around 10 dpi [37] . With ZIKV and YFV , dissemination was observed only at 14 dpi , YFV spreading at a higher rate than ZIKV suggestive of a stronger role of the midgut barrier with YFV . Transmission was detected at 14 dpi with YFV as observed with other Ae . albopictus populations [39] and 21 days with ZIKV which is longer than expected [40] . CHIKV presents a different profile . This alphavirus infects , disseminates and is transmitted more intensively and more quickly than the three other viruses . This viral strain presents an amino acid substitution ( A226V ) in the envelope glycoprotein E1 [31] favoring the viral transmission by Ae . albopictus [41 , 42] . Importantly , exposure of infected mosquitoes to lower temperatures ( lower than 25°C ) compatible to values recorded in Morocco can modulate transmission [37] . It has been demonstrated that Ae . albopictus were able to better transmit CHIKV at a temperature lower than 28°C [43] . These assessments of vector competence of Ae . albopictus from Morocco to CHIKV , DENV , ZIKV and YFV are important for appraising the risk of local transmission . ZIKV shows the longer extrinsic incubation period ( EIP ) which refers to the time between the uptake of the virus during the blood feeding and the delivery of the virus by vector bite after successful infection and dissemination in the mosquito . If the EIP is longer than the daily survival rate of the mosquito , the risk of transmission is low . By shortening mosquito lifespan , vector control measures reduce disease transmission [44] . However , other factors such as environmental factors , e . g . the temperature , may influence the vector competence [43] . The vector competence and the EIP both contribute to estimating the vector capacity which describes the basic reproductive rate of a pathogen by a vector [44] . A high abundance of the vector [45] , increased contacts between the vector and humans ( i . e . anthropophily of mosquitoes ) [5] and a high proportion of immunologically naïve humans , are also factors that should be considered in estimating the risk of emergence . Introductions of viremic travelers from endemic countries for all these viruses may initiate local transmission and outbreaks . Therefore surveillance of travelers must be reinforced .
|
The Asian tiger mosquito Aedes albopictus is responsible for the transmission of several arboviruses such as dengue and chikungunya viruses . In 30 to 40 years , it has extended its geographical distribution in both tropical and temperate regions of all continents . The species was first detected in September 2015 , in Rabat , Morocco . Using experimental infections , we demonstrated that Ae . albopictus Morocco are competent to transmit zika and yellow fever viruses in addition to the transmission of dengue and chikungunya viruses . Our results are central to suggest developing the most effective national surveillance program and to designing the most suitable control strategy to avoid the mosquito spreading beyond its point of entry in Morocco .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"invertebrates",
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"animals",
"alphaviruses",
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"neglected",
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"insect",
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"africa",
"infectious",
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"insects",
"arthropoda",
"people",
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"places",
"mosquitoes",
"eukaryota",
"anatomy",
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] |
2019
|
Potential of Aedes albopictus to cause the emergence of arboviruses in Morocco
|
The ongoing conflict between viruses and their hosts can drive the co-evolution between host immune genes and viral suppressors of immunity . It has been suggested that an evolutionary ‘arms race’ may occur between rapidly evolving components of the antiviral RNAi pathway of Drosophila and viral genes that antagonize it . We have recently shown that viral protein 1 ( VP1 ) of Drosophila melanogaster Nora virus ( DmelNV ) suppresses Argonaute-2 ( AGO2 ) -mediated target RNA cleavage ( slicer activity ) to antagonize antiviral RNAi . Here we show that viral AGO2 antagonists of divergent Nora-like viruses can have host specific activities . We have identified novel Nora-like viruses in wild-caught populations of D . immigrans ( DimmNV ) and D . subobscura ( DsubNV ) that are 36% and 26% divergent from DmelNV at the amino acid level . We show that DimmNV and DsubNV VP1 are unable to suppress RNAi in D . melanogaster S2 cells , whereas DmelNV VP1 potently suppresses RNAi in this host species . Moreover , we show that the RNAi suppressor activity of DimmNV VP1 is restricted to its natural host species , D . immigrans . Specifically , we find that DimmNV VP1 interacts with D . immigrans AGO2 , but not with D . melanogaster AGO2 , and that it suppresses slicer activity in embryo lysates from D . immigrans , but not in lysates from D . melanogaster . This species-specific interaction is reflected in the ability of DimmNV VP1 to enhance RNA production by a recombinant Sindbis virus in a host-specific manner . Our results emphasize the importance of analyzing viral RNAi suppressor activity in the relevant host species . We suggest that rapid co-evolution between RNA viruses and their hosts may result in host species-specific activities of RNAi suppressor proteins , and therefore that viral RNAi suppressors could be host-specificity factors .
As obligate intracellular parasites , viruses modulate and exploit the host cellular environment for their replication . The host antiviral defense system restricts virus infections , and in turn , viruses dedicate a significant fraction of their coding capacity to produce factors that antagonize the antiviral immune response [1] , [2] . Co-evolution of virus and host may therefore lead to a host-specific adaptation of viral counter-defense to the host antiviral defense system , which can contribute to host specificity of the virus [3] . The RNA interference ( RNAi ) pathway is a major antiviral defense system in plants , arthropods , nematodes and fungi [4]–[7] and has recently been suggested to control virus infection in mammals [8] , [9] . Double stranded RNA ( dsRNA ) , which is typically produced during virus infection but absent from non-infected cells [10] , triggers the RNAi pathway . In insects , cleavage of viral dsRNA by the ribonuclease Dicer-2 ( Dcr-2 ) generates viral small interfering RNAs ( vsiRNAs ) [11]–[23] . Dcr-2 and its binding partner R2D2 bind these vsiRNAs and load the small RNA duplexes into an Argonaute-2 ( AGO2 ) containing RNA induced silencing complex ( RISC ) [24] . One strand of the vsiRNA is retained and guides the recognition and cleavage of complementary viral RNAs by AGO2 [11] , [25]–[28] . In response , insect and plant viruses encode suppressors of RNAi ( VSRs ) to counteract the antiviral RNAi pathway [29] . Different mechanisms for RNAi suppression have been identified; for example , some VSRs bind long dsRNA and/or siRNAs to shield them from Dicer cleavage or prevent their loading into Argonaute [11] , [30]–[38] . Other suppressors interact with Argonaute proteins to inhibit their activity or induce their degradation [14] , [39]–[45] . The ongoing arms race with viruses can impose a strong selective pressure on immune genes of the host [46] . Consistent with this , Dcr-2 , R2D2 , and AGO2 belong to the 3% fastest evolving genes in D . melanogaster and D . simulans and show very high rates of adaptive amino acid substitution with evidence for recent selective sweeps in multiple Drosophila species [47]–[49] . It has been hypothesized that this rapid adaptive evolution may be driven by antagonistic co-evolution with viral suppressors of RNAi [50] , as the RNAi pathway continues to evolve new ways to escape viral antagonists , leading to counter-adaptations by viruses that require further adaptations in the RNAi pathway of the host . A potential outcome of this antagonistic co-evolution is that viral RNAi suppressors become specialized to suppress RNAi in their host species , while losing this activity in non-host species . This may be unlikely for viral antagonists that bind dsRNA , which often efficiently suppress RNAi in both host and non-host species , and in some cases even across kingdoms [51]–[55] . However , when viruses antagonize protein components of the RNAi pathway , there is ample opportunity for co-evolution and the evolution of host-specificity . Nora virus of Drosophila melanogaster ( DmelNV ) is a recently identified natural fruit fly pathogen , which contains a single-stranded positive-sense RNA genome and appears to fall within the order of Picornavirales [56] . In contrast to other picorna-like viruses , DmelNV encodes four open reading frames: ORF 2 encodes replication proteins with clear homology to other Picornavirales members , ORF 4 encodes capsid proteins [57] ( Figure 1A ) . No homology exists between the protein products of ORF1 or ORF3 and proteins of other viruses . DmelNV causes persistent infections in laboratory stocks as well as in wild caught flies . Persistent infections are thought to reflect a dynamic equilibrium between host defense responses and viral counter-defense mechanisms [58] . The widespread abundance and persistent nature of DmelNV infections may suggest an equilibrium between antiviral RNAi and viral counter-defense , in which replication is restrained , but the infection is not cleared . Consistent with this , we recently showed that DmelNV is a target and a suppressor of the antiviral RNAi pathway [14] . We identified viral protein 1 ( VP1 ) , the product of open reading frame 1 , as an RNAi suppressor that counteracts AGO2 mediated target RNA cleavage ( slicer activity ) . Here we present two novel Nora-like viruses identified by metagenomic sequencing of wild populations of D . immigrans ( DimmNV ) and D . subobscura ( DsubNV ) , and we use these viral genomes to study RNAi antagonism from an evolutionary perspective . We find that the RNAi suppressor activity of DimmNV VP1 appears to be restricted to its natural host species , whereas DmelNV VP1 does not display any evidence of host specificity . We conclude that co-evolution between Nora viruses and their Drosophila hosts can result in host species-specific antagonism of AGO2 , and therefore that viral suppressors of RNAi are candidate host specificity determinants .
RNAi genes evolve rapidly and adaptively in multiple species of Drosophila [47] , [48] . We therefore hypothesized that the interaction between RNAi proteins and viral suppressors of RNAi may also evolve rapidly when viruses adapt to different hosts . In particular , optimization of such interactions in a specific host species may come at the cost of losing the interaction in non-host species . To test these hypotheses , we set out to identify novel Nora-like viruses from divergent Drosophila species . During an exploratory RT-PCR survey of Nora virus prevalence in wild Drosophila , we identified two novel Nora-like viruses in wild populations of D . immigrans ( DimmNV ) and D . subobscura ( DsubNV ) . Following this observation , we took a metagenomic RNA-sequencing approach to recover near-complete viral genomes for both viruses from population samples of D . immigrans and D . subobscura collected in the United Kingdom . The viral sequences were 12 , 265 nt and 12 , 276 nt , respectively ( compare to 12 , 333 nt for DmelNV ) and include all protein coding regions , a conserved CCTGGGSGGGGGTTA motif in their 5′ untranslated region , and a 3′ poly-A tract ( Figure S1A ) . These novel viruses are more closely related to the Nora virus originally identified in D . melanogaster ( DmelNV ) [56] than they are to the Nora-like virus recently described in the horn fly Haematobia irritans [59] , two Nora-like viruses identifiable in the transcriptomes of the lacewing Chrysopa pallens and the moth Spodoptera exigua , or the more distantly related Nora-like virus described in the wasp Nasonia vitripennis [60] ( Figure 1B ) . Overall , DmelNV is more divergent from DimmNV than it is from DsubNV ( 65% vs . 71% overall nucleotide identity , respectively ) , but phylogenetic analysis based on the coat protein ( VP4 ) suggests that DmelNV and DimmNV may be each other's closest relatives . The low genome-wide nonsynonymous to synonymous substitution ratio ( dN/dS = 0 . 076 , SE = 0 . 003 ) estimated by PAML [61] indicates that evolution of the protein sequence is highly constrained . However , divergence between the three viruses is too high to reliably estimate dS [62] , [63] and the estimated dN/dS may represent an upper limit . Amino-acid divergence between the viruses varies substantially between genes ( Figure 1C ) . For example , amino-acid identity between DimmNV and DmelNV varies from 82% for VP4 ( capsid ) to only 43% for VP3 ( unknown function ) , with VP1 showing an intermediate level of conservation ( 51% amino acid identity ) . A sliding-window analysis of nonsynonymous divergence shows that DimmNV is much more divergent from DmelNV and DsubNV in VP1 and VP2 , but that the three viruses are equidistant from each other in VP3 and VP4 . This may be a result of host-mediated selection , perhaps reflecting the closer relationship between D . melanogaster and D . subobscura , or it may be a result of recombination in the history of these three viruses . To test whether the interaction between antiviral RNAi components and viral RNAi antagonists is host specific , we first analyzed whether the DimmNV and DsubNV VP1 proteins are able to suppress RNAi in the S2 cell line from D . melanogaster . To this end , we cloned the full-length ( FL ) VP1 sequences and N- and C-terminal deletion mutants thereof ( ΔN and ΔC ) as N-terminal fusions to the V5 epitope in an insect expression plasmid ( Figure S1B ) . We verified expression of the DimmNV VP1 constructs by western blot after transfection in Drosophila S2 cells ( Figure 2A ) . With the exception of the DimmNV VP1ΔN362 , all DimmNV VP1 constructs were expressed at least at the level of DmelNV VP1FL that efficiently suppresses RNAi in reporter assays in S2 cells [14] . We then analyzed the ability of the DimmNV VP1 constructs to suppress RNAi in reporter assays . We transfected S2 cells with firefly and Renilla luciferase ( Fluc and Rluc ) reporter plasmids along with VP1 expression plasmids , and induced silencing of the Fluc reporter by soaking the cells in Fluc specific dsRNA . As reported earlier [14] , all DmelNV VP1 constructs , except DmelNV VP1ΔC74 , suppressed RNAi-mediated silencing of the Fluc reporter . In contrast , none of the DimmNV VP1 constructs efficiently suppressed silencing of the reporter ( Figure 2B ) . To confirm these results , we used an RNAi sensor assay that is independent of dsRNA uptake by S2 cells . In this sensor assay , the Rluc reporter is silenced by expression of an inverted repeat that folds into an Rluc-specific RNA hairpin . In line with the previous RNAi sensor assay , DimmNV VP1 did not suppress hairpin-induced silencing of the Rluc reporter in D . melanogaster S2 cells , whereas DmelNV VP1 efficiently suppressed RNAi ( Figure 2C ) . In addition , we tested if the VP1 constructs can suppress RNAi in a sensor assay in which silencing is induced by co-transfection of siRNAs . Also in this assay , DimmNV VP1 was unable to suppress silencing of the Fluc reporter , whereas DmelNV VP1 efficiently suppressed RNAi-based silencing ( Figure S2 ) . Similarly , the DsubNV VP1 constructs were unable to suppress long dsRNA or siRNA induced RNAi in D . melanogaster derived S2 cells ( Figure S2A–C ) . Moreover , recombinant DmelNV VP1 efficiently suppressed AGO2 slicer activity in embryo lysates of D . melanogaster , whereas DsubNV VP1 was unable to do so ( Figure S2D ) . Together , these results indicate that VP1 of DimmNV and DsubNV do not suppress RNAi in D . melanogaster . The inability of DimmNV VP1 and DsubNV VP1 to suppress RNAi in Drosophila S2 cells may be explained in two ways . First , viral RNAi suppressors may have a species-specific activity , following the prediction that prolonged virus-host coevolution may result in efficient RNAi suppressive activity in host species but not in non-host species . Second , some Nora-like viruses may either be unable to suppress RNAi , or they may encode RNAi suppressor activity in different regions of the viral genome , as has been observed for members of a single plant virus family [64]–[66] . To address the first possibility , we tested the ability of DimmNV VP1 and DmelNV VP1 to suppress RNAi in both host species using in vitro RNA cleavage ( slicer ) assays [67] in lysates of embryos from D . melanogaster and D . immigrans . Unfortunately , we were not successful in producing slicer competent lysates for D . subobscura . Moreover , members of the Drosophila obscura group encode multiple AGO2-like proteins of unknown function [68] . These proteins may be functionally redundant , and may not all be targeted by a VSR . We therefore chose not to include D . subobscura and DsubNV in subsequent analyses . In slicer assays , RNAi dependent cleavage of a 32P cap-labelled target RNA is induced by the addition of a target specific siRNA . Since the target RNA is radio-labelled at its 5′ cap , the 5′ cleavage product can be visualized by autoradiography after polyacrylamide gel electrophoresis . As expected , in both D . melanogaster and D . immigrans embryo lysates a specific cleavage product was observed after incubation with a target specific siRNA ( Figure 3A , lanes 2 and 7 ) . In line with our earlier report [14] , recombinant DmelNV VP1 protein potently inhibited cleavage of the target RNA in D . melanogaster embryo lysate , whereas the control , Maltose Binding Protein ( MBP ) , was unable to do so ( Figure 3A , compare lanes 3 and 4 ) . In contrast , recombinant DimmNV VP1 protein did not inhibit slicer activity in D . melanogaster embryo lysate ( Figure 3A , lane 5 ) , which is in line with our observation that DimmNV VP1 did not suppress RNAi in cell-based reporter assays in D . melanogaster cells ( Figure 2 ) . Surprisingly , in the D . immigrans embryo lysate both the DmelNV VP1 and the DimmNV VP1 protein substantially inhibited target RNA cleavage ( Figure 3A , lanes 9 and 10 ) . Again , as expected , the MBP control protein did not inhibit slicer activity ( Figure 3A , lane 8 ) . Quantification of independent experiments indicates that both DmelNV and DimmNV VP1 proteins suppressed slicer activity to a similar extent in the D . immigrans embryo lysate ( Figure 3B ) . These results , together with those from the cell-based reporter assays , indicate that DimmNV VP1 inhibits slicer activity in its natural host D . immigrans , but is unable to suppress RNAi in a heterologous D . melanogaster background . In contrast , DmelNV VP1 inhibits slicer activity in both a D . melanogaster and a D . immigrans background . We recently showed that DmelNV VP1 inhibits RNA cleavage ( slicer ) activity of a pre-assembled RISC in D . melanogaster [14] , suggesting that VP1 interacts with AGO2 to suppress its catalytic activity . To investigate a physical interaction between VP1 and AGO2 , we analyzed DmelNV VP1 immunoprecipitations ( IPs ) for the presence of AGO2 . To this end , we transfected S2 cells with a functional V5 epitope-tagged VP1 construct ( V5-VP1 ) that encodes the C-terminal 124 amino acids of VP1 along with a FLAG-tagged AGO2 cDNA construct . Immunoprecipitation of V5-VP1 resulted in specific co-precipitation of the FLAG-AGO2 protein ( Figure 4A ) . In contrast , the vector control failed to co-purify FLAG-AGO2 . To confirm the interaction between VP1 and AGO2 , we performed the reverse experiment . IP of FLAG-AGO2 protein co-precipitated V5-VP1 , while a FLAG-control vector was unable to do so ( Figure 4B ) . Although the interaction between VP1 and AGO2 is evident , only a minor fraction of VP1 was immunoprecipitated along with AGO2 . This observation is in agreement with our microscopic analyses , in which only a small fraction of FLAG-AGO2 protein co-localizes with VP1-EGFP ( data not shown ) . To confirm these results , we immunoprecipitated V5-VP1 protein and probed for endogenous AGO2 in the IP fraction . As expected , we observed a strong enrichment of endogenous AGO2 protein after VP1 IP , whereas IP of cells transfected with control plasmid did not co-precipitate AGO2 protein ( Figure 4C ) . These results indicate that DmelNV VP1 interacts with Dmel AGO2 in Drosophila S2 cells . These data and the results from our previous report [14] indicate that DmelNV VP1 interacts with Dmel AGO2 to antagonize the antiviral RNAi response . Similarly , given the observation that DimmNV VP1 suppresses slicer activity in D . immigrans lysates , it is likely that DimmNV VP1 interacts with Dimm AGO2 . We hypothesized that the inability of DimmNV VP1 to suppress RNAi in D . melanogaster may then be due to an inefficient interaction with Dmel AGO2 . To test these hypotheses , we analyzed VP1 interactions with host and non-host AGO2 proteins by co-IPs . First , we co-expressed V5 epitope-tagged DmelNV VP1 or DimmNV VP1 with Dmel FLAG-AGO2 in S2 cells and immunopurified the VP1 proteins using V5 affinity beads . As controls , we analyzed IPs of cells transfected with empty vector . As observed above ( Figure 4 ) , IP of DmelNV VP1 co-precipitated Dmel FLAG-AGO2 protein . In contrast , IP of DimmNV VP1 did not enrich Dmel FLAG-AGO2 in the IP fraction , compared to IP of the vector control ( Figure 5A ) . To confirm these results , we analyzed the interaction between VP1 proteins and endogenous D . melanogaster AGO2 . While DmelNV VP1 , but not the control vector , co-precipitated endogenous Dmel AGO2 ( Figure 4C , Figure 5B ) , DimmNV VP1 failed to co-IP endogenous Dmel AGO2 , which mirrors our observation with epitope-tagged Dmel AGO2 . These observations imply that the inability of DimmNV VP1 to suppress RNAi in D . melanogaster is due to its inability to efficiently interact with Dmel AGO2 . We next set out to analyze the interaction of DimmNV VP1 with Dimm AGO2 . To this end , we cloned the D . immigrans AGO2 cDNA sequence downstream of the FLAG epitope ( Dimm FLAG-AGO2 ) . As expected , the predicted protein domains of Dimm FLAG-AGO2 are similar to those of Dmel AGO2 , suggesting that the overall protein structure of Dimm and Dmel AGO2 are alike . Overall amino acid identity is 56% ( 63% when excluding the poly-glutamine repeats ) , with a higher level of conservation in the PIWI domain ( 77% identity ) than in the PAZ domain ( 45% identity ) . We thus analyzed the interaction of DmelNV VP1 or the DimmNV VP1 with Dimm FLAG-AGO2 in co-IP . Both DmelNV VP1 and DimmNV VP1 efficiently co-purified the Dimm AGO2 protein ( Figure 5C ) . These results show that AGO2-VP1 interactions correlate with RNAi suppressor activity: DmelNV VP1 interacts with both Dmel and Dimm AGO2 and suppresses slicer activity of these hosts; DimmNV VP1 interacts with Dimm AGO2 , but not Dmel AGO2 , and suppresses slicer activity in D . immigrans , but not in D . melanogaster . The species-specific interaction of DimmNV VP1 with Dimm AGO2 suggests that this interaction is the major determinant for the observed species specificity in slicer activity . To test this hypothesis , we set out to reconstitute Dimm AGO2-based silencing in D . melanogaster S2 cells and to analyze whether DimmNV VP1 could suppress this reconstituted pathway . To this end , we reduced endogenous AGO2 expression in D . melanogaster S2 cells using RNAi , and rescued its activity with either a Dmel AGO2 or Dimm AGO2 cDNA construct . First , we assessed the efficacy of knockdown of AGO2 expression in S2 cells using dsRNA targeting the coding sequence ( CDS ) or the 3′ untranslated region ( 3′ UTR ) of the endogenous Dmel AGO2 transcript . To monitor AGO2 activity in these S2 cells we induced RNAi with the Rluc-specific RNA hairpin ( described in Figure 2C ) . Compared to a non-specific dsRNA control , dsRNA against the CDS or the 3′UTR of AGO2 efficiently reduced hairpin-induced silencing of the Rluc reporter ( Figure 6A ) . This experiment thus creates the opportunity to knock down endogenous AGO2 expression with UTR-targeting dsRNA and rescue silencing defects with Dmel AGO2 or Dimm AGO2 cDNA constructs that lack the AGO2 3′UTR sequence and are therefore not targeted by this RNAi approach . Strikingly , both Dmel AGO2 and Dimm AGO2 rescued silencing activity in D . melanogaster cells , whereas Dmel AGO1 only slightly increased silencing activity relative to the vector control ( Figure 6B ) . These results indicate that Dimm AGO2 is fully functional in a D . melanogaster background and that the limited sequence identity to Dmel AGO2 does not impede its ability to interact with Dmel Dcr-2 , R2D2 and other components of the D . melanogaster RISC complex . Using this AGO2 rescue assay , we investigated whether DimmNV VP1 suppressed Dmel and Dimm AGO2-mediated silencing . DimmNV VP1 expression did not impede Dmel Ago2-mediated RNAi ( Figure 6B ) , which is in line with our observations that DimmNV VP1 did not inhibit RNAi in D . melanogaster S2 cells ( Figure 2A ) . In contrast , we observed that Dimm AGO2-mediated silencing was efficiently suppressed by DimmNV VP1 ( Figure 6B ) . We were unable to analyze DmelNV VP1 in this assay , as its potent RNAi suppressive activity would impede silencing of endogenous Dmel AGO2 , which is required for this assay . Together , these results indicate that the interaction of VP1 with AGO2 is the major determinant for its RNAi suppressive activity . Moreover , these data imply that the VP1-AGO2 interaction is a major determinant for the species-specific effects of VP1 . Together , our data suggest that the interaction between viral RNAi suppressors and its cellular protein targets can be host specific . Thus , DimmNV VP1 suppresses AGO2-mediated silencing of its D . immigrans host , but not in non-host D . melanogaster; in contrast , DmelNV VP1 seems to be more promiscuous and inhibits AGO2-mediated RNAi in both D . melanogaster and D . immigrans . An exciting hypothesis is therefore that the species-specific interaction between VP1 and AGO2 can mediate host specificity of Drosophila Nora viruses . To test this hypothesis , we generated replication-competent Sindbis virus ( SINV ) recombinants expressing either DimmNV VP1 , DmelNV VP1 , or , as a control , GFP from a second subgenomic promoter ( Figure 7A ) . As SINV is restricted by antiviral RNAi in Drosophila [14] , [69] , suppression of RNAi by expression of an exogenous viral RNAi suppressor is expected to yield higher viral RNA levels . Indeed , we previously showed that a DmelNV VP1 transgene renders SINV more pathogenic in D . melanogaster in an RNAi-dependent manner [14] . Our hypothesis thus predicts that the DimmNV VP1-expressing SINV recombinant reaches higher viral RNA levels than Sindbis-GFP in D . immigrans , but not in D . melanogaster , whereas Sindbis-DmelNV VP1 is expected to produce more viral RNA than SINV-GFP in both D . immigrans and D . melanogaster . We first verified stable expression of the VP1 transgenes by SINV recombinants by western blot ( Figure 7B ) . Next , we analyzed whether SINV recombinants are equally replication competent in the C6/36 cell line that does not express functional Dicer-2 . In this background , the presence of the VP1 transgene should not provide a replicative advantage over the GFP transgene . Indeed , VP1-expressing Sindbis virus recombinants replicated to slightly lower viral RNA levels than SINV-GFP in C6/36 cells ( Figure 7C ) , indicating that none of the recombinant viruses suffer from major replication defects . We next analyzed replication of SINV recombinants in D . melanogaster and D . immigrans hosts . As expected [14] , in D . melanogaster the DmelNV VP1 transgene strongly increased viral RNA levels compared to SINV-GFP infection at 7 days post-infection ( dpi ) ( Figure 7D , left panel ) . In general , D . immigrans only supported low levels of SINV replication . Nevertheless , in this host DmelNV VP1 increased SINV RNA levels , which is in line with our observation that this protein has RNAi suppressive activity in both hosts . The effects of DimmNV on viral RNA production also mirrored host specificity of its biochemical activity . Viral RNA levels of SINV-DimmNV VP1 were similar to SINV-GFP RNA levels in D . melanogaster ( Figure 7D , left panel ) . In D . immigrans however , a strong increase in viral RNA levels was observed . Thus , DimmNV VP1 enhances viral RNA levels of recombinant Sindbis virus in a host species-specific manner , suggesting that the interaction of viral RNAi suppressors with AGO2 may be a determinant of host-specific pathogenicity .
Viruses and their hosts engage in an ongoing arms race in which viral counter-defense mechanisms drive the adaptive evolution of host immune genes , which in turn requires ongoing counter-adaptations in viral immune antagonists [3] , [46] . This cycle of adaptation and counter-adaptation may result in species-specific interactions between virus and host [46] , [70] . The antiviral RNAi genes R2D2 , Dcr-2 and AGO2 belong to the 3% fastest evolving genes of Drosophila melanogaster and show evidence of positive selection in multiple species [47] . Strikingly , rapid evolution is observed in the antiviral RNAi pathway , whereas the microRNA pathway does not show evidence for rapid evolution . It is therefore possible that antagonistic host-parasite interactions – either through prolonged coevolution or through invasion by novel pathogens – are responsible for the observed rapid adaptive evolution in RNAi genes . Similarly , reciprocal antagonism between microbial pathogens and their hosts has been suggested to be the cause of positive selection observed in other insect immune genes , such as Relish and α-2-Macroglobulin [71]–[73] . Nora virus is a positive-sense RNA virus that was recently identified in laboratory stocks of Drosophila melanogaster [56] . Its unique genome organization and capsid structure suggests that Nora virus is the founding member of a novel virus family [57] . We report here that divergent Nora-like virus sequences are found in wild-caught D . immigrans and D . subobscura flies . Together with the recent isolation of Nora-like virus sequences from the horn fly Haematobia irritans and the parasitoid wasps Nasonia vitripennis and N . giraulti [59] , [60] and the presence of Nora-like sequences in the transcriptomes of the lacewing Chrysopa pallens and the moth Spodoptera exigua ( this report ) , our observations suggest that Nora virus is a member of a large family of widespread pathogens that infects multiple insect species . Although little is known regarding the natural host range of Nora viruses , it is worth noting that neither of our population samples of D . immigrans or D . subobscura contained sequences derived from the other Nora lineages ( i . e . DmelNV was not identified in D . immigrans or D . subobscura , and similarly for the other Nora-like viruses [DJO , unpublished data] ) , despite being initially collected as mixed samples of multiple Drosophila species . It is therefore possible that , as is the case for the purely vertically transmitted Sigma viruses , Nora viruses rarely move between hosts [74] . Plant and insect viruses can suppress the antiviral RNAi pathway of their hosts via a variety of mechanisms [11] , [14] , [29] , [30] , [35] , [38] , [43] , [75] . We recently showed that Nora virus VP1 suppresses RNAi by inhibiting AGO2 slicer activity of a pre-assembled RISC [14] . Here we show that the RNAi suppressor activity of VP1 from Nora-like viruses can be host specific and that its RNAi suppressive activity correlates with its ability to interact with AGO2 . DimmNV VP1 efficiently interacts with Dimm AGO2 and suppresses AGO2-mediated slicer activity in D . immigrans embryo lysates . In contrast , DimmNV VP1 was unable to suppress RNAi in D . melanogaster cells , did not interact with Dmel AGO2 , and did not inhibit slicer activity in D . melanogaster embryo lysates . These results are consistent with a model in which adaption and co-evolution of DimmNV with its host resulted in a species-specific AGO2-VP1 interaction . Our findings have important practical implications . Experimentally amenable model systems , such as Drosophila melanogaster or Arabidopsis thaliana , are often used to identify and characterize viral suppressors of RNAi , including those of viruses that naturally do not infect these hosts . Our observation that RNAi suppressor proteins may have species-specific activity suggests that it is important to take into account the correct evolutionary context in experiments aimed at the identification of viral suppressors of RNAi . For example , we note that we would not have detected RNAi suppressive activity in DimmNV , if we had solely relied on experiments in D . melanogaster . In striking contrast to DimmNV , DmelNV VP1 did not show species-specific activity . It can engage in an interaction with both Dimm and Dmel AGO2 and , accordingly , it inhibited slicer activity in both D . immigrans and D . melanogaster embryo lysates . We suggest that there are two potential explanations for this . First , it may be that these viruses differ in natural host range; the broader-spectrum functionality of DmelNV VP1 across divergent hosts could be maintained by selection if DmelNV has a wider host range than DimmNV . In support of this hypothesis , although none of these three viruses was identified from the other host species , DmelNV ( but not DimmNV ) has been identified in wild Drosophila simulans ( DJO , unpublished data ) . Second , if there is not a substantial trade-off associated with host-specialization and if DmelNV has colonized D . melanogaster quite recently , it could just be a matter of time until DmelNV loses its broad-spectrum VSR . We successfully reconstituted Dimm AGO2-based silencing in D . melanogaster cells . This result suggests that the limited amino acid identity with Dmel AGO2 ( ∼63% ) does not impede its ability to interact with Dmel Dicer-2 and R2D2 or other components of RISC and RISC-loading complexes . Thus , even though RNAi genes are rapidly evolving and show high rates of adaptive substitution , these results imply that this diversification has not impeded cross-species interactions of RNAi genes , even over the tens of millions of years that separate D . melanogaster and D . immigrans . This conservation of function may imply that the need for interaction between Dicer-2 , R2D2 , AGO2 , and other RNAi pathway genes imposes a constraint on the evolution of these genes , and thus their opportunity to evolve in response to virus-mediated selection . Together , our results suggest that rapid co-evolution between RNA viruses and their hosts may result in host species-specific activities of RNAi suppressor proteins . Moreover , our observation that DimmNV VP1 enhances viral RNA levels in a host-specific manner , suggest that viral RNAi suppressors are putative host-specificity factors .
Wild Drosophila populations were surveyed for the prevalence of Dmel Nora virus using RT-PCR ( unpublished data; PCR primers: forward 5′-GACCATTGGCACAAATCACCATTTG-3′ , reverse 5′-TCTTAGGCCGGTTGTCTTCACCC-3′ ) , which resulted in the identification of Nora virus-like PCR products from D . immigrans and from members of the obscura group ( sampled in Edinburgh , UK; longitude 55 . 928N , latitude 3 . 170W ) . A metagenomic approach was then used to obtain near-complete viral genomes . Flies were collected from elsewhere in the UK and samples were pooled by species for RNA extraction and Illumina double-stranded nuclease normalized RNA-sequencing . For D . subobscura , only male flies were used as females are difficult to distinguish morphologically from close relatives . RNA was extracted from each collection using a standard Trizol ( Invitrogen ) procedure , according to the manufacturer's instructions , and pooled in proportion to the number of contributing flies . In total , the two pools comprised 338 male D . subobscura ( 60 flies collected July 2011 Edinburgh 55 . 928N , 3 . 170W; 60 flies October 2011 Edinburgh 55 . 928N , 3 . 170W; 38 flies July 2011 Sussex 51 . 100N , 0 . 164E; 180 flies August 2011 Perthshire 56 . 316N , 3 . 790W ) and 498 D . immigrans ( 63 flies , July 2011 Edinburgh 55 . 928N , 3 . 170W; 285 flies July 2011 Edinburgh N55 . 921 , W3 . 193; 150 flies July 2011 Sussex 51 . 100N , 0 . 164E ) . Total RNA was provided to the Beijing Genomics Institute ( Hong Kong ) for normalization and 90-nt paired-end Illumina sequencing . Paired-end reads were quality trimmed using ConDeTri version 2 [76] and assembled de novo using the Trinity transcriptome assembler with default settings ( r2011-08-20 , ref . [77] ) . We used tBlastn with a DmelNV protein query to identify two partially overlapping Nora-like contigs from D . immigrans , and a single contig from D . subobscura . Quality-trimmed paired-end reads were mapped back to these contigs using Stampy ( version 1 . 0 . 21 , ref . [78] ) to obtain a consensus sequence , based on majority calls at each position . In total , 286 , 242 reads mapped to DimmNV ( 0 . 45% of all reads derived from D . immigrans , median read depth 1200-fold ) and 68 , 914 reads mapped to DsubNV ( 0 . 13% of all reads derived from D . subobscura , median read depth 133-fold ) . Consensus sequences have been submitted to GenBank under accession numbers KF242510 ( DsubNV ) and KF242511 ( DimmNV ) . The relationship between DmelNV ( GenBank NC_007919 . 3; [57] ) , DsubNV , DimmNV and other Nora-like sequences was inferred from VP4 ( capsid protein ) , which is the most conserved gene and the one with the most coverage in the non-Drosophila sequences . The other Nora-like sequences included Nasonia vitripennis Nora-like virus ( GenBank FJ790488; [60] ) , Haematobia irritans Nora-like virus ( GenBank HO004689 , HO000459 , and HO000794; [59] ) , and two Nora-like sequences newly identified here in the transcriptomes of Spodoptera exigua ( GenBank GAOR01000957; [79] ) and Chrysopa pallens ( GenBank GAGF01018485; [80] ) . We excluded sequences virtually identical to DmelNV that appear in the transcriptomes of Leptopilina boulardi and Leptopilina heterotoma ( GenBank GAJA01006738 , GAJC01010128 and GAJA01017939; [81] ) , as these species are widely cultured on D . melanogaster in the laboratory . For protein alignment , see text S1 . For the N . vitripennis Nora-like virus we selected the longest sequence ( FJ790488 ) for analysis . Two approaches to phylogenetic inference were used . First , MrBayes ( v3 . 2 . 1 , ref . [82] ) with discrete gamma-distributed rate variation and model-jumping between amino acid substitution models . Two parallel runs of four heated chains were used , and convergence was assessed by examination of the potential scale reduction factor ( PSRF ) and the variance in split-frequencies between runs ( PSRF ∼1 for all parameters; variance in split-frequencies <0 . 001 ) . Second , a maximum-likelihood analysis was run using PhyML [83] under a WAG amino-acid substitution model [84] with discrete gamma-distributed rate variation . Data were bootstrapped 1000 times to infer bootstrap node-support . The nonsynonymous divergence along each of the branches leading to DmelNV , DsubNV , and DimmNV was inferred using the method of Li [85] , relative to an ancestral sequence inferred by maximum likelihood using PAML [61] . Sliding windows of 50 codons wide were placed every 30 codons . Nominal genome-wide ‘significance’ thresholds for peaks were derived by repeating the sliding-window analysis on 1000 randomizations of codon-position order . The following constructs were described previously: all DmelNV VP1 constructs [14] , pAFW-AGO1 and pAFW-AGO2 [86] , pAFW ( Drosophila Genomics Resource Center , https://dgrc . cgb . indiana . edu ) , pMT-Luc [38] , pMT-Rluc [38] , pRmHa-Renilla-hairpin [87] , pAc5-V5-His-A ( Invitrogen ) , and pAc5-V5-His-Ntag [14] . cDNA of D . immigrans and D . subobscura was made using Promega MMLV-RT in the presence of Promega RNasin Plus according to manufacturer's instructions . Subsequently , DimmNV VP1 and DsubNV VP1 sequences were PCR amplified from D . immigrans and D . subobscura cDNA and cloned as full-length and deletion constructs downstream of the V5-His tag in pAc5-V5-His-Ntag ( details available upon request ) . The D . immigrans AGO2 cDNA sequence ( GenBank KF362118 ) , including partial 5′ and 3′ UTRs , was PCR amplified using the primer pair 5′-TGCAGCAAAAATTAGAAGCAAA-3′ and 5′-AGCCGTACCTAGAACCAGCA-3′ . The resulting PCR product was used as a template in a nested PCR using primer pair 5′-AGTTCTAGACCGCGGGAATGGGTAAAAAGAACAAGTTCAAACCA-3′ and 5′-AGTTCTAGACCGCGGGAAGCGCTGTGGCACAGCTTCCGC-3′ . The nested PCR product was subsequently cloned into the pAFW vector using the SacII and SalI restriction sites . To fuse the DimmNV VP1ΔN295 protein to the C-terminus of the maltose binding protein ( MBP ) , we PCR amplified the VP1 coding sequence from pAc5 . 1-Ntag-DimmNV VP1FL with primer pair 5′-AGTGGATCCCCAAAACTTCCAAGTGTACCTTCAAAG -3′ and 5′-GGTGTCGACTTAGTTTTGTTTATTTTTGTACCAATCGTTGG -3′ . The DsubNV VP1ΔN281 sequence was amplified from pAc5 . 1-Ntag-DsubNV VP1FL with primer pair 5′-TGACGGATCCCCAAACAAACCTCTAAAACC -3′ and 5′-ACTGGTCGACTCATTGTTGCTGAGTTGATTTG -3′ . The resulting PCR products were cloned into the pMal-C2X vector ( New England Biolabs ) using BamHI and SalI restriction sites . Double-stranded RNA was generated by in vitro transcription using T7 promoter-flanked PCR fragments as a template , as described previously [88] . For production of AGO2 dsRNA , a fragment of the coding sequence or the 3′ untranslated region of Dmel AGO2 was PCR amplified using primer combination 5′-TAATACGACTCACTATAGGGAGATACTATGGTGAAGAACGGGTCG-3′ and 5′-TAATACGACTCACTATAGGGAGAGAACATGTCCTCAATCTCCTCC-3′ , or primer combination 5′-TAATACGACTCACTATAGGGAGAGCAACGTATTGAATCTTATT-3′ and 5′-TAATACGACTCACTATAGGGAGAAGAACAATATTTGGCGGACC-3′ , respectively . miRNA and RNAi sensor assays in Drosophila S2 cells were performed as described [14] , [88] . For hairpin-induced silencing of the Rluc reporter , 5×104 S2 cells were seeded per well in a 96-well plate . The seeded cells were co-transfected with 10 ng pMT-Fluc , 10 ng pMT-Rluc , 50 ng pRmHa-Renilla-hairpin , and 50 ng of expression plasmids encoding VP1 and/or AGO per well using Effectene transfection reagent ( Qiagen ) . The pAc5-Ntag-DmelNV VP1Δ284 and pAc5-Ntag-DimmNV VP1ΔN295 plasmids were used for VP1 expression . For knockdown of endogenous AGO2 , 5 ng of AGO2 dsRNA or control dsRNA was co-transfected along with reporter plasmids . Two days after transfection , the expression of the luciferase reporters and the Rluc hairpin was induced by the addition of 0 . 5 mM CuSO4 per well . The next day , cells were lysed and Fluc and Rluc activity was measured with the Dual luciferase reporter assay system ( Promega ) according to manufacturer's protocol . For immunoprecipitations , S2 cells were seeded in 6-well plates at a density of 2×106 cells per well . The next day , cells were transfected with AGO2 and/or VP1 expression plasmids using Effectene transfection reagent ( Qiagen ) . Expression plasmids encoding DmelNV VP1ΔN351 , DmelNV VP1ΔN284 , or DimmNV VP1ΔN295 were used for co-immunoprecipitation experiments , as indicated in the figure legends . Three days after transfection , cells were washed twice with PBS and subsequently resuspended in lysis buffer ( 30 mM HEPES-KOH , 150 mM NaCl , 2 mM Mg ( OAc ) , 0 . 1% NP-40 , 5 mM DTT ) supplemented with protease inhibitor cocktail ( Roche ) . After incubation on ice for 10 minutes , the samples were passed forty times through a 25-gauge needle , followed by incubation on ice for 10 minutes . Subsequently , cell lysates were centrifuged at 13 , 000 rpm for 30 minutes and a sample of the supernatant was taken to analyze the input for IP . To remove proteins that non-specifically bind to the IP beads , the remaining supernatant was incubated with Pierce protein G agarose at 4°C for 5 hours while mixing end-over-end . Next , the protein G agarose was separated from the supernatant by centrifugation , after which the supernatant was incubated overnight with anti-V5 agarose affinity gel ( Invitrogen ) at 4°C while mixing end-over-end . The next day , the anti-V5 agarose was separated from the supernatant by centrifugation , and a sample was taken from the supernatant . After the remaining supernatant was removed , the V5-agarose was washed three times with lysis buffer , and three times with either wash buffer 150 ( 25 mM Tris-Cl , 150 mM NaCl ) or wash buffer 200 ( 25 mM Tris-Cl , 200 mM NaCl ) . All wash steps were done with 40 to 60 times beads-volume of wash buffer . Subsequently , the beads were boiled in SDS sample buffer at 95°C for 10 minutes , followed by a brief centrifugation step to collect the beads at the bottom of the tube . The proteins in the supernatant were then separated on a SDS-PAGE gel , after which they were transferred onto a nitrocellulose membrane by western blot . Primary antibodies used for western blot detection were anti-FLAG-M2 ( 1∶1000 dilution; Sigma ) , anti-V5 ( 1∶5000 dilution; Invitrogen ) , anti-AGO2 ( 1∶500 dilution; generously provided by the Siomi lab ) , and anti-tubulin-alpha ( 1∶1000 dilution , Sanbio ) ; secondary antibodies were goat anti-mouse-IRdye680 ( 1∶15 , 000 dilution; LI-COR ) , and goat anti-rabbit-IRdye800 ( 1∶15 , 000 dilution; LI-COR ) . All western blots were scanned using an Odyssey infrared imager ( LI-COR biosciences ) . To purify recombinant VP1 as MBP fusion proteins , the pMal-C2X-DimmNV VP1ΔN295 and the pMal-C2X-DsubNV VP1ΔN281 plasmids were transformed into the Escherichia coli BL21 ( DE3 ) strain . Subsequently , expression of recombinant protein was induced by addition of 0 . 2 mM IPTG . Protein expression was allowed to proceed overnight at 18°C . The next day , recombinant MBP-DimmNV VP1 and MBP-DsubNV VP1 were purified using amylose resin ( New England Biolabs ) according to the manufacturer's protocol . Purified protein was subsequently transferred to a dialysis membrane ( molecular weight cut-off 12–14 kDa ) and incubated overnight in dialysis buffer ( 20 mM Tris-Cl , 0 . 5 mM EDTA , 5 mM MgCl2 , 1 mM DTT , 140 mM NaCl , 2 . 7 mM KCl ) at 4°C , followed by a second dialysis step for 5 hours at 4°C . The dialyzed protein solution was stored at −80°C in dialysis buffer containing 30% glycerol . Purification of MBP-DmelNV VP1ΔN284 has been described previously [14] . A new D . immigrans isofemale line was established from flies collected in June 2012 in Edinburgh ( Coordinates 55 . 921N , 3 . 193W ) . D . immigrans was cultured similarly as D . melanogaster on standard media . Embryo lysates were generated from D . immigrans and from an RNAi-competent D . melanogaster laboratory control strain ( w1118 ) . In vitro target RNA cleavage assays in D . melanogaster embryo lysates were performed as described [14] . Minor changes were incorporated for the slicer assay in D . immigrans embryo lysate: the reaction contained 0 . 9 mM MgCl2 and was allowed to proceed for 5 hours at 25°C before RNA extraction . Suppressor activities of MBP-DmelNV VP1ΔN284 , DsubNV VP1ΔN281 , and MBP-DimmNV VP1ΔN295 proteins were analyzed in slicer assays . To produce recombinant Sindbis viruses , N-terminal V5 tagged DmelNV VP1ΔN284 and DimmNV VP1ΔN295 were PCR amplified from the respective insect expression vectors using primers V5 Fw: AGTTCTAGAAACATGGGTAAGCCTATCC; Dmel VP1 Rv: GGTTCTAGATTAACATTGTTGTTTCTGCGAG; and Dimm VP1 Rv: TGACTCTAGATTAGTTTTGTTTATTTTTGTACC . PCR products were cloned into the XbaI site following the second subgenomic promoter of the pTE3'2J vector [89] . The resulting plasmids were linearized with XhoI , and in vitro transcribed using the mMESSAGE mMACHINE SP6 High Yield Capped RNA Transcription kit ( Ambion ) . Transcribed RNA was then purified using the RNeasy kit ( Qiagen ) and transfected into BHK-21 cells to produce infectious virus . Supernatant was harvested and titered by plaque assay on BHK-21 cells . Sindbis-GFP was described previously [69] . The replicative capacity of recombinant viruses was analyzed on Dicer-2 deficient C6/36 cells . The cells were cultures as described previously [90] and inoculated at an multiplicity of infection of 0 . 01 . Cells were harvested directly after inoculation ( t = 0 ) and at 24 h thereafter and total RNA was isolated using isol-RNA lysis reagent ( 5 Prime ) . The RNA was treated with DNaseI and used as template for cDNA synthesis using Taqman reverse transcription reagents ( Roche ) . Viral RNA levels were determined by qPCR using the GoTaq qPCR Master Mix ( Promega ) and primers for either Sindbis ( SINV NS4 Fw: AACTCTGCCACAGATCAGCC; SINV NS4 Rv: GGGGCAGAAGGTTGCAGTAT ) and Aedes Albopictus RpL5 for normalization ( Aalb RpL5 Fw TCGCTTACGCCCGCATTGAGGGTGAT; Aalb RpL5 Rv: TCGCCGGTCACATCGGTACAGCCA ) . Flies ( Drosophila melanogaster w1118 and Drosophila immigrans ) were grown on standard yeast/agar medium at 25°C on a 12-h light/dark cycle . Flies were cured of Wolbachia sp . by tetracycline treatments as described in [91] . Five to seven-day-old female flies were CO2-anesthetized and intrathoracical single injections of 50 . 6 nL , corresponding to 5 , 000 plaque forming units for each virus , were performed using a nanoinjector Nanoject II ( Drummond Scientific Company ) as described in [92] . For each time point , total RNA from three independent pools of three flies was isolated using TRIzol Reagent ( Life Technologies ) . RNase-free DNase I treatment ( Roche ) was performed according to manufacturer's instructions , followed by acid-phenol/chloroform ( Life Technologies ) inactivation . Total RNA was quantified using a ND-1000 NanoDrop spectrophotometer ( Thermo Fisher Scientific ) . Reverse transcription was performed using SuperScript II Reverse Transcriptase with random hexamers as primers ( Life Technologies ) on 2 µg of total RNA . Quantitative PCR was performed with three technical replicates for each cDNA sample using FastStart SYBR Green Master ( Rox ) ( Roche ) on a ViiA7 Real-Time PCR instrument ( Life Technologies ) . As negative controls , cDNA reactions without reverse transcriptase and PCR amplification without cDNA template were included . Oligonucleotide primers were as follows ( F , forward; R , reverse ) Sindbis virus: SINV-NSP3_F , AAAACGCCTACCATGCAGTG; SINV-NSP3_R , TTTTCCGGCTGCGTAAATGC , and for normalization Dimm-AGO2_F , TTTTGTGCTGGGCGACAAAC; Dimm-AGO2_R , ATTCACCGCTTCGCAAATCG and Dmel-RpL32_F , CGGATCGATATGCTAAGCTGT; Dmel-RpL32_R , GCGCTTGTTCGATCCGTA . Relative viral RNA levels were calculated using the 2−ΔΔCT method [93] relative to input viral RNA , determined in flies that were harvested immediately after inoculation . Following log-transformation to homogenize variances , a T-test was used to compare relative RNA levels in SINV-VP1 recombinants to those in SINV-GFP . D . immigrans AGO2 cDNA sequence: KF362118; DsubNV consensus sequence: KF242510; DimmNV consensus sequence: KF242511; DmelNV: NC_007919 . 3; Nasonia vitripennis Nora-like virus: FJ790488; Haematobia irritans Nora-like virus: HO004689 , HO000459 , and HO000794; Transcriptome of Spodoptera exigua: GAOR01000957; Transcriptome of Chrysopa pallens: GAGF01018485 .
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Viruses and their hosts can engage in an evolutionary arms race . Viruses may select for hosts with more effective immune responses , whereas the immune response of the host may select for viruses that evade the immune system . These viral counter-defenses may in turn drive adaptations in host immune genes . A potential outcome of this perpetual cycle is that the interaction between virus and host becomes more specific . In insects , the host antiviral RNAi machinery exerts strong evolutionary pressure that has led to the evolution of viral proteins that can antagonize the RNAi response . We have identified novel viruses that infect different fruit fly species and we show that the RNAi suppressor proteins of these viruses can be specific to their host . Furthermore , we show that these proteins can enhance virus replication in a host-specific manner . These results are in line with the hypothesis that virus-host co-evolution shapes the genomes of both virus and host . Moreover , our results suggest that RNAi suppressor proteins have the potential to determine host specificity of viruses .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"invertebrates",
"rna",
"interference",
"microbiology",
"animals",
"animal",
"models",
"drosophila",
"melanogaster",
"model",
"organisms",
"epigenetics",
"drosophila",
"research",
"and",
"analysis",
"methods",
"viral",
"immune",
"evasion",
"insects",
"arthropoda",
"biochemistry",
"rna",
"cell",
"biology",
"nucleic",
"acids",
"virology",
"genetics",
"biology",
"and",
"life",
"sciences",
"molecular",
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"biology",
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] |
2014
|
Novel Drosophila Viruses Encode Host-Specific Suppressors of RNAi
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Phenotypic heterogeneity can confer clonal groups of organisms with new functionality . A paradigmatic example is the bistable expression of virulence genes in Salmonella typhimurium , which leads to phenotypically virulent and phenotypically avirulent subpopulations . The two subpopulations have been shown to divide labor during S . typhimurium infections . Here , we show that heterogeneous virulence gene expression in this organism also promotes survival against exposure to antibiotics through a bet-hedging mechanism . Using microfluidic devices in combination with fluorescence time-lapse microscopy and quantitative image analysis , we analyzed the expression of virulence genes at the single cell level and related it to survival when exposed to antibiotics . We found that , across different types of antibiotics and under concentrations that are clinically relevant , the subpopulation of bacterial cells that express virulence genes shows increased survival after exposure to antibiotics . Intriguingly , there is an interplay between the two consequences of phenotypic heterogeneity . The bet-hedging effect that arises through heterogeneity in virulence gene expression can protect clonal populations against avirulent mutants that exploit and subvert the division of labor within these populations . We conclude that bet-hedging and the division of labor can arise through variation in a single trait and interact with each other . This reveals a new degree of functional complexity of phenotypic heterogeneity . In addition , our results suggest a general principle of how pathogens can evade antibiotics: Expression of virulence factors often entails metabolic costs and the resulting growth retardation could generally increase tolerance against antibiotics and thus compromise treatment .
Genetically identical bacterial cells can exhibit remarkable phenotypic differences even when grown in homogeneous environments [1] , [2] . These differences can arise from stochastic fluctuations in the expression of individual genes [3] . Although there is evidence that the majority of genes are under selection for tight control of expression [4] , some genes are expressed heterogeneously . This raises the question of whether phenotypic heterogeneity can provide benefits and what those benefits might be . Two possible types of benefits have been proposed . First , heterogeneous gene expression can enable a population to hedge its bets in an unpredictable and fluctuating environment [3] , [5]–[7] . In this bet-hedging scenario , one part of the population expresses a phenotype optimized for the current environment , allowing it to survive and reproduce at a high rate . Another part of the population expresses a phenotype less well suited to the current environment , yet it is adapted to a state the environment might change into . Second , phenotypic heterogeneity can promote the division of labor in groups of genetically identical individuals [8]–[10] . This allows a population to perform different functions simultaneously that would be costly or impossible to combine within a single individual . Bet-hedging and division of labor are two fundamentally different adaptive strategies: The benefit of bet-hedging only manifests in fluctuating environments over time; the benefit of division of labor does not require environmental fluctuations to manifest , and the payoff to each subpopulation depends on the interaction with the other subpopulation . Both strategies have been shown independently to play important roles in microbial populations [8]–[13] . Whether heterogeneity in a single trait can promote both functions simultaneously , and how these functions can interact , is an open question . Our aim is to address this question and thereby to gain new insights into the functional complexity of phenotypic heterogeneity . Here , we present a case where phenotypic heterogeneity in a single trait—virulence gene expression in Salmonella typhimurium—shows characteristics of both strategies , the division of labor and bet-hedging . In S . typhimurium , expression of the type three secretion system 1 ( ttss-1 ) is bistable [14]–[16] . S . typhimurium uses ttss-1 for injecting effector proteins into host cells , promoting penetration of the host tissue . It is , therefore , an important determinant of virulence in this pathogen [17] . It has been shown that the bistable expression of ttss-1 leads to the division of labor among the members of a population . One subpopulation expresses ttss-1 ( T1+ cells ) and a fraction of those cells invade host tissue and evoke an inflammatory response that is beneficial for the S . typhimurium cells that do not invade [18] , [19] . This is thus a special case of “cooperative virulence” where the cooperative behavior is only expressed by a fraction of the population . Recently , it has also been shown that members of the T1+ subpopulation have low cellular growth rates [9] , [20] . Slow growth has been associated with tolerance to environmental stresses such as exposure to antibiotics [11] , [21]–[25] , and the formation of a slow-growing and persistent subpopulation has been interpreted as a typical example for bet-hedging in other organisms [11] , [26] . This raised the question of whether the slowly growing T1+ subpopulation is more tolerant to antibiotic exposure than the faster growing T1− subpopulation , so that the formation of these two subpopulations could promote bet-hedging during exposure to antibiotics . Although this question does not imply that exposure to antibiotics was the selective force that might have promoted phenotypic heterogeneity in virulence gene expression , it is interesting to ask whether a bet-hedging benefit under exposure to antibiotics is a potentially very relevant consequence of this heterogeneity .
In this study , we observed a connection between virulence gene expression and tolerance to antibiotics that could be general: The expression of virulence factors often entails metabolic costs [20] , [35] , [36] , possibly as a side effect of the expression of abundant proteins , and the resulting growth retardation could generally increase tolerance against antibiotics and thus compromise treatment . Under this scenario , pathogens would show tolerance to antibiotics even in situations where treatment was not an important selective factor in their evolutionary past . Understanding the cellular basis of antibiotic tolerance , and the consequences it can have on selection for virulence , is important for using existing treatment options effectively and for developing new strategies for controlling pathogens . In addition , our results suggest a general mechanism that could contribute to the evolutionary stability of cooperative behavior in microorganisms: If individuals that express a costly cooperative trait are also better protected against environmental impacts , then this could lead to a stabilization of the cooperative phenotype .
LB Lennox ( Sigma ) was used as the growth medium for preculturing for all experiments and as the growth medium in microscopy experiments where indicated . Ampicillin ( AppliChem ) was added at 100 µg/ml to the growth medium when required . LB buffered with mineral salts [37] was used for growth in chemostats . For the medium used in microscopy experiments , BSA ( Sigma ) and salmon sperm DNA ( Sigma ) was added to the medium at 150 µg/ml and 50 µg/ml , respectively , to avoid sticking of the cells to PDMS . Spent medium was obtained by growing the same strain as used in the respective experiments in LB without antibiotics , and by filter sterilizing it when the culture reached an OD 600 nm of 0 . 8–0 . 9 . Ciprofloxacin ( Fluka ) was used at a concentration of 0 . 05 µg/ml for the experiments shown in Figure 1 , Figure 3 , Figure S2 , Figure S3 , Figure S7 , Figure S8 , and Figure S9 , and at a concentration of 10 µg/ml for the experiments shown in Figure 2 . Kanamycin ( Sigma ) was used at a concentration of 16 µg/ml for the experiment shown in Figure S4 and at a concentration of 50 µg/ml for the experiment shown in Figure S6 . Plates containing 50 µg/ml kanamycin were used to determine strain ratios and colony forming units in the experiment shown in Figure 3 and Figure S9 . For the experiment shown in Figure S8 , spent LB was supplemented with IPTG ( Promega ) at the indicated concentrations . All strains are derivatives of S . typhimurium SL1344 [38] ( see Table S1 for a list of all strains used ) . Bacteria were grown overnight in culture tubes ( 100 mm×16 mm PP reaction tube , Sarstedt , Nümbrecht , Germany ) in 5 ml LB shaking at 220 rpm at 37°C , and then diluted 1∶100 in LB 2–3 h before the experiments to obtain exponentially growing cells in steady state . MICs for ciprofloxacin and kanamycin were determined by the standard method ( [39] , and Figure S5 ) , and a concentration of 2× MIC ( Figure S5 and Text S1 ) was used for antibiotic treatment in all experiments except for the experiments shown in Figure 2 and Figure S6 . For microscopy experiments , the flagella mutant strain X8602 [40] was used to avoid loss of cells from the channels . The plasmid psicA gfp [20] driving expression of gfpmut2 from the sicA promoter was introduced in all strains used for microscopy and flow cytometry , and GFP expression from this plasmid was used to assess induction of ttss-1 . For the experiment in Figure S2 , a hilD deletion allele from strain M2007 was P22 transduced into the X8602 background to yield strain M3139 , and subsequently transformed with the psicA gfp plasmid . For the experiment in Figure 3 and Figure S9 , 10 clones ( cultures grown from single colonies ) of a kanamycin-sensitive wild-type strain ( SB300 ) were competed against 10 clones of a kanamycin-resistant ΔhilD strain ( M2007 ) [20] , and 10 clones of a kanamycin-resistant wild-type ( resistance cassette inserted at the lpfED locus , showing an identical ttss-1 expression pattern to the kanamycin-sensitive wild type; Figure S9 ) were competed against 10 clones of a kanamycin-sensitive ΔhilD strain ( Z19 ) . Deletion mutants were constructed via lambda red recombination as described in [41] and P22 transduced into the clean SB300 or X8602 background , respectively . For the experiment shown in Figure S8 , the plasmid pCA24N-lacZ from the ASKA ( – ) collection [31] was transformed into M3139 . The microfluidic devices were made using a design adapted from the one published by Wang et al . [27] ( Figure S1 ) . Masks for photolithography were ordered at ML&C GmbH , Jena , Germany . Two-step photolithography was used to obtain silicone wafers . PDMS ( Sylgard 184 Silicone Elastomer Kit , Dow Corning ) was mixed in a ratio of 10∶1 , mixed by stirring , poured on the dust-free wafer , degassed in a desiccator until no visible air bubbles were present , and incubated overnight at 80°C for curing . PDMS chips of approximately 1 . 5 cm×3 . 5 cm were cut out around the structures on the wafer . Holes for medium supply and outlet were punched using 18G needles ( 1 . 2 mm×40 mm ) that were modified by breaking off the beveled tip and sharpening the edges of the then straight tip . Chemical activation of surface residues on the PDMS chips and on 24 mm×40 mm glass coverslips ( Menzel-Gläser , Braunschweig , Germany ) was performed by treating them for 6 min in a UV-Ozone cleaner ( Novascan PSD-UV ) . The PDMS chips were then placed on the glass coverslips , the exposed sides facing each other , and put on a heated plate at 90°C overnight for binding . Before an experiment , chips were rinsed with LB containing BSA and salmon sperm DNA ( concentrations as mentioned above , 2 ml/h pump speed ) until the growth channels were filled . Cells from an early exponential phase culture were concentrated approximately 100× by centrifugation ( 12 , 470× g , 2 min ) and loaded into the chip using a pipette . The process of cells entering the channels was observed microscopically , and when sufficient occupation of the channels was observed ( after 10–20 min ) , medium was pumped through . For all experiments , syringe pumps ( NE-300 , NewEra Pump Systems ) with 60 ml syringes ( IMI , Montegrotto Terme , Italy ) containing the media were used . Tubing ( Microbore Tygon S54HL , ID 0 . 76 mm , OD 2 . 29 mm , Fisher Scientific ) was connected to the syringes using 20G needles ( 0 . 9 mm×70 mm ) , which were directly inserted into the tubing . Smaller tubing ( Teflon , ID 0 . 3 mm , OD 0 . 76 mm , Fisher Scientific ) was then inserted into the bigger tubing and directly connected to the inlet hole in the PDMS chip . Medium change was performed by disconnecting the bigger and smaller tubings and reconnecting to the bigger tubing of a second medium supply . All experiments were run at a pump speed of 2 ml/h . Microscopy was performed using an Olympus IX81 inverted microscope system with automated stage , shutters , and a laser-based ZDC autofocus system . Several different positions were monitored in parallel on the same device , and phase contrast and fluorescence images ( where applicable ) of every position were taken every 5 min . Images were acquired using an UPLFLN100xO2PH/1 . 3 phase contrast oil immersion objective ( Olympus ) and a cooled CCD camera ( Olympus XM10 ) . For image acquisition , the CellM software package ( Olympus ) was used . Fluorescence images were acquired using a 120W mercury short arc lamp ( Xcite 120PC Q ) and the U-N41001 GFP filter set ( 450–490 nm ex/500–550 em/495 dichroic mirror , Chroma ) . The whole microscope was placed in an incubated box ( Life Imaging Services , Reinach , Switzerland ) at 37°C during all experiments . Images were analyzed using the plugin MMJ ( available at https://github . com/penamiller/mmJ ) for ImageJ [42] . It allows extracting of fluorescence intensities and cell length for the bottom cell of each channel during the course of the whole experiment , and scores division events based on cell length . For analysis of the experiments shown in Figure 1 , Figure S2 , Figure S3 , Figure S4 , Figure S8 , and for determining growth rates , the standard version of MMJ was used . For the experiments shown in Figure 2 and Figure S6 , a modified version of MMJ ( MMJAll ) was used that allows the extraction of all cells on single frames . Data were then further processed and plots were generated using R [43] . Cells were counted as surviving if they divided at least once after removal of antibiotic . For competition experiments , strains were mixed in a 1∶1 ratio in fresh LB , according to their optical density in overnight cultures . After 3 . 5 h of growth , all cultures were diluted 1∶100 in spent LB to extend the time cells spend in an induced state , and 0 . 05 µg/ml ciprofloxacin was added where indicated . Samples were taken at the indicated times , optical density was measured , and dilutions were spread on LB agar plates . After overnight growth , colonies were counted on the LB agar plates , and replica plated on LB agar plates containing 50 µg/ml kanamycin . Surviving colonies on LB kanamycin plates were counted the next day , and ratios of strains were determined . To control for a possible influence of the placement of the kanamycin resistance marker , the experiment was performed with two different strain combinations , 10 replicates each: Kanamycin-sensitive wild type ( SB300 ) was competed against kanamycin-resistant ΔhilD ( M2007 ) and kanamycin-resistant wild type ( resistance cassette inserted at the lpfED locus ) were competed against kanamycin-sensitive ΔhilD ( Z19 ) . Statistical analysis showed no significant influence of maker placement on the time-dependent relative frequency of the strains ( three way ANOVA , treatment×time×marker p = 0 . 19 ) . Data from both strain combinations were pooled for the plots shown in Figure 3 and Figure S9 . To determine the growth rates of the T1+ and T1− subpopulations , we grew ΔfliCΔfljB psicA gfp cells in the same microfluidic devices as used in Figure 1 . After initial growth in LB for 2 h , 45 min , we changed the medium to spent LB ( see above ) , which still contains enough nutrients to sustain growth , and monitored growth and gene expression for 13 h , 45 min . We identified all cells ( 11 cells in total ) in the experiment whose fluorescence levels were higher than 10 standard deviations above the fluctuations in background fluorescence ( i . e . , fluorescence of areas not containing cells in the vicinity of the respective cells measured ) , and determined the number of cell divisions during that time . To determine the growth rate of T1− cells , we used 11 cells from channels neighboring channels harboring T1+ cells that do not show a significant increase in fluorescence and determined the number of doublings of those cells during the same time period as for the T1+ cells in the neighboring channel . Data on cell length and divisions were extracted for a period of 100 min ( 20 frames ) —75 min ( 15 frames ) before and 25 min ( 5 frames ) after addition of the antibiotic—and linear regression was performed on the natural logarithm of cell lengths between divisions , between the start of the period and the first division in the period , and between the last division in the period and the end of the period , respectively , to determine the slope of the length increase during every division . Arithmetic means of the slopes of every individual cell were then calculated and multiplied by 12 to get a number for length doublings per hour . Chemostat growth was performed using a Sixfors system ( Infors HT , Bottmingen , Switzerland ) with six parallel reactors . Buffered LB was used as growth medium , as described in Ihssen et al . [37] . We inoculated 400 ml of medium in each reactor with 1 ml early exponential phase cultures that were previously diluted 1∶100 from six overnight cultures of individual clones . The reactors were stirred at 800 rpm , aerated with sterile air , and the temperature was controlled to be at 37°C . Growth as batch cultures was allowed for 3 . 5 h . Then fresh medium was pumped into the reactors at 104 ml/h ( 0 . 26 volume changes per hour , corresponding to a doubling time of 2 . 66 h ) , and total volume in the reactors was kept constant at 400 ml . After 16 h , pumping speed was changed for three of the six reactors to be 384 ml/h ( 0 . 96 volume changes per hour , corresponding to a doubling time of 0 . 72 h ) . After 6 h , 0 . 05 µg/ml ciprofloxacin was added to the medium supply , and all reactors were spiked with ciprofloxacin to a final concentration of 0 . 05 µg/ml , to keep the amount of the antibiotic constant in all replicates . However , we cannot rule out the possibility that metabolic differences between the slow and fast growing chemostat populations could lead to differences in the pharmacokinetics of the antibiotic . Samples were taken every 30 min , optical density at 600 nm was determined , samples were diluted up to 1∶107 in a series of 1∶10 dilutions , and 5 µl of each dilution were spotted on LB plates . After the spots dried , plates were incubated at 37°C overnight . Spots with numbers of colonies suitable for counting were then identified , and the number of colony forming units for every time point was calculated and normalized to the total number of cells as determined by the measured OD . For the experiment in Figure S10 , overnight cultures were diluted 1∶20 in LB Lennox , and analyzed in a flow cytometer ( LSRII , Becton Dickinson ) at an OD 600 nm of 0 . 9 . Bacteria were identified by side scatter , and GFP emission was measured at 530 nm . Data were analyzed using FlowJo software ( Tree Star , Inc . ) .
|
Scientists have recently realized that nature and nurture are not the only determinants of an individual's traits; some organisms also use random molecular processes to generate phenotypic variation among genetically identical individuals . This raises the question of whether such phenotypic variation could be beneficial and what such possible benefits might be . Working with pathogenic Salmonella bacteria , we discovered that phenotypic variation in one single trait—the expression of virulence genes—provides this pathogen with two critical benefits . First , it leads to the division of labor between different phenotypic variants that allows for effective host colonization , and second , it provides tolerance to antibiotics through a “bet-hedging” mechanism . Our results provide a new perspective on how phenotypic differences between individuals can provide benefits to clonal groups of organisms . At the same time , this study contributes to explaining why some pathogens can evade treatment , and could help to find new and better ways for controlling infectious disease .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"organismal",
"evolution",
"ecology",
"and",
"environmental",
"sciences",
"medicine",
"and",
"health",
"sciences",
"microbial",
"physiology",
"ecology",
"medical",
"microbiology",
"microbial",
"evolution",
"epidemiology",
"disease",
"dynamics",
"microbial",
"pathogens",
"population",
"dynamics",
"biology",
"and",
"life",
"sciences",
"population",
"biology",
"microbiology",
"evolutionary",
"biology",
"microbial",
"ecology"
] |
2014
|
Bistable Expression of Virulence Genes in Salmonella Leads to the Formation of an Antibiotic-Tolerant Subpopulation
|
Most cases of human African trypanosomiasis ( HAT ) start with a bite from one of the subspecies of Glossina fuscipes . Tsetse use a range of olfactory and visual stimuli to locate their hosts and this response can be exploited to lure tsetse to insecticide-treated targets thereby reducing transmission . To provide a rational basis for cost-effective designs of target , we undertook studies to identify the optimal target colour . On the Chamaunga islands of Lake Victoria , Kenya , studies were made of the numbers of G . fuscipes fuscipes attracted to targets consisting of a panel ( 25 cm square ) of various coloured fabrics flanked by a panel ( also 25 cm square ) of fine black netting . Both panels were covered with an electrocuting grid to catch tsetse as they contacted the target . The reflectances of the 37 different-coloured cloth panels utilised in the study were measured spectrophotometrically . Catch was positively correlated with percentage reflectance at the blue ( 460 nm ) wavelength and negatively correlated with reflectance at UV ( 360 nm ) and green ( 520 nm ) wavelengths . The best target was subjectively blue , with percentage reflectances of 3% , 29% , and 20% at 360 nm , 460 nm and 520 nm respectively . The worst target was also , subjectively , blue , but with high reflectances at UV ( 35% reflectance at 360 nm ) wavelengths as well as blue ( 36% reflectance at 460 nm ) ; the best low UV-reflecting blue caught 3× more tsetse than the high UV-reflecting blue . Insecticide-treated targets to control G . f . fuscipes should be blue with low reflectance in both the UV and green bands of the spectrum . Targets that are subjectively blue will perform poorly if they also reflect UV strongly . The selection of fabrics for targets should be guided by spectral analysis of the cloth across both the spectrum visible to humans and the UV region .
Tsetse flies ( Glossina spp . ) are restricted to sub-Saharan Africa where they transmit the trypanosomes causing the diseases of nagana in livestock and sleeping sickness , also known as human African trypanosomiasis ( HAT ) , in humans . Tsetse are commonly divided into three groups: i ) the Morsitans group ( savannah species ) which are the main vectors of the trypanosomes causing nagana; ii ) the Palpalis group ( riverine species ) which are largely responsible for transmission of Trypanosoma brucei spp , the causative agents of HAT , and iii ) the Fusca group ( forest species ) which currently are usually only minor vectors . There is no vaccine against trypanosomiasis , and the use of drugs is limited by problems of toxicity and resistance [1] . This , in addition to the fact that there are no prophylactic drugs available for humans , makes vector control particularly important . Given the distributions of tsetse vectors [2] and the incidence of HAT [3] , [4] , [5] , it seems that at least 90% of all cases of HAT are transmitted by the subspecies of Glossina fuscipes ( Palpalis group ) . One of the most important methods of tsetse control is the use of stationary artificial baits , represented either by three-dimensional traps or , more cost-effectively , by two-dimensional cloth screens ( targets ) that are treated with insecticide [6] . Most of the work on the optimisation of target design has been performed with tsetse other than G . fuscipes , especially with the savannah species G . morsitans morsitans and G . pallidipes and the riverine species G . palpalis palpalis and G . tachinoides [7] , [8] , [9] . For these tsetse species the most effective target consists of black and/or phthalogen blue panels of cotton cloth , which traditionally have been used to make a target of about 1×1 m . The colour “phthalogen blue” produced by colouring processes based on pigment blue 15 ( copper phthalocyanine ) or its solubilized derivatives ( turquoise blue ) appears to be the optimal colour . This has been demonstrated in detailed comparisons of traps , fabrics , dyes and paints [10] , [11] . Unfortunately , the most convenient locally-available blue fabric for tsetse applications , phthalogen blue cotton , has been difficult to obtain since the mid 1990's . Recently we have shown that for all subspecies of G . fuscipes , for G . tachinoides and G . palpalis gambiensis , but not for G . m . morsitans and G . pallidipes [12] , the cost-effectiveness of a target can be improved several fold by using only phthalogen blue cloth , reducing its size by about 94% , to become 25×25 cm , and by adding a panel of fine black polyester netting of the same size [13] , [14] . The distinctive optimum size of targets for Palpalis group flies suggests that targets for this group might also have a distinctive optimum colour . Moreover , even if blue panels were confirmed to be best for this group , it might be beneficial to opt for a fabric other than phthalogen blue cotton [10] , [11] because of its limited availability . Polyester fabrics in particular have great potential as they are more suitable in most technical respects than cotton and can be produced cheaply . Under outdoor conditions polyester lasts about four times longer than cotton [15] , which is particularly affected by UV degradation [15] , mildew [16] and rot [17] . Colour fastness is easier to achieve in polyesters [18] and the amount of insecticide needed to impregnate polyester is less than for cotton [19] . Furthermore , polyester is easier to transport because it weighs less than cotton . The present paper reports screening tests for the attractiveness of various colours and types of fabric in small cloth-and-net targets for G . f . fuscipes , one of the two most important vectors of sleeping sickness .
Targets consisted of a 25×25 cm panel of cloth flanked by the same-sized panel of fine black polyester netting ( Quality no . 166 , Swisstulle , Nottingham , UK ) . Various materials , obtained from different sources , were used for the cloth panel . Phthalogen blue cotton ( Phthalogen blue C ) ( used as the standard ) and black cotton ( Black 1 ) were already available at the research station and were from the same stocks used in previous studies of target design [13] . All other cotton materials ( Brown , Orange , Red 1–2 , Green 1–3 , Yellow 1 , Grey 1–2 , Purple 1 and White 1 ) were bought in a textile shop in Sweden . The white cotton cloth ( White 1 ) was washed with household bleach ( KlorinT , Colgate-Palmolive , active ingredient: sodium hypochlorite ) to create a material with high reflectance in the UV-region ( supplementary Fig . S1 and S2 ) . A black polyester ( Black 2 ) and two blue polyester ( Blue 7 and 8 called Phthalogen blue and Royal blue respectively by Vestergaard Frandsen Ltd , Lausanne ( VF ) ) panels were made from materials identical to those used in the tsetse traps and targets produced by VF . The material called Phthalogen blue polyester by Vestergaard is dyed with a blue dye to create a polyester cloth of a colour similar to phthalogen blue cotton but it was not dyed with phthalogen blue dye which can only be used on cotton material . In addition , VF supplied polyester materials that were blue ( Blue 2–6 ) , purple ( Purple 3–8 ) , white ( White 3 ) and yellow ( Yellow 2 ) . These polyester materials differed in weight , gloss and weave . Another seven polyester materials ( Blue 9–13 , Purple 2 , White 2 ) were produced at the Centre for Technical Textiles , University of Leeds , by applying dyes ( Appendix 1 ) to 100% polyester fabric ( matt , texturized; knitted; 150 denier; 36 filaments; weight 114 g m−2 ) supplied by VF . A total of 37 different materials were used . Their reflectance spectra were measured at the Danish technological service institute ( http://www . dhigroup . com ) on a Shimadzu dual beam photometer , from 190–900 nm at 10 nm intervals ( supplementary Fig . S1 ) . Studies were performed from February to December 2009 on Chamaunga Island ( 0 . 5 km2 ) ( 0° 25′S , 34°13′E ) , Lake Victoria , Kenya , using targets in which the cloth and netting panels were each covered on both sides with an electrocuting grid of fine black wires [20] . Tsetse knocked down by the grids fell into a tray of soapy water below each panel . In this way the catch from each panel could be recorded separately . Fifteen separate experiments ( supplementary Fig . S2 ) were conducted between 09 . 00 and 13 . 00 h , when G . f . fuscipes is most active [21] , [22] . Each experiment involved five targets with different coloured cloth panels , which were compared in two blocks of Latin squares of 5 days ×5 sites , with sites at least 50 m apart . This produced a total of 10 daily replicates with each target . The sites were the same throughout the 15 experiments: none of the sites was shaded by vegetation and all targets were oriented the same way relative to the sun . All experiments were performed under dry conditions . The combined daily catch of the cloth and net panels ( n ) was transformed to log ( n+1 ) for analysis of variance , the significance of differences between means being assessed by Tukey's Honest Significant Difference ( HSD ) test . All data analysis were performed using R [23] . Each experiment employed a target with Phthalogen blue C cloth as a standard , and the catches with the other targets were expressed as a proportion of the standard catch , to give a ‘catch index’ . Thus a target that caught , say , twice as many tsetse as the standard would have a catch index of 2 . 0 , and a target that caught only half that of the standard would have a catch index of 0 . 5 . Following earlier work [7] , [8] we also assessed the effect of colour on landing response by comparing the proportion of the total catch taken from the coloured panel . The proportion is termed the ‘landing score’ . The results were subjected to logistic regression with binomial errors using the statistical package R [23] . The catch of tsetse from ( i ) the target only and ( ii ) the target +flanking net were specified as the dependent variable and binomial denominator , respectively . Explanatory variables were the target colour , site and day . The significance of changes in deviance was assessed by either χ2 or , if the data were overdispersed , an F-test following re-scaling . The landing scores ( reported in table 1 and 2 ) are accompanied by their sample size . For analyses of catch and landing , the term “significant” implies P<0 . 05 . Multiple regression analyses were done in R to examine the relationship between the catch index and mean reflectance of all the 37 materials utilised in this study , in four colour bands which broadly matched those used in previous studies: 300–400 nm ( ‘ultraviolet’ ) , 410–500 nm ( ‘blue’ ) , 510–600 nm ( ‘green’ ) and 610–700 nm ( ‘red’ ) [7] , [24] . In addition , multiple regression analyses with percentage reflectance at four wavelengths ( 330 , 355 , 460 and 520 nm ) as explanatory variables were performed . Tsetse flies , like most higher flies , are believed to possess four photoreceptor types in their eyes . These four wavelengths were selected as being representative of the peak sensitivities of the four photoreceptor types , as indicated by previous studies [25] , [26] . Therefore they provide a measure of the stimulation of each photoreceptor by the 37 different fabric panels , which can be evaluated individually and relative to the other receptors , as in fly colour models [27] . Following earlier work [24] , logs were taken of both the target catch index and percent reflectivity as the relationship was found to be log-linear . Explanatory variables were removed from a model in which all terms were fitted without any interactions . Terms that reduced deviance significantly from the model were then used in a maximal model in which all terms were fitted with all their interactions . Non-significant interaction terms were removed by a series of F- tests commencing with terms having the highest order of interaction and least significance . Only terms that reduced deviance significantly from the maximal model were included in the final , minimally-adequate model .
The first set of seven experiments ( Table 1 ) compared the responses of G . f . fuscipes to baits of different colour . The colours can be divided into two groups: i ) “cut-off” colours , i . e . , colours with a steeply sloped spectrum ( yellow , orange , red and brown , Fig . 1 and Supplementary Fig . S1 ) , and ii ) “band reflecting” colours ( i . e . blue , green Fig . 2 and Supplementary Fig . S1 and S2 , [24] ) . The total catches suggest that no colour was significantly better than the Phthalogen blue C standard ( Table 1 ) – the index with other colours being on average only 0 . 58 ( range: 0 . 30–0 . 85 ) for males and 0 . 48 ( range: 0 . 30–0 . 85 ) for females , albeit that the index was not always significantly different from the Phthalogen blue C standard of 1 . 00 . “Cut off” colours , with spectra of slope >500 nm , had efficacies that more closely approached the Phthalogen blue C standard , being on average 0 . 63 ( range: 0 . 44–0 . 84 ) for males and 0 . 56 ( range: 0 . 35–0 . 84 ) for females ( Exp . 1 , 2 , 4 and 5 , Fig . 1B ) . Yellow and green targets performed poorly , with an average index of 0 . 51 ( range: 0 . 39–0 . 67 ) for males and 0 . 40 ( range: 0 . 32–0 . 55 ) for females ( Exp . 2–4 ) , while purple ( Purple 1 ) was highly effective for male ( average 0 . 84 , range: 0 . 82–0 . 85 ) flies but not females ( average 0 . 45 , range: 0 . 43–0 . 47 , Exp . 3 and 5 ) . The series of achromatic targets ( see Fig . 2 inset ) compared in two experiments indicated that effectiveness tended to decline in the order black , dark grey , light grey and white ( Exp . 6 and 7 ) , albeit that the index for White 2 differed almost two-fold between experiments . Since the catch with the Phthalogen blue C standard was higher than with any of the achromatic colours it seems that the effectiveness of the blue is dependent on colour discrimination rather than intensity contrast alone . In general the proportion caught on the cloth ( the landing score ) was low for all colours ( Table 1 ) , averaging 0 . 24 ( range: 0 . 08–0 . 40 ) for males and 0 . 23 ( range: 0 . 07–0 . 44 ) for females . The lowest proportions being observed for three shades of green cotton ( Green 1–3 ) and a purple cotton ( Purple 1 ) material in Exp . 3 and a white polyester ( White 2 ) in Exp . 7 ( Table 1 ) . These were the only experiments where a significant difference in landing score compared to the standard was observed . However , the landing score for three of the same materials was not significantly different to the standard in three other experiments ( comp . Exp . 4 for Green 2 , Exp . 5 for Purple 1 and Exp . 6 for White 2 . The second set of experiments ( Table 2 ) focused on the blue , purple and black colours that performed well in the first set ( Table 1 ) , but explored a wider range of materials . Again the Phthalogen blue C standard performed better than any other cloth . A higher peak at the reflectance accounting for most of the reflectance of Phthalogen blue C standard ( supplementary Fig . S2 ) did not increase the catch ( Exp . 9 ) . The same was observed in experiment 10 which compared blue materials with reflectance peaks at a slightly lower wavelength than the Phthalogen blue C standard ( among them Blue 8 ) . This contrasts with a previous study [24] which found a positive linear relationship between log transformed blue reflectance of the materials used for traps and the log transformed catches of the traps . This difference may be explained by the higher reflectance in the UV range for all the materials compared to the standard and Blue 8 respectively ( Supplementary Fig . 2 ) . The Phthalogen blue C standard was about twice as effective as the corresponding polyester cloth ( Exp . 8 , 9 and 13 ) . This poor performance of polyester did not seem to be due to the relatively high translucence of the fabric since reducing the translucence of the polyester , by using three layers together , did not increase the catch , in fact it lowered it . This decrease in fly numbers was significant for males ( Exp . 13 ) . Of all the fabrics tested the most promising alternative to the Phthalogen blue C standard was purple polyester ( Purple 2 , Exp . 11 , 12 and 14 ) . Furthermore , the purple polyester bait performed well in relation to the blue polyester material ( Blue 7 ) . Two experiments compared different shades of purple polyester cloth ( Exp . 14 and 15 ) . For males , Purples 4 , 5 and 8 had high catch indices ( Table 2 ) , while Purples 3 , 6 and 7 performed less well . The latter three purples were comparatively dark , with reflectance peaking at relatively lower wavelengths ( Supplementary Fig . S2 ) . For females the indices seemed little affected by the type of purple . As with the first set of experiments ( Table 1 ) , the second set ( Table 2 ) showed that a relatively low proportion of tsetse landed on the cloth panel . Overall the landing score was highest with the standard ( range: 0 . 28–0 . 45 for males , 0 . 19–0 . 43 for females ) . The significantly lower landing score observed for some materials ( Exp . 8 , 9 and 12 ) was mainly for blue polyester cloth which had a reflectance peak at the same wavelength as the standard but with a higher peak ( Blue 7 , 9 , 10 , 11 , 12 and 13 , Supplementary Fig . S2 ) . However , as in the first set of experiments the significantly lower landing response was not consistent between experiment ( comp . Blue 7 in Exp . 8 and 9 to Exp . 13 ) . Details of the regression models are shown in Table 3 . Modelling catch as a function of reflectance in the various colour bands showed that for both sexes , catch was negatively correlated with reflectivity in the ‘ultraviolet’ and ‘green’ bands but positively correlated with reflectivity in the ‘blue’ band . For females only , there was also a positive correlation with reflectivity in the ‘red’ band . Carrying out the regression analysis with reflectance at four wavelengths where tsetse show peak sensitivities showed that reflectivity at 360 nm , 460 nm and 520 nm were highly significant and exhibited the same trend as the analyses with colour bands: catches were negatively correlated with reflectivity at 360 nm ( ≈UV ) and 520 nm ( ≈green ) but positively correlated with 460 nm ( ≈blue ) . The ‘band’ ( regressions 1 and 2 ) and ‘peak’ models ( regressions 3 and 4 ) explained similar amounts of variation ( 40–42% for the male catches and 61–62% for females ) . For both the ‘colour band’ and ‘wavelength’ models , there were no significant interactions between the main explanatory variables .
The results show that the responses of G . f . fuscipes to colour are broadly similar to those of other tsetse: blues , and phthalogen blue sensu stricto in particular , are more attractive than other colours whereas reds and blacks are intermediate and green-yellow is least attractive [7] , [8] . In studies of G . pallidipes in Zimbabwe , [24] catch was modelled from different coloured traps as a function of mean reflectivity in four colour bands: 300–410 nm ( ultraviolet ) , 410–520 nm ( blue-green ) , 520–615 nm ( green-yellow-orange ) and 615–700 nm ( red ) . A similar approach was followed with studies of G . palpalis palpalis in Côte d'Ivoire using three colour bands: 300–380 nm ( ultraviolet ) , 380–480 nm ( ultraviolet-blue ) and 480–620 nm ( blue-green-yellow- red ) [7] . Furthermore , physiological studies of the eyes of tsetse [26] , [28] and other higher Diptera such as Musca [25] suggest that they have four peaks of sensitivity at 330 nm , 360 nm , 460 nm and 520 nm . Consequently these four bands and four reflectivity peaks were used in multiple regression analysis in this study . The results of these analyses , which show a negative correlation with ‘ultraviolet’ ( band and peak ) , green ( peak ) and ‘green’ ( band ) reflectivity and a positive correlation with ‘blue’ ( band and peak ) reflectivity , are in accordance with those for G . pallidipes [24] and G . palpalis palpalis [7] . Even though our data show that there are many similarities between the response of G . f . fusipes and other tsetse species to visual cues , the data also confirms the observed differences between Palpalis and Morsitans group tsetse flies . In the present study there is a 2–3× difference in catch between the best ( phthalogen blue cotton ) and worst ( yellow and targets with high UV reflectance ) targets . This range is similar to that reported for other Palpalis-group tsetse [7] , [8] but much less than the ten-fold range reported for Morsitans-group tsetse [29] . It seems likely therefore that the Palpalis-group tsetse are less responsive than the Morsitans-group to colour . Furthermore , Morsitans-group tsetse are equally attracted to black and blue targets , and black elicits a stronger landing response [29] , which contrasts with the landing scores reported here . Previous studies show that for Palpalis group tsetse , ( G . p . palpalis and G . tachinoides ) phthalogen blue is more attractive than black , and black does not seem to elicit a marked landing responses [7] , [8] . Our data confirm these results for G . f . fuscipes ( Exp . 5–7 , Table 1 and Exp . 8 , Table 2 ) . The landing score was in general low in this study and it did not increase with the greater UV reflectance of white ( Exp . 7 Table 2 ) , as was observed for G . p . palpalis , G . tachinoides and G . pallidipes in previous studies [7] , [8] , [30] , [31] . The widespread attraction of tsetse , along with many other species of biting Diptera , to blue and black objects is intriguing . It has been suggested that the contrast of blue against the green-yellow reflectance of vegetation is essentially a stimulus of ‘not vegetation’ [32] . More recently , it has been suggested that this phenomenon is related to the resting behaviour of tsetse; tsetse commonly rest in shady places which are tinted bluish by the scattered blue skylight [33] . However , tsetse attracted to targets are generally in a host- and/or mate-seeking mode of behaviour rather than seeking a resting site [8] , [34] and thus it seems unlikely that tsetse are ‘mistaking’ targets for shady places . Nonetheless , hosts themselves are characterised by shaded areas , particularly those on the underside of their bodies – hence the suggestion that countershading has evolved to conceal prey from predators [35] . The response to blue may therefore be related , at least in part , to the shadows created on the bodies of potential hosts . The data presented support the view that phthalogen blue cotton is at least as effective as any other material tested , and probably more effective than most or all of them . This is unfortunate given the declining availability of phthalogen blue dye , the technical problems with cotton , and the difficulties of dyeing artificial fibres with phthalogen blue . There seem to be two main options . First , it might be useful to look for other alternatives to phthalogen blue dyes – ones that can be used with polyester . Scientists have searched for such options previously [10] , [11] . Present experiments indicate the wavelengths on which such a search should concentrate for G . fuscipes . The purple-blue range ( 370–470 nm ) and red range ( >500 nm , for “cut off” colours ) was much more effective for males and females than the yellow-green range ( 525–600 nm , for “band reflecting” colours ) . Furthermore , light blue fabrics ( Blue 4 , Blue 5 and Blue 11 ) were in general of poor effectiveness . Our results underline the important negative effects of UV reflectivity on the attraction of tsetse to targets . Hence the selection of fabrics must be guided by spectral analysis and not just visual inspection of the cloth to identify fabrics that reflect strongly in the blue- but weakly in the UV-region of the spectrum . Second , if the only highly effective and colour-fast dye that is available can be used only on cotton , it might be acceptable to employ targets where the cloth panel is not treated with insecticide . Previous work has shown that treating a net with 0 . 8% deltamethrin results in >70% mortality for at least 9 months [36] . Present data for the distribution of catches between the netting and cloth panels ( the landing score ) suggest that the loss of effectiveness due to not treating the cloth will not be greater than about a third , and the loss might be much less if , as expected [37] , many or most of the flies that alight first on the cloth panel subsequently fly round it and so collide with the net before departing from the target site . In any event , allowing that it might be useful to screen cloth materials for use with those types of target in which only the netting is impregnated with insecticide , it would be useful if future screening tests employed not only the present fully-electrified targets but also targets in which the grid is restricted only to the net .
|
Efforts to control human African trypanosomiasis ( HAT ) would be strengthened by the development and application of more cost-effective methods of controlling the various species of tsetse fly vector . Among the most promising approaches is the use of insecticide-treated targets which use various olfactory and visual stimuli to attract and kill tsetse . Following on from previous studies of the responses of tsetse to odours and target size and shape , we compared the numbers of G . f . fuscipes attracted to different coloured targets . Our results show that the attraction of tsetse is correlated positively with reflectance in the blue region of the spectrum but negatively with the UV- and green regions . The best blue targets attract and kill three times more tsetse than the worst because of different UV reflectance levels in the different blue cloths . Hence selecting fabrics for use in targets must be based on spectral analysis of the fabrics' reflectance across the spectrum visible to tsetse , which includes UV , and not simply on the ‘rule of thumb’ that targets to control tsetse should be blue .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"vector",
"biology",
"tsetse",
"fly",
"biology",
"microbiology"
] |
2012
|
Optimizing the Colour and Fabric of Targets for the Control of the Tsetse Fly Glossina fuscipes fuscipes
|
One of the major challenges for management of visceral leishmaniasis ( VL ) is early diagnosis of cases to improve treatment outcome and reduce transmission . We have therefore investigated active case detection of VL with the help of accredited social health activists ( ASHA ) . ASHAs are women who live in the community and receive performance-based incentives for overseeing maternal and other health-related issues in their village . Through conducting interviews with 400 randomly selected ASHAs from four primary health care centers ( PHCs ) , it was observed that their level of knowledge about visceral leishmaniasis ( VL ) regarding transmission , diagnosis , and treatment was limited . The baseline data indicated that less than 10% of VL cases seeking treatment at the PHCs were referred by ASHAs . To increase the knowledge and the referral rate of VL cases by ASHAs , training sessions were carried out during the monthly ASHA meetings at their respective PHCs . Following a single training session , the referral rate increased from less than 10% to over 27% and the overall knowledge about VL substantially improved . It was not possible , however , to demonstrate that ASHA training reduced the time that individuals had fever before treatment at the PHC . Training ASHAs to identify VL cases in villages for early diagnosis and treatment at the local PHC is feasible and should be undertaken routinely to improve knowledge about VL .
There are estimated 200 , 000 to 400 , 000 new cases of visceral leishmaniasis ( VL ) , also known as kala-azar [1] every year worldwide . Bihar state in India contributes the majority of the disease burden of VL which is most prevalent in poorest populations [1] , [2] . The major risk factor for infection is living in the same household as someone with VL patients therefore it is important to identify and treat people as soon as possible [3] , [4] . Serological diagnosis with the rk39 rapid diagnostic test ( RDT ) can be performed on a single drop of blood on individuals with prolonged fever and splenomegaly [4] , [5] . Early diagnosis and complete treatment with new drugs such as oral miltefosine , paromomycin and liposomal amphotericin B used alone or in combination with each other can contribute to the elimination of VL [6]–[9] . Notwithstanding how effective VL point of care the diagnosis and treatments are , VL will continue to be transmitted and remain embedded in the community if VL cases do not seek early treatment . Awareness remains a major challenge in the most endemic districts of Bihar when considering the scale of the problem which involves thousands of villages [10] , [11] . Conducting one day fever camps is an effective approach to identify VL cases in highly endemic villages but requires significant resources when performed on large scale [11] , [12] . We have therefore considered a different approach for case detection including enlisting the involvement of community health care workers , also known as accredited social health activists ( ASHA ) to help identify potential VL cases in the endemic villages . One of the key strategies under the National Rural Health Mission ( NRHM ) in India is to have one ASHA for every 1000 villagers in rural populations . There are over 82 , 000 ASHAs for a population of 100 million people in the state of Bihar ( Source: State Health Society , Bihar ) . Selected from the village , ASHAs are women between 25 and 45 years with a minimum level of formal education who are trained to work as an interface between the villages and public health system and receive performance based incentives for promoting the different health care programs [13] , [14] . ASHAs are provided with training to acquire knowledge , skill and confidence for performing roles in immunization , referral and escort services for family planning , antenatal care and child health with the aim to reduce infant and maternal mortality . Some ASHAs have been trained to bring other ailing rural populations to the PHCs for diagnosis and treatment to reduce transmission of disease including for example HIV infections [15] . Recently it has been reported that ASHAs in Bihar were generally aware of VL but that their knowledge of treatment was limited and few were involved in VL control [16] . The National Vector Borne Disease Control Program of India has recently recognized the potential for training ASHAs to identify potential VL cases in the villages and has provided an incentive of 200 rupees for every case registered in PHCs and ensuring complete treatment . The purpose of this study was to determine whether targeted training of ASHAs can increase their knowledge of VL and whether this will result in increased recruitment of VL patients to the PHC for diagnosis and treatment .
Two districts , Muzaffarpur and Saran were selected on the basis of high VL and post kala-azar dermal leishmaniasis endemicity . The distance between these districts was about 80 kilometers . One highly endemic PHC from each of the two districts was selected as intervention PHCs ( Paroo and Marhoura ) where the ASHAs received training . Similarly , one highly endemic PHC from each of two districts was selected as control PHCs ( Sahebganj and Baniyapur ) where training was not conducted . The total population of the four PHCs is nearly two million . Approximately five hundred ASHAs ( in batches of approximately hundred ) from two intervention PHCs were trained on VL and PKDL case identification and on referral to PHCs for diagnosis and treatment . Training was provided during ASHA monthly meeting days which was cost effective in moving large numbers of ASHAs from village to PHC for training . Training was provided by experts from the research team using standard power point presentation , photographs and discussion . The importance of active case detection , early diagnosis and complete treatment in control of VL transmission was explained to the ASHAs . The knowledge of vector and its control by insecticide spraying was also explained to ASHAs extending their role and cooperation during spraying activity in their villages . Trained ASHAs were given a booklet on Kala-azar written in Hindi , register , carry bag , referral slip and a poster to place in their village describing what to do if someone has VL and PKDL symptoms . The study was approved by the ethics committee of the Rajendra Memorial Research Institute of Medical Sciences , Patna , India . Subjects participated in the research after a written informed consent . Data was collected by field assistants trained by faculty of the Rajendra Memorial Research Institute of Medical Sciences ( RMRIMS ) , Patna and support staff under direct supervision of the investigator team . Two trained field assistants were deployed in each of the 4 PHCs in the study . Data on VL cases was collected for both intervention and control PHCs before ASHA training ( 2011 ) and after ASHA training ( 2012 ) . Structured questionnaires prepared and pretested by faculty of RMRIMS were used for data collection from VL and PKDL cases treated in the 4 PHCs during 2011 and 2012 . Data was collected on treatment , compliance , duration of fever , first point of contact for health care after onset of symptoms and by whom the patients were referred for treatment . After training of ASHAs in March 2012 , data was again collected for VL and PKDL positive cases for the year 2012 ( April 2012 to December 2012 ) . To assess ASHA knowledge on different aspects of VL and PKDL and vector control after training in March 2012 , a questionnaire was administered to randomly selected 100 ASHAs from all 4 PHCs ( trained vs . non-trained ) from October to November 2012 and their knowledge were evaluated . This did not affect the working of the ASHAs in their village . Data entry was done in EpiInfo version 3 . 5 . 1 , software specifically designed for the study . Data analysis was done in Graph Pad , online Statistical Software .
Initially we determined which PHCs had the highest number of VL cases in 2009 and 2010 in Muzaffarpur and Saran districts of Bihar State so that these could be selected for this study . As shown in Figure 1 , using State government medical records , the highest number of treated cases was in Paroo and Sahebganj PHCs in Muzaffarpur district and Baniyapur and Marhoura PHCs in the Saran district . We therefore selected Paroo , Sahebganj , Baniyapur and Marhoura PHCs for this study . Using medical records from the PHCs , it was possible to obtain relevant information on the treated VL patients including where they lived , when they were treated and what they were treated with . Field assistants traveled into the community to locate the VL cases and obtained information including how long the VL cases were ill before seeking treatment , why they sought treatment at the PHC , and whether they were cured of symptoms . Once the base-line information was obtained , ASHAs received training about VL and PKDL through a power point presentation and discussion at the Paroo and Marhoura PHCs . Training was conducted during the routine monthly meetings where typically 100–200 ASHAs attended . The control PHCs were Sahebganj and Baniyapur where baseline information was also gathered but the ASHAs were not trained . Approximately 6 months after training , ASHAs from the intervention PHCs ( Paroo , Marhoura ) and control PHCs ( Sahebganj , Baniyapur ) were interviewed to determine their level of knowledge about VL . As shown in Table 1 , there was a significant increase in the basic knowledge about transmission , diagnosis and treatment in the group of ASHAs from the intervention PHCs compared to the ASHAs from the control PHCs . This demonstrates that the training session did improve knowledge about VL . It is particularly noteworthy that considerable more ASHAs in the trained group were aware that treatment with miltefosine required 4 weeks and this should help with compliance in the future . Table 2 shows the results for VL case referrals by the ASHAs in 2011 ( period prior to training ) and 2012 ( period following training ) . In the intervention PHCs Paroo and Marhoura , referrals by ASHAS were 9 . 8% and 4 . 0% respectively in 2011 and this increased following training to 28 . 3% and 27 . 5% in 2012 . In the control PHCs Sahebganj and Baniyapur , referrals were 4 . 5% and 6 . 2% in 2011 respectively and 26 . 6% and 9% in 2012 . The increase in referrals from 4 . 5% to 26 . 5% in the control PHCs , Sahebganj was unexpected . We determined that this was due to a single village ( Tarawa ) where one ASHA referred 14 VL cases making up the majority of the total cases referred to the Sahebganj PHC . The ASHA in Tarawa had become informed about VL from the field assistants when baseline information on previous VL cases was collected from her village in 2011 . Subsequently in 2012 , there were 14 VL cases in Tarawa and the ASHA referred all of these cases to the Sahebganj PHC . If these 14 cases were not included in the analysis ( shown in brackets in Table 2 ) , then the percentage of cases referred to this control PHC in 2012 would be 10% . We also attempted to determine the time that the VL cases had fever before seeking treatment at the PHC and whether this interval was shortened following ASHA training . The recorded mean duration of fever however did not change between 2011 ( before training ) and 2012 ( after training ) and varied from 5–7 weeks as shown in Table 3 . This could indicate that ASHA training does not reduce the time before patients seek treatment . Alternatively , the reason there was no change may be due to the difficulty to accurately determining the length of time that fever was present through the interview process .
This study was initiated to address the challenges imposed by scaling up active case detection of VL cases when the target region involves thousands of villages in multiple districts and resources are limited . We therefore considered interventions that use existing resources . ASHAs live in the endemic villages , are aware of community health issues and are accessible as a large group during monthly meeting sessions at their local PHCs . ASHAs have already been involved in improving different health care programmes under NRHM [14] , [15] and have been reported to have a basic knowledge of VL [16] . Our results support the conclusion of the previous study and extend this by showing that ASHA knowledge of VL can be substantially augmented by additional training at their local PHCs . Several key observations were made in this study . First , although of 50% of the ASHAs in this study had a basic knowledge of VL symptoms and transmission , less than 20% of the ASHAs were familiar with diagnosis and current treatment of VL despite being in the most highly endemic districts . This knowledge increased dramatically at 6 months following the training when 80% of ASHAs were familiar with the time necessary for treatment with miltefosine . This could be useful to increase treatment compliance . Second , it was possible to more than double the percentage of patients recruited to the government PHCs following only one ASHA training session during one of their monthly meetings at the PHC . We expect this would increase if the training were performed at least 2 times per year . In addition to the training sessions , approximately 500 ASHAs were also provided with a poster to be placed in a prominent place in 500 villages to inform people about VL and PKDL symptoms and that diagnosis and treatment is free of cost at the local PHC . We believe that display of posters in 500 villages helped to create awareness of VL and PKDL reaching about one million rural populations in the highly endemic area . We are currently in the process of conducting training for ASHAs in control PHCs with the distribution of posters for wider dissemination of knowledge regarding VL . There were however several drawbacks of this study . First , it was difficult to have an unbiased control group because ASHAs and villagers became more knowledgeable of VL during the collection of baseline information in the control villages . As described in the results section , one ASHA from a highly endemic control village ( Tarawa ) had discussed the study with the field assistants as they interviewed previous VL cases . As a result , this ASHA became knowledgeable about VL and sent 14 cases to the Sahebganj PHC . Although this compromised the control group , it did demonstrate that the ASHA was attentive to health related issues in her village and responded appropriately . Another drawback was the difficulty to confidently determine how long patients had fever prior to seeking treatment at the PHC . Although low-grade fever may be present , this is generally not considered an illness in these villages making it difficult to accurately measure time of fever . Furthermore , many VL cases had initially sought treatment from local quacks which further complicated the ability to accurately determine the time of fever before seeking attention at the PHC . Better refinement of the questionnaire could help . For example , asking the patient to describe their symptoms and then asking how long they had those symptoms before going to the PHC may be more effective way in determining the duration of illness . Under the current government supported VL elimination program , ASHAs should be paid 200 rupees for every VL case they identify . The current cash incentive scheme is not functioning properly because of poor financial management at district and sub-district levels . For the purpose of this study , ASHAs were paid from study funds but clearly the issue of payment must be corrected otherwise the training program will lose credibility . Reducing the time a VL case remains in the village will reduce the time of disease transmission and reduce cases . Therefore the reimbursement of ASHAs would represent a significant cost saving to the government . Taken together , the observations from this study argue that training ASHAs at the PHCs is feasible and should be undertaken to support the active case detection of VL cases in endemic districts of Bihar . Furthermore , this would also recruit non-VL febrile cases to the PHCs to identify and treat other infections in the area .
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Visceral leishmaniasis ( VL ) is a potentially deadly parasitic disease that affects over 20 , 000 people in Bihar , India annually . Accredited social health activists ( ASHA ) are women who live in the community and render their services towards maternal and other health concerns in the villages where VL is endemic . One of the major problems is that VL cases remain in the village without seeking treatment and , during this period , continue to transmit the disease . To address this problem , we have investigated the possibility of training ASHAs to identify potential VL cases and to send them for treatment at the local primary health care centers ( PHCs ) . We demonstrate that ASHA knowledge about VL increased significantly with training and this resulted in increased recruitment of patients for diagnosis and treatment to the local PHCs . These observations demonstrate that training of ASHAs should be conducted routinely to support the elimination of VL .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"public",
"and",
"occupational",
"health",
"infectious",
"diseases",
"medicine",
"and",
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2014
|
Impact of ASHA Training on Active Case Detection of Visceral Leishmaniasis in Bihar, India
|
Few effective drugs are available for soil-transmitted helminthiases and drug resistance is of concern . In the present work , we tested the efficacy of the veterinary drug monepantel , a potential drug development candidate compared to standard drugs in vitro and in parasite-rodent models of relevance to human soil-transmitted helminthiases . A motility assay was used to assess the efficacy of monepantel , albendazole , levamisole , and pyrantel pamoate in vitro on third-stage larvae ( L3 ) and adult worms of Ancylostoma ceylanicum , Necator americanus and Trichuris muris . Ancylostoma ceylanicum- or N . americanus-infected hamsters , T . muris- or Ascaris suum-infected mice , and Strongyloides ratti-infected rats were treated with single oral doses of monepantel or with one of the reference drugs . Monepantel showed excellent activity on A . ceylanicum adults ( IC50 = 1 . 7 µg/ml ) , a moderate effect on T . muris L3 ( IC50 = 78 . 7 µg/ml ) , whereas no effect was observed on A . ceylanicum L3 , T . muris adults , and both stages of N . americanus . Of the standard drugs , levamisole showed the highest potency in vitro ( IC50 = 1 . 6 and 33 . 1 µg/ml on A . ceylanicum and T . muris L3 , respectively ) . Complete elimination of worms was observed with monepantel ( 10 mg/kg ) and albendazole ( 2 . 5 mg/kg ) in A . ceylanicum-infected hamsters . In the N . americanus hamster model single 10 mg/kg oral doses of monepantel and albendazole resulted in worm burden reductions of 58 . 3% and 100% , respectively . Trichuris muris , S . ratti and A . suum were not affected by treatment with monepantel in vivo ( following doses of 600 mg/kg , 32 mg/kg and 600 mg/kg , respectively ) . In contrast , worm burden reductions of 95 . 9% and 76 . 6% were observed following treatment of T . muris- and A . suum infected mice with levamisole ( 200 mg/kg ) and albendazole ( 600 mg/kg ) , respectively . Monepantel reveals low or no activities against N . americanus , T . muris , S . ratti and A . suum in vivo , hence does not qualify as drug development candidate for human soil-transmitted helminthiases .
The hookworm species Ancylostoma duodenale and Necator americanus , the whipworm Trichuris trichiura , the threadworm Strongyloides stercoralis , and the roundworm Ascaris lumbricoides are soil-transmitted helminths ( STH ) of great public health importance . Cumulatively , these parasites affect more than one billion people globally , particularly in developing regions of Asia , Africa , and Latin America [1] , [2] . If untreated , infections with STH are present for years and patients suffer from moderate to severe intestinal disturbances , anemia , nutrient loss and profound physical and mental deficiencies [3] , [4] . Helminth control relies primarily on the regular administration of anthelmintics , typically carried out within the framework of school-based deworming programs , once or twice a year [5]–[7] . Five drugs are currently available for the treatment of infections with STH ( albendazole , mebendazole , pyrantel pamoate , levamisole , and ivermectin ) , all of which have been registered for human use before or during the 1980's [8] , [9] . No new anthelmintic drug for human use has reached the market since then . Moreover , none of these drugs are efficacious using single doses on all STH species , with particularly low efficacy observed on T . trichiura [10] . Relying on only a handful of drugs is a precarious situation , in the light of a possible emergence of drug resistance [10] . Since drug resistance to nematodes of veterinary importance is widely spread and increasing in frequency , most of the anthelmintic drug research and development efforts are motivated by veterinary needs [11] . For example , albendazole , mebendazole , and pyrantel pamoate were originally developed for livestock and pets [12] . Monepantel ( AAD1566 ) belongs to a new class of veterinary anthelmintics , the amino-acetonitrile derivatives . It has been proposed that monepantel interferes with nematode-specific acetylcholine receptor subunits , leading to body wall muscle paralysis and subsequent death of worms . Due to its unique mode of action , the drug has proven efficacy against nematodes infecting livestock which are resistant to current anthelmintic drugs [13] . Monepantel has been extensively tested on different nematode isolates . Administered at a single oral dose of 2 . 5 mg/kg , it was found to be safe , well-tolerated by ruminant hosts , and showed high cure rates on fourth stage larvae and adult worms of 15 nematode species [13]–[16] . Due to its high and broad nematocidal activity , monepantel was considered to be a candidate for a human health directed program . The aim of the present investigation was to study the activity of monepantel , compared with the reference drugs , albendazole , levamisole , and pyrantel pamoate , in five parasite-rodent models , that correspond to important human STH and in vitro . Ancylostoma ceylanicum and Necator americanus were both adapted using eggs from infected dogs or humans to an unnatural host , the golden hamster , and represent robust rodent models for hookworm infections [17] , [18] . The Trichuris muris mouse model is an excellent model for trichuriasis [19] , [20] . Strongyloides ratti in rats is a commonly used murine model for strongyloidiasis [21] . Finally , murine infection with Ascaris suum is a model which mimics the early infection of A . lumbricoides . The survival of different larval stages and adult worms of A . ceylanicum , N . americanus , and T . muris was evaluated in vitro , following monepantel incubation using a motility assay . The in vitro activity of monepantel on S . ratti has been described recently [22] . In vivo , we studied worm burden reductions and for A . ceylanicum , N . americanus , and T . muris , worm expulsion rates were also measured .
Monepantel was kindly provided by Novartis Animal Health , St-Aubin , Switzerland . Albendazole and pyrantel pamoate were purchased from Sigma-Aldrich ( Buchs , Switzerland ) , and levamisole-hydrochloride from Fluka ( Buchs , Switzerland ) . For the in vitro studies , stock solutions of the drugs were prepared in 100% DMSO ( Fluka , Buchs , Switzerland ) and stored at 4°C . For the in vivo studies , drugs were suspended in 7% ( v/v ) Tween 80% and 3% ( v/v ) ethanol or DMSO/PEG shortly before treatment . Three-week-old male Syrian Golden hamsters were purchased from Charles River ( Sulzfeld , Germany ) . Four-week-old female NMRI mice and 3-week-old female C57Bl/6J mice were purchased from Harlan ( Horst , The Netherlands ) . Three-week-old female Wistar rats were purchased from Harlan ( Horst , The Netherlands ) . All animals were kept in macrolon cages under environmentally-controlled conditions ( temperature: 25°C , humidity: 70% , light/dark cycle 12 h/12 h ) and had free access to water and rodent food ( Rodent Blox from Eberle NAFAG , Gossau , Switzerland ) . They were allowed to acclimatize in the animal facility of the Swiss Tropical and Public Health Institute ( Swiss TPH ) for 1 week before infection . The current study was approved by the local veterinary agency based on Swiss cantonal and national regulations ( permission no . 2070 ) . Ancylostoma ceylanicum third-stage larvae ( L3 ) were kindly provided by Prof . J . M . Behnke ( University of Nottingham ) . The A . ceylanicum life cycle [23] had been maintained at the Swiss TPH since June 2009 [17] . To maintain the life cycle , hamsters were treated orally 1 day before infection and then twice weekly with 3 mg/kg hydrocortisone ( Hydrocortone® , MSD ) or with 1 mg/l dexamethasone ( dexamethasone water-soluble , Sigma-Aldrich ) in the drinking water . They were orally infected with 150 A . ceylanicum L3 , which had been harvested less than 1 month before infection and had been assessed microscopically for viability . Animals assigned to in vivo studies were not treated with hydrocortisone and were infected with 300 L3 . Infective N . americanus L3 were the gift of Prof . S . H . Xiao ( National Institute for Parasitic Diseases , Shanghai ) . Hamsters were immunosuppressed with dexamethasone as described above and were infected subcutaneously with 250 viable N . americanus L3 . Embryonated T . muris eggs were kindly obtained from Prof . J . M . Behnke and Prof . H . Mehlhorn . The life cycle had been maintained at the Swiss TPH since January 2010 as described elsewhere [19] . Briefly , T . muris eggs were evaluated for embryonation under the microscope ( magnification 80–160× , Carl Zeiss , Germany ) . NMRI mice were orally infected with 400 embryonated eggs . Mice were treated either subcutaneously ( s . c . ) 1 day before infection and then every second day between days 5 and 15 with 15 mg hydrocortisone ( Hydrocortisone 21-hemisuccinate sodium salt , Sigma-Aldrich ) in 0 . 9% NaCl solution , or with 8 mg/l dexamethasone in the drinking water until the end of the experiment . The S . ratti life cycle had been maintained over decades at the Swiss TPH , by serial passage through rats . Rats were infected subcutaneously with 735 freshly harvested S . ratti L3 . Infective A . suum eggs were obtained from Prof . S . M . Thamsborg , University of Copenhagen and Prof . G . Cringoli , University of Naples . Briefly , C57Bl/6J mice were orally infected with 500 embryonated eggs , according to a procedure described elsewhere [24] . The larval or adult motility assay is currently the method of choice to evaluate drug sensitivity of different nematode species [25]–[27] . Non-motile worms were considered as dead and the percent viability or survival in each well was calculated . The average of motility scores for one drug was calculated for each concentration and normalized into percentage , relative to control . IC50 values were expressed based on the median effect principle using CompuSyn ( version 1 . 0 ) . The r value represents the linear correlation coefficient of the median-effect plot , indicating the goodness of fit , hence the accuracy of the IC50 [33] . Variance analysis in the ovicidal activity studies was performed with the Fisher's exact test , using StatsDirect ( version 2 . 4 . 5; StatsDirect Ltd; Cheshire , UK ) . The worm burden reductions were determined by comparing the mean number of adult worms in the intestine of a treated group with the mean numbers of worms in the control group . Means and standard deviations were calculated using Microsoft® Excel 2003 . The worm expulsion rates were calculated by dividing the number of expelled worms of a treatment group by the group's total worm burden . The Kruskal-Wallis test and the Mann-Whitney U test were used to assess the statistical significance of the worm burden reduction , using StatsDirect .
The effects of monepantel and reference drugs on L3 and adult worms of A . ceylanicum and T . muris after 72 h of exposure in vitro are presented in Table 1 .
To date , only five drugs are included in the WHO model list of essential medicines to treat infections with human STH . Most of these anthelmintics were discovered before the 1980s . Though there is no evidence yet for emerging resistance to any of these drugs in human helminth populations , there are worrying signs that anthelminthic efficacy may be declining [34] , [35] . In addition , the increased frequency of reported low cure rates , in particular against T . trichiura and hookworm infections , highlight the need to find alternative drugs [10] . A . ceylanicum , N . americanus , T . muris , S . ratti , and A . suum are five well-established laboratory parasite-rodent models of relevance to human STH . The aim of the present study was to determine their sensitivities to monepantel , a broad spectrum and safe drug used for livestock which recently entered the market for veterinary use . It is one of the few available drug candidates eligible for rapid transitioning into development for human STH infections [36] . Monepantel activates signaling via nematode-specific DEG-3 subtype nicotinic acetylcholine receptors ( nAChRs ) , causing a hypercontraction of the body wall muscles leading to paralysis and hence , death of the worm [13] . ACR-23 protein , a member of the DEG-3 group in Caernohabtitis elegans , and its homolog MPTL-1 in Haemonchus contortus , another model for gastrointestinal nematodes , are major targets of monepantel . The absence of MPTL-1 , observed in some nematode species resulted in reduced drug sensitivity [22] . Ancylostoma ceylanicum adult worms were found to be highly sensitive to monepantel in vitro , in contrast to the third-stage larvae , but the drug lacked ovicidal activity . Hamsters harboring adult A . ceylanicum were cleared from the worms following a 10 mg/kg single oral dose of monepantel . N . americanus was not affected by the drug in vitro and only moderately susceptible in vivo to 10 mg/kg or higher doses . These findings suggest a relative stage and species specificity , which might be explained by the absence of a functional MPTL-1 homolog in A . ceylanicum L3 and possibly in L3 and adult N . americanus . Trichuris muris third-stage larvae were only moderately sensitive to monepantel after incubation for 72 h in vitro , whereas adult stages were not affected , neither in vitro nor in vivo . Monepantel had already been reported to lack activity against T . ovis , a minor parasite of sheep [15] , [16] , a finding that is in accordance with our data . In addition , monepantel lacked activity in S . ratti-infected rats , a result in line with a recent investigation , which revealed that S . ratti third-stage larvae were not affected by monepantel after 72 h of incubation [22] . For comparison , a complete elimination of adult worms was achieved with ivermectin ( 0 . 5 mg/kg ) in S . ratti-infected rats [32] . Strongyloides ratti has a remote homolog of DES-2 and ACR-23/MPTL-1 only , which is not targeted by monepantel [22] . Finally , although only one high dosage was tested , our data indicate that A . suum is not affected by treatment with monepantel in vivo , whereas albendazole reduced the worm burden of A . suum in mice at the same dose . Like H . contortus , A . ceylanicum and N . americanus are members of the nematode clade V , whereas S . ratti belongs to clade IV , A . suum , to clade III , and T . muris to clade I [37] . One could hypothesize that only clade V species exhibit sensitivity to monepantel , whereas those that diverged from this lineage of the evolutionary tree earlier ( clades I to IV ) might not have evolved homologous receptors . As available for A . suum [38] , further genome sequencing of A . ceylanicum , N . americanus and Trichuris spp . remains to be performed in order to extend current knowledge about evolutionary and functional relationships of receptors involved in sensitivity to monepantel . In the present investigation , albendazole , levamisole , and pyrantel pamoate have been extensively studied in vitro and in vivo . The results obtained are in agreement with earlier in vivo [29] , [39]–[41] and in vitro [41] work using A . ceylanicum and N . americanus . In addition , to our knowledge , the in vitro and in vivo sensitivities of these three drugs against T . muris are presented for the first time . In line with human efficacy data [10] , albendazole showed highly potent activity against A . ceylanicum , N . americanus and A . suum , yet much less pronounced activity against T . muris in vivo . A similar trend was observed for pyrantel pamoate , which achieved a moderate effect against A . ceylanicum but lacked activity in T . muris-infected mice . These results on pyrantel pamoate are compatible with cure rates reported in clinical trials [10] . On the other hand , levamisole was highly efficacious in our ancylostomiasis and trichuriasis rodent models , while low to moderate cure rates have been recently reported in humans [10] , [42] . Interestingly , contradictory results were obtained with albendazole , levamisole , and pyrantel pamoate against adult A . ceylanicum in vitro and in vivo . In addition , albendazole showed excellent activity in the N . americanus hamster model but lacked activity in vitro . This finding might be partially explained by the presence of active metabolites , since for example albendazole and levamisole are rapidly metabolized in vivo [43]–[45] . In addition , large differences in sensitivity between larval and adult hookworm stages were observed with levamisole ( and albendazole for A . ceylanicum ) . It is commonly accepted that the benzimidazoles tend to be lethal to developing stages but not always to adult worms . Developing cells are obviously more harmed by the benzimidazoles , as the utilization of tubulin in the mitotic cycles is affected [46] . In conclusion , to our knowledge , we have for the first time analyzed the efficacy of monepantel in animal models corresponding to human intestinal helminthiases . A recently developed target product profile suggested that a drug development candidate for the treatment of infections with STH should ideally target all stages ( at least adult and ova ) and species of the major geohelminths such as Ascaris , Trichuris , both hookworm species and Enterobius [36] . Hence , based on our results , established in nematode-rodent models , monepantel does not fulfill the required minimal product characteristics for a new intestinal anthelmintic .
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Soil-transmitted helminthiases affect more than one billion people among the most vulnerable populations in developing countries . Currently , control of these infections primarily relies on chemotherapy . Only five drugs are available , all of which have been in use for decades . None of the drugs are efficacious using single doses against all soil-transmitted helminths ( STH ) species and show low efficacy observed against Trichuris trichiura . In addition , the limited availability of current drug treatments poses a precarious situation should drug resistance occur . Therefore , there is great interest to develop novel drugs against infections with STH . Monepantel , which belongs to a new class of veterinary anthelmintics , the amino-acetonitrile derivatives , might be a potential drug candidate in humans . It has been extensively tested against livestock nematodes , and was found highly efficacious and safe for animals . Here we describe the in vitro and in vivo effect of monepantel , on Ancylostoma ceylanicum , Necator americanus , Trichuris muris , Strongyloides ratti , and Ascaris suum , five parasite-rodent models of relevance to human STH . Since we observed that monepantel showed only high activity on one of the hookworm species and lacked activity on the other parasites tested we cannot recommend the drug as a development candidate for human soil-transmitted helminthiases .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"soil-transmitted",
"helminths",
"trichuriasis",
"hookworm",
"infection",
"parasitic",
"diseases",
"helminth",
"infection"
] |
2011
|
In Vitro and In Vivo Efficacy of Monepantel (AAD 1566) against Laboratory Models of Human Intestinal Nematode Infections
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Sexual dimorphisms in trait expression are widespread among animals and are especially pronounced in ornaments and weapons of sexual selection , which can attain exaggerated sizes . Expression of exaggerated traits is usually male-specific and nutrition sensitive . Consequently , the developmental mechanisms generating sexually dimorphic growth and nutrition-dependent phenotypic plasticity are each likely to regulate the expression of extreme structures . Yet we know little about how either of these mechanisms work , much less how they might interact with each other . We investigated the developmental mechanisms of sex-specific mandible growth in the stag beetle Cyclommatus metallifer , focusing on doublesex gene function and its interaction with juvenile hormone ( JH ) signaling . doublesex genes encode transcription factors that orchestrate male and female specific trait development , and JH acts as a mediator between nutrition and mandible growth . We found that the Cmdsx gene regulates sex differentiation in the stag beetle . Knockdown of Cmdsx by RNA-interference in both males and females produced intersex phenotypes , indicating a role for Cmdsx in sex-specific trait growth . By combining knockdown of Cmdsx with JH treatment , we showed that female-specific splice variants of Cmdsx contribute to the insensitivity of female mandibles to JH: knockdown of Cmdsx reversed this pattern , so that mandibles in knockdown females were stimulated to grow by JH treatment . In contrast , mandibles in knockdown males retained some sensitivity to JH , though mandibles in these individuals did not attain the full sizes of wild type males . We suggest that moderate JH sensitivity of mandibular cells may be the default developmental state for both sexes , with sex-specific Dsx protein decreasing sensitivity in females , and increasing it in males . This study is the first to demonstrate a causal link between the sex determination and JH signaling pathways , which clearly interact to determine the developmental fates and final sizes of nutrition-dependent secondary-sexual characters .
The evolution of sex-specific traits in animals has long fascinated biologists . How is growth regulated so that it differs dramatically between males and females ? Sexual dimorphisms are widespread across diverse animal taxa and include exaggerated sexually selected traits like the antlers of deer , the enormous clawed chelae of crabs , and the elaborate trains of peacocks [1] , [2] , [3] . Some of the most striking sexually dimorphic traits are found within insects , such as the horns of rhinoceros beetles and the large mandibles of male stag beetles [3] , [4] , [5] . Sex-specific exaggerated traits often develop in a condition-dependent manner , so that not all individuals produce the trait even in the same sex [6] , [7] , [8] , [9] , [10] . Virtually all of the most extreme ornaments and weapons are also conditionally-expressed; they are exquisitely phenotypically plastic structures , whose growth depends on larval/juvenile access to nutrition [3] , [5] , [9] , [11] , [12] . Consequently , developmental mechanisms generating sex-specific trait growth and nutrition-dependent phenotypic plasticity are each likely to regulate the expression of extreme structures of sexual selection . The near universality of sex differences in the nutrition sensitivity of these traits suggests that common developmental mechanisms may be involved . Yet we still know almost nothing about how the processes of sex-specific growth and nutrition-sensitivity interact with each other to generate sexual dimorphism . Recent studies in model organisms such as the fruit fly , nematode , medaka fish , and mouse , implicate a group of highly conserved proteins known as DM , or DNA binding motif proteins , as major effectors of sexual differentiation ( recently reviewed in [13] and [14] . The fruit fly DM domain gene Doublesex ( dsx ) is conserved in structure and function in all insect species where it has been examined [2] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] . The dsx gene is transcribed in both sexes , but then differentially spliced to produce a male-specific or a female-specific mRNA ( for review see [13] ) . These alternatively-spliced sex-specific transcripts code for a male ( DsxM ) or a female-specific ( DsxF ) protein [13] . Both types of Dsx proteins contain a zinc finger-like DNA binding domain called the DM domain [23] , and act as transcriptional regulators responsible for sexual differentiation of tissues during development [1] , [2] , [24] , [25] . For these reasons , dsx is a promising candidate for the regulation of sexual dimorphisms in the weapons of beetles . Indeed , recent published papers on dsx function in dung beetles ( Onthophagus taurus and O . sagittarius ) and rhinoceros beetles demonstrate a functional role for dsx in sex-specific growth of horns [20] , [22] , [26] . In stag beetles , many species show strong sexual dimorphism in the size of their mandibles [5] , [27] , [28] , [29] , [30] , [31] , [32] . Males that have access to unlimited amounts of food as larvae develop disproportionately larger mandibles than males with restricted access to food , but more importantly , female mandibles never proliferate to the extent of even poorly-fed , small males ( Fig . 1 ) [5] . Gotoh et al . recently found that nutrition-dependent mandibular growth in stag beetles is mediated by juvenile hormone ( JH ) in a sex-specific fashion [5] . JH titers were positively correlated with individual nutritional condition , and , in males , high JH titers promoted the growth of mandibles . In contrast , although females had similar levels of JH to males , female mandibles did not respond to high JH . Also , JH treatment did not affect to the growth of mandibles in females . These results indicate a sex-specific response of these traits to nutritional condition via JH [5] . However , other than this intriguing result , the mechanisms underlying developmental links between sex-determination , endocrine signaling , and sex-specific trait growth have yet to be characterized for any insects with exaggerated sexual dimorphism in insects . Here , we investigated the developmental mechanisms of sex-specific mandible growth in the stag beetle Cyclommatus metallifer , focusing on dsx gene function and its interaction with JH signaling . This species was used in previous studies on mandible development [5] , [33] and we have recently constructed a transcriptome database for this species ( Gotoh et al . in prep ) . To characterize dsx in Cyclommatus metallifer , the full length C . metallifer dsx ( hereafter Cmdsx ) transcript was obtained by degenerate PCR and subsequent Rapid Amplification of cDNA Ends PCR ( RACE-PCR ) . Expression analyses of Cmdsx were carried out by Reverse Transcription PCR ( RT-PCR ) and real-time quantitative PCR ( qPCR ) to reveal the spatio-temporal expression pattern and sex-specificity of the Cmdsx transcripts during the prepupal period , which is known to be the critical period when mandibular tissues proliferate to their final adult size ( Fig . 2 ) [5] . The function of dsx during sex-specific morphogenesis was investigated by gene knockdown using RNA interference ( RNAi ) against the Cmdsx transcripts . In addition to this , to investigate the putative interaction between dsx and endocrine ( JH ) signaling during mandibular growth , we ectopically applied JH analog to dsxRNAi individuals .
The full-length Cmdsx transcript was obtained by degenerate PCR and subsequent RACE-PCR ( Fig . 3A ) . Four distinct splice variants ( A , B , C and D isoforms ) were identified , which contain the highly conserved DM domain and encode protein sequences with high sequence similarity to known insect Dsx proteins ( Fig . S1 , [34] ) . Protein sequence similarity of the stag beetle isoforms with that of the recently reported doublesex gene of Onthophagus taurus ( Scarabaeidae , Coleoptera; [20] ) , and RT-PCR expression analyses show that CmdsxA and CmdsxB are male-specific , while isoforms CmdsxC and CmdsxD are female-specific ( Fig . 3B ) . There are several differences in structure among the four splice variants of the Cmdsx transcript . First , a large exon ( exon 4 ) containing primarily noncoding sequence and showing no similarity to dsx exons in any other insects , only occurs in splice variant A ( Fig . 3A ) . In addition , CmdsxA contains neither exon 8 nor exon 9 ( found in variants B , C , and D ) . Cmdsx variants C and D are similar to each other overall , with the exception of exon 6 which is only found in CmdsxC ( Fig . 3A ) . An important difference between the predicted isoforms is the absence of 14 amino acid residues at the 3′-end of the conserved dsx dimer domain in the A and B isoforms ( Fig . S1 ) ; this difference in the dsx dimer domain was also reported in the doublesex gene of Onthophagus taurus [20] . CmDsxB and the male-specific Dsx isoform of O . taurus ( OtDsxM ) also share a 25 amino acid sequence at their 3′ end ( Fig . S1 ) . Also CmDsxC and CmDsxD had similar 3′ end sequences to the female-specific Dsx isoforms of O . taurus ( OtDsxF1 and OtDsxF2 ) , respectively ( Fig . S1 ) . Expression patterns of exons of the Cmdsx transcript were examined in developing mandibles of both sexes in detail by real-time qRT-PCR during different stages of prepupal development ( Fig . 3C ) Tissue-specific expression and nutrition-dependent expression were examined by measuring the expression level of exon 1 , which represents the total Cmdsx isoform expression since it is shared by all splice variants . Also , expression patterns of exons 4 , 6 , 8 and 9 were examined in order to characterize the sex-specific usage of these exons . Mandibles are sexually dimorphic ( e . g . males have disproportionately large mandibles , Fig . 1B ) and were expected to show high Cmdsx expression . Maxillae , on the other hand , are not dramatically different in the two sexes ( e . g . maxillae show isometric allometry in both sexes , Fig . 1C ) and we expected lower levels of expression of Cmdsx . As predicted , expression of exon 1 was higher in mandibles than in maxillae in both males and females , especially during prepupal Stages 1 and 2 ( Fig . 3C ) . Exon 1 was expressed at its highest level in male mandibles during prepupal Stage 2 , but peaked later during ( Stage 3 ) in female mandibles ( Fig . 3C ) . No differences in expression of exon 1 were detected in Stage 4 of prepupal development in either trait ( Fig . 3C ) . Large and small males have different nutritional histories and undergo different amounts of mandible growth . However , expression levels of Exon 1 were similar for large and small males , during Stages 1 , 3 and 4 in both mandibles and maxillae ( Fig . 3C ) . Only during Stage 2 were there significant differences in expression of Exon 1 ( Fig . 3C ) . Sex-specificity of each exon was examined during Stages 2 and 3 , when total Cmdsx expression reached its peak in males and females ( Fig . 3C ) . Expression levels of Exon 4 were five times higher in males than females during Stage 2 ( Fig . 3C ) and only low levels of expression of this exon were found in both males and females during Stage 3 ( Fig . 3C ) . The female-specific exon 8 was more highly expressed in females during both stages 2 and 3 but especially during Stage 3 ( Fig . 3C ) . Exon 6 and exon 9 were expressed similarly in both males and females during Stage 2 , but showed increased expression in females during Stage 3 ( Fig . 3C ) . The increase of expression of exons 6 and 9 in Stage 3 females is expected to correspond to an overall expression peak of all dsx isoforms in females during Stage 3 ( Fig . 3A ) Injections of Cmdsx dsRNA reduced Cmdsx transcript abundances by 13–84% in prepupal mandibles , compared with control injections of GFP dsRNA ( Fig . S2 ) . The region of the Cmdsx transcript that was targeted extended from exon 1 to exon 3 , and was therefore predicted to knockdown all four of the expressed transcripts of Cmdsx in both sexes ( Fig . 3A ) . Knockdown of the Cmdsx gene by RNAi during prepupal development confirmed a significant functional role in the regulation of sex-specific mandible growth in stag beetles . The phenotype of dsxRNAi females was changed to be more male-like in body color , mandible size , foreleg tibial spine number , and genital shape and genital size ( Fig . 4A , B , C , D ) . Significant mandible growth was induced in dsxRNAi females compared with GFPRNAi females ( t = 4 . 509 , P = 0 . 000357 , Fig . 4B ) . In contrast , in dsxRNAi males , mandible growth was dramatically and significantly suppressed ( Fig . 4E , F ) , resulting in more female-like forms . The relationships of body size and mandible size are significantly different between GFPRNAi and dsxRNAi males ( F = 19 . 072 , P = 0 . 0002982 ) . In the range of the observed body size , dsxRNAi males possessed smaller mandibles , and the mandible-size difference became larger as body size increases ( Fig . 4F ) . The intersex phenotypes resulting from the dsxRNAi knockdown extended to the body color of females , transforming them from the black color typical of females to a metallic copper typical of males ( Fig . 4A ) . The number of spines on the tibia also changed . Females typically develop with four or five tibial spines ( and males with zero ) . However , in dsxRNAi females this number decreased from four to fewer ( becoming more male-like ) , and in dsxRNAi males the number of spines increased from zero to four ( more female-like ) ( Fig . 4C , G ) . Finally , the size and length of the genitalia changed in sex-inappropriate directions in both dsxRNAi females and dsxRNAi males ( Fig . 4D , H ) . We have previously shown that JH titer during the prepupal period is correlated with adult male body size and mandible size in the stag beetle , and that ectopic application of JH to the prepupal male induces male mandible proliferation [5] . At least part of the exquisite condition-sensitivity of extreme mandible growth appears to involve sensitivity of mandibular tissues to circulating JH . However , we have also shown that mandibular tissues of females do not respond to JH in the same way as males . Mandibles in females did not respond to ectopic JH , despite the fact that females had similar levels of circulating JH to males during this developmental period [5] . This suggests that female mandibular tissues may be insensitive to JH signaling . We predicted that sex-differences in tissue sensitivity to JH could be caused by action of the sex-determination cascade , specifically by expression of alternative splice variants of Cmdsx . To test for a functional role of Cmdsx in causing sex differences in the sensitivity of mandibular cells to JH , we applied a JH analog ( JHA ) to RNAi ( GFP or dsx ) treated males and females ( Fig . 5 ) . In control ( GFPRNAi ) females , JHA application did not induce mandible growth ( t = −0 . 611 , P = 0 . 5549390199 , Fig . 5 ) , which corroborates our previously reported result that JHA application does not affect mandibular growth in wild-type females [5] . In contrast , JHA application to dsxRNAi females induced significant growth of mandibles compared with acetone application to dsxRNAi females ( t = 2 . 254 , P = 0 . 0429177662 , Fig . 5 ) . Thus , knockdown of Cmdsx caused mandibles of females to behave like those of males . Their growth became sensitive to JH , and therefore should also have become condition-dependent . In control ( GFPRNAi ) males , JHA application induced significant mandible growth ( t = 5 . 5500 , P = 0 . 0004876470 , Fig . 5 ) , corroborating our earlier report that JHA application promotes mandibular growth in wild-type males [5] . For dsxRNAi males , JHA application rescued the defective mandibular phenotype by promoting mandibular growth ( ANCOVA , t = 4 . 918 , P = 0 . 0003321826 , Fig . 5 ) , however , the effect of JHA application tended to be decreased in dsxRNAi individuals . We suspect that here , too , the result was to make mandibles in males behave more like those of females . That is , growth of mandibles in knockdown males might be less sensitive to JH than it otherwise would have been .
Spatiotemporal patterns of expression and functional analyses of Cmdsx support the hypothesis that sex-specific growth of exaggerated mandibles in stag beetles is controlled by doublesex . The differences in the 3′ end between male- and female-specific CmDsx are predicted to have important consequences for DNA binding . In Drosophila , it is known that this domain enhances DNA recognition by promoting dimerization of Dsx [35] . Thus , this difference of domain structure in CmDsx suggests differential DNA-binding ability of the predicted male and female proteins . In addition to the differences between sex-specific isoforms , all four isoforms differ from each other in their amino-acid sequence at the 3′ end , raising the possibility that each isoform is deployed differentially in space and time in a sex- and tissue-specific manner . Expression analyses in other body parts and isoform-specific knockdown experiments will be required to confirm this possibility . Examination of Cmdsx expression in the sexually dimorphic mandibles compared to the sexually monomorphic maxillae revealed that there are differences in expression in a developmental and tissue specific pattern ( Fig . 3C ) . Recent work in Drosophila showed that dsx expression was temporally and spatially restricted to body parts showing sexual dimorphism [36] , [37] . In stag beetle mandibles , female-specific Cmdsx transcripts showed their highest levels of expression at the exact stage ( Stage 3 of prepupal development ) when mandibular cells proliferate maximally in males [5] . Thus , female specific Cmdsx expression coincides precisely with inhibition of mandibular cellular proliferation ( Fig . 3C ) . Expression of male-specific Cmdsx transcripts in mandibles peaked just before this stage , during a period ( prepupal Stage 2 ) when cells in male mandibles are especially sensitive to the growth-promoting effects of JH [5] . Both of these sex- and trait-specific patterns of expression are consistent with isoform-specific regulatory roles for Cmdsx during mandible growth . Considering the results of Cmdsx knockdown , we suggest that male-specific Cmdsx transcripts may promote mandible growth , and female-specific transcripts inhibit mandible growth , in part by enhancing or repressing the sensitivity of mandibular cells to JH . Our results demonstrate , for the first time in any insect , a functional link between Dsx expression and JH signaling . Knockdown animals had significantly altered responses to topical JHA application , compared with control animals ( Fig . 5 ) . In females , knockdown of Cmdsx caused mandibles to be sensitive to JHA , where they otherwise would not have been , suggesting that normal expression of female-specific isoforms of CmDsx contributes to insensitivity of female mandibles to JH . Because JH acts to stimulate cell proliferation during this developmental stage , such a mechanism would repress excessive growth of this structure in females . In males , knockdown of Cmdsx combined with topical application of JHA stimulated some mandible growth , but not as much as in control animals with application of JHA . This indicates that male mandibles retained some sensitivity to JH even in their lowered expression of Cmdsx . We suggest that some sensitivity of mandibular cells to JH is the default developmental state for these animals . In normal males , male-specific CmDsx isoforms may increase the sensitivity of mandibular cells to JH , contributing to rapid and disproportionate growth of these exaggerated structures . In this case , knockdown of Cmdsx would remove this extra-sensitivity , restoring mandibular cells to their default state and producing males with large , but not extreme , mandible sizes . Another possibility is that dsx and JH act in parallel to regulate mandible growth in males . If this were the case , then Cmdsx and JH would act independently to stimulate exaggerated growth of male mandibles , and their effects would simply be additive . Thus , crosstalk between dsx and JH in males will need to be investigated in future studies . Although there have been many previous reports of sex-specific JH actions on secondary-sexual characters in various insect lineages [38] , [39] , [40] , [41] , this study is the first to demonstrate a causal link between the JH signaling pathway and the sex determination pathway , which clearly interact to determine the developmental fates of secondary-sexual characters . A recent study on dsx regulation of sexual dimorphism has also been reported for horned beetles ( Onthophagus taurus ) [20] . In this study , critical roles of dsx in sex differentiation , including development of sex-specific exaggerated traits , were shown . Horns in O . taurus are dimorphic in two ways: females do not produce horns ( sexual dimorphism ) , and males smaller than a threshold body size produce only rudimentary horns ( male dimorphism ) . Kijimoto et al showed that only large males expressed the male specific isoform of Otdsx ( OtdsxM ) ; small males did not [20] . Because body size and horn morphology depend critically on nutrition in this species , the findings of Kijimoto et al raise the possibility that levels of expression of OtdsxM may be sensitive to nutrition , as well as sex [20] . This contrasts with C . metallifer , where horns do not exhibit male dimorphism ( all males produce enlarged mandibles ) and where we find at best minimal evidence of nutrition-dependent expression of dsx ( based on comparisons between large and small males ) . Expression of Cmdsx in mandibles of large males was at most 1 . 3 times that of mandibles in small males ( during Stage 2; Fig . 3C ) , which is much smaller than the differences observed for Onthophagus ( large males showed approximately 3 times higher expression of OtdsxM than small males ) . Based on these results we suggest that endocrine pathways sensitive to nutrition may interact with the sex determination pathway both upstream [20] and downstream ( our study ) of dsx . The inability of JHA treatment of dsxRNAi males to induce full growth of mandibles may indicate the action of other regulatory pathways for mandible growth . One likely candidate is the insulin-signaling pathway , because this pathway is known to regulate body and organ size in insects in accordance with nutritional conditions [42] , [43] , [44] . Growing horns in male rhinoceros beetles ( Trypoxylus dichotomus ) are known to be more sensitive to insulin signals than other metric traits ( e . g . , wings , genitalia ) [3] , and Emlen et al . reported sex- and morph- ( major vs minor male ) specific expression of the insulin receptor ( InR ) in growing horns of the dung beetle ( Onthophagus nigriventris ) [10] . It is likely that the enlarged mandibles of male stag beetles will also be sensitive to insulin signaling during their period of growth , and we suspect that Cmdsx may contribute to sex differences in sensitivity to these signals as well ( Fig . 6 ) . Future studies such as expression analyses of InR and insulin-like peptides will be needed to examine these additional mechanisms , but already it is clear that a rich interplay between endocrine and sex-determination pathways coordinates the growth of exaggerated sexually-selected and sexually-dimorphic characters .
Stag beetle adults ( Cyclommatus metallifer ) were purchased from Hercules-Hercules , Sapporo , Japan . Detail rearing and breeding methods are described in the Supporting Information ( Text S1 ) . We defined four developmental stages during the prepupal period based on specific developmental landmarks ( Fig . 2 ) . First , the stag beetle final instar larva constructs a pupal cell prior to pupation which marks the border between the end of the larval stage and the onset of the prepupal stage . After pupal cell construction ( PCC ) , the larva undergoes a two-stage gut purge ( GP ) in which all gut contents are egested from the body . It takes two days from the onset of PCC to the start of the first GP , which is termed ‘Stage 1’ ( Fig . 2 ) . The period of time that the first GP continues lasts about 3–4 days and is ‘Stage 2’ ( Fig . 2 ) . Overall body weight gradually decreases during stage 2 ( Fig . 2 ) . After the first GP is over , the individual remains in a suspended state for 3–5 days during which time the adult structures are proliferating and growing ( Stage 3 ) . Stage 4 is a very brief period which corresponds just a few hours prior to pupation when the individual purges all of its remaining gut contents for the second GP and completes metamorphosis into the pupal stage . Partial transcript sequences of the C . metallifer orthologs for dsx were cloned by degenerate PCR . Three additional transcripts for C . metallifer reference genes for real time qPCR were also cloned by degenerate PCR – glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) , elongation factor 1 alpha ( EF-1a ) and ribosomal protein L32 ( rpl32 ) . Primer sequences for degenerate PCR are listed in Table S1 . Data base searches for homologies were performed using BlastX at the NCBI server ( http://blast . ncbi . nlm . nih . gov/Blast . cgi ) . To further confirm the orthologues , we made multiple alignments of dsx genes including the orthologues from the other insect species , and constructed neighbor-joining trees of protein sequences ( for Cmdsx ) or mRNA sequences ( for GAPDH , EF-1a and rpl32 ) using ClustalX program [45] ( http://www . clustal . org/ ) ( Fig . S3 , S4 , S5 ) . Confidence was estimated with 1000bootstraps . Detailed cloning procedures are described in the Supporting Information ( Text S1 ) . Rapid amplification of cDNA ends ( RACE ) -PCR was performed to obtain the full length C . metallifer dsx transcript sequence using the following RACE primers ( for 5′-RACE: 5′- CCT GAA CAC GTC GGG AAA AGA CGG CG-3′ , for 3′-RACE: CTC GAA GAT TGC CAT AAG CTC CTG GAA AGG-3′ ) and the SMART RACE cDNA Amplification Kit ( Clontech , Palp Alto , CA ) . The amplified cDNA fragments were subcloned and sequenced as described before . The protein domains were predicted by using CDD ( conserved domain database ) on NCBI ( http://www . ncbi . nlm . nih . gov/Structure/cdd/wrpsb . cgi ) . The expression patterns of Cmdsx transcripts in small and large male and female prepupae were examined during the period of maximal mouthpart growth with RT-PCR and real-time qPCR . Briefly , individuals were reared under high versus low nutrition conditions that result in small versus large prepupae; details for this can be found in our previous study [5] . See Supporting Information ( Text S1 and Table S2 ) for a detailed description of our methods for RT-PCR and real-time qPCR and primer sequences for real-time PCR . Functional analysis of the stag beetle dsx was accomplished by knockdown of the dsx transcript by RNA interference ( RNAi ) during prepupal development . To silence all Cmdsx transcripts , double-stranded RNA ( dsRNA ) against a 352 bp region of Cmdsx common to all four splice variants ( Fig . 3A ) was synthesized . Detailed procedures for dsRNA synthesis are described in the Supporting Information ( Text S1 ) . All dsRNA was diluted with 1×PBS . One µg of dsRNA in 5 µl of PBS was injected into the dorsal prothorax of late 3rd instar larvae using a microliter syringe ( Hamilton , Reno , NV ) under a stereomicroscope . This stage is just prior to the prepupal period and prior to adult mandibular cellular proliferation , so the effect of RNAi was targeted to pupal development ( Fig . 2 ) . Individuals that successfully eclosed into adults were used for analyses; these included 7 GFPRNAi females , 12 dsxRNAi females , 8 GFPRNAi males , and 16 dsxRNAi males . For statistical test of Cmdsx RNAi effect , analysis of covariance ( ANCOVA ) was performed with body size as a covariate using R 3 . 0 . 1 software [46] . The equality of the slopes of regression lines was tested and no significant interaction was detected in female samples ( F = 0 . 2779 , P = 0 . 6058 ) . In male samples , the slopes were significantly different between GFPRNAi and dsxRNAi samples ( F = 19 . 072 , P = 0 . 0002982 ) . RNAi efficiency was also examined by measurement of Cmdsx expression levels using real-time qPCR in the prepupal mandibles of males and females injected with dsRNA against GFP ( control ) or Cmdsx . Primers for real-time qPCR were designed to the common region shared by all isoforms ( forward primer: 5′-TTC CGC TCT CAT TCA TAA ACGA-3′ , reverse primer: 5′-TGC GGA AAA CGG CAA AGT-3′ ) . To prevent overestimation of transcripts by detecting injected dsRNA , we designed the primers to amplify a region that had no overlap with the region used in dsRNA synthesis . To investigate the effects of Cmdsx on JH action , we combined a Cmdsx knockdown experiment with ectopic application of the JH analog ( JHA ) . According to previous study [5] , we used fenoxycarb for JHA application . First , we injected dsRNA against GFP or Cmdsx into the dorsal thorax of late 3rd instar C . metallifer larvae as described above . Then , when the knockdown experimental prepupae reached stage 2 , five µg of the JH analog fenoxycarb diluted in 10 µl of acetone ( Wako ) was applied to the dorsal thorax according to previous study [5] . The control groups were dsRNA-injected pupae treated with acetone only . Pupal weight and pupal ( in males ) or adult ( in females ) mandible length were recorded . Sample sizes of surviving animals with normal , measurable traits are described in Table S3 . To estimate the effect of JHA application on relative mandible size for each of the four RNAi categories ( GFPRNAi males , dsxRNAi males , GFPRNAi females , dsxRNAi females ) , analysis of covariance ( ANCOVA ) was performed with body size as a covariate using R 3 . 0 . 1 software [46] . The equality of the slopes of the regression lines was tested and no significant interaction was detected in all the four RNAi categories ( F = 0 . 6789 , P = 0 . 4313 in GFPRNAi males; F = 2 . 9354 , P = 0 . 1029 in dsxRNAi males; F = 2 . 4669 , P = 0 . 1507 in GFPRNAi females , F = 0 . 6751 , P = 0 . 4185 in dsxRNAi females ) . Statistical significance of JHA application effects was adjusted for multiple comparisons by using Benjamini & Hochberg method [47] .
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Sexual dimorphisms such as the exaggerated antlers of deer , the enormous clawed chelae of crabs , and the horns and mandibles of beetles , are widespread across animal taxa and have fascinated biologists for centuries . Much recent work has uncovered the importance of the role of the sex-determination pathway in the expression of sexually dimorphic traits . However , critical interactions between this pathway and other growth regulatory mechanisms – for example , the physiological mechanisms involved in nutrition-dependent expression of these traits – are less well understood . In this study , we provide evidence of a developmental link between nutrition-sensitivity and sexual differentiation in the giant mandibles of the sexually dimorphic stag beetle , Cyclommatus metallifer . We examined the regulation and function of a key sex determination gene in animals , doublesex ( dsx ) , and its interaction with juvenile hormone ( JH ) , an important insect hormone known to regulate insect polyphenisms including the regulation of the disproportionate growth of male stag beetle mandibles . We found that Cmdsx changes mandibular responsiveness to JH in a sex-specific pattern . Based on these results , we hypothesize that sex-specific regulation of JH responsiveness is a developmental link between nutrition and sexual differentiation in stag beetles .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"genetics",
"biology",
"evolutionary",
"biology",
"zoology"
] |
2014
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Developmental Link between Sex and Nutrition; doublesex Regulates Sex-Specific Mandible Growth via Juvenile Hormone Signaling in Stag Beetles
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During evolution , herpesviruses have developed numerous , and often very ingenious , strategies to counteract efficient host immunity . Specifically , Kaposi's sarcoma-associated herpesvirus ( KSHV ) eludes host immunity by undergoing a dormant stage , called latency wherein it expresses a minimal number of viral proteins to evade host immune activation . Here , we show that during latency , KSHV hijacks the complement pathway to promote cell survival . We detected strong deposition of complement membrane attack complex C5b-9 and the complement component C3 activated product C3b on Kaposi's sarcoma spindle tumor cells , and on human endothelial cells latently infected by KSHV , TIME-KSHV and TIVE-LTC , but not on their respective uninfected control cells , TIME and TIVE . We further showed that complement activation in latently KSHV-infected cells was mediated by the alternative complement pathway through down-regulation of cell surface complement regulatory proteins CD55 and CD59 . Interestingly , complement activation caused minimal cell death but promoted the survival of latently KSHV-infected cells grown in medium depleted of growth factors . We found that complement activation increased STAT3 tyrosine phosphorylation ( Y705 ) of KSHV-infected cells , which was required for the enhanced cell survival . Furthermore , overexpression of either CD55 or CD59 in latently KSHV-infected cells was sufficient to inhibit complement activation , prevent STAT3 Y705 phosphorylation and abolish the enhanced survival of cells cultured in growth factor-depleted condition . Together , these results demonstrate a novel mechanism by which an oncogenic virus subverts and exploits the host innate immune system to promote viral persistent infection .
Kaposi's sarcoma-associated herpesvirus ( KSHV ) , also known as human herpesvirus 8 ( HHV8 ) , is a DNA tumor virus associated with the development of Kaposi's sarcoma ( KS ) , primary effusion lymphoma ( PEL ) , and a subset of multicentric Castleman's disease [1]–[3] . KS is a vascular tumor of proliferative endothelial cells displaying vast inflammation and uncontrolled angiogenesis while PEL and MCD are lymphoproliferative diseases of B-cells [4] , [5] . The life cycle of KSHV consists of latency and lytic replication phases [6] . Following acute infection , KSHV establishes latency in the immunocompetent hosts . During latency , KSHV replicates in the episome form expressing only a limited number of viral latent proteins . As a result , KSHV latency is an effective strategy for evading host immune surveillance and maintaining persistent infection [6] , [7] . In contrast , during lytic replication , KSHV replicates as a linear genome expressing cascades of viral proteins and producing infectious virions , which are exposed to host immune surveillance [6] , [7] . In KSHV-related tumors , KSHV sustains a persistent infection with most tumor cells in latency and a small number of them undergoing lytic replication [5] . Therefore , KSHV latency is paramount to persistent infection in hosts with and without pathological manifestations . KSHV maintains latency by evolving effective mechanisms for episome persistence , silencing expression of viral lytic genes , and promotion of survival and proliferation of infected cells [6] . A number of cellular signaling pathways including NF-κB , β-catenin , PI3K/AKT , c-Myc and ERK MAPK pathways are implicated in the growth and survival of latently KSHV-infected cells [8]–[13] . The STAT3 pathway , which can be activated by both KSHV-encoded IL-6 ( vIL-6 ) and cellular IL-6 , is essential for the survival of PEL cells [14] , [15] . Although it is activated without involving vIL-6 and IL-6 , the role of STAT3 pathway in the survival of latently KSHV-infected endothelial cells remains unclear [16] . The complement system consisting of over sixty components and activation fragments is a major arm of the innate immune system and plays important roles in stimulating inflammatory reactions , opsonization , complement-mediated cell killing , and induction of humoral and cell-mediated immune responses [17]–[20] . There are three distinct complement pathways including classical , lectin and alternative complement pathways . The classical complement pathway is activated by immune complexes involving the interaction of a minimum of two globular regions of C1q with the CH2 domains of an IgG duplex or a single IgM molecule [20] , [21] . Thus , C1q is required for the activation of this pathway . The lectin pathway is initiated by binding of mannose-binding lectin to carbohydrate groups on the surface of bacterial cells [20] , [21] . Unlike other complement pathways , the alternative complement pathway is spontaneously and constantly activated by the C3 complement protein , which itself is the recognition molecule [20] , [21] . Tiny amounts of C3 are spontaneously hydrolyzed to C3 ( H2O ) generating C3 convertase ( C3bBb ) with factor B and factor D [21] . Activation of the classical and lectin pathways , on the other hand , generates C4bC2a convertase , which is composed of C4b and C2a . Both C3bBb and C4bC2a convertases cleave C3 to C3a and C3b , also involving factor B and factor D [20] , [21] . Addition of C3b to C3bBb and C4bC2a leads to the generation of C5 convertases C3bBbC3b and C4bC2aC3b , respectively , which cleave C5 to C5a and C5b [20] , [21] . This initiates the terminal pathway , which leads to the formation of terminal complement complex , also known as MAC or C5b-9 complex consisting of C5b , C6 , C7 , C8 and C9 [20] , [21] . Under normal conditions , complement regulatory proteins , which include soluble proteins and membrane-associated proteins , inhibit the activation of complement to protect cells from complement attack [20]–[22] . Soluble proteins include factor H and its related proteins and variants , and factor I while membrane-associated proteins include CD35 , CD46 , CD55 , and CD59 [20]–[22] . In particular , factor H together with factor I bind to and cleave C3b in the alternative complement pathway , effectively preventing its further activation [20] , [21] , [23] . The membrane-associated protein CD55 primarily binds to C3b to prevent the activation of the complement pathway while CD59 binds to C5b-8 to prevent the formation of the C5b-9 complex [20] , [21] . Blood-contacting cells such as red blood cells , white blood cells , and endothelial cells express high levels of complement regulatory proteins on their surfaces . If complement regulatory proteins are downregulated , the complement system can be activated [18] , [24]–[26] . During complement activation , C3 , C5 and their activation products in addition to the C5b-9 complex bind to cell surface receptors to trigger diverse biological effects including induction of inflammation , and cell growth and survival if the complexes are present at sublytic concentrations [18] , [21] , [27] , [28] . Killing of target cells and pathogens upon activation is primarily mediated by the end product of the complement system , the C5b-9 complex , which forms transmembrane channels on the target cells [18] , [19] . These channels disrupt the phospholipid bilayer of target cells , leading to cell lysis and death . Nucleated cells are more resistant to complement than erythrocytes or prokaryotes [20] , [21] , [29] . Killing of nucleated cells is a multi-hit process and requires formation of multiple channels on the cell membrane [20] , [21] , [29] . When formation of MAC on the cell surface is unable to lyse the target cells , MAC can trigger other biological effects [18] , [29]–[33] . As a result , deregulation of the complement system has been linked to diverse pathological processes including oncogenic signal transduction associated with neoplastic progression , activation of cell cycle , enhanced angiogenesis , and resistance to apoptosis [18] , [34] , [35] . In this study , we have unexpectedly discovered that KSHV activates the complement system during latency . Interestingly , most of the latently KSHV-infected cells are resistant to complement-mediated cell killing . Furthermore , complement activation promotes cell survival of KSHV-infected cells cultured in medium without growth factors by activating the STAT3 pathway . These observations illustrate a strategy by which KSHV exploits the complement system for cell survival and persistent infection . Furthermore , we have observed complement activation in KS tumors indicating a role for the complement in promoting inflammation and angiogenesis during KSHV-induced tumorigenesis .
During the process of investigating the mechanism of KSHV immune evasion , we unexpectedly found that KSHV activated the complement system during latency . In KS lesions , strong staining of C5b-9 was observed on the spindle tumor cells ( Figure 1A ) . Consistent with C5b-9 staining , strong staining for C3d was also observed on the spindle tumor cells ( Figure 1B ) , which were identified by positive staining for the major KSHV latent protein LANA ( ORF73 ) ( Figure 1C ) [36] . A non-immune rabbit serum did not detect any positive signal in the KS lesions ( Figure 1D and 1E ) . No C5b-9 , C3d or LANA staining was observed in the healthy tissues adjacent to the KS lesions ( Figure 1F , 1G and 1H ) . C3d is part of C3b , which is the central product of all three complement activation pathways while C5b-9 is the final product of all three complement activation pathways [18] , [20] , [21] . Detection of C3b and C5b-9 deposition on the tumor cells indicates activation of the complement system in KS tumors . To determine if KSHV infection caused the activation of the complement system , we examined telomerase-immortalized microvascular endothelial cells ( TIME ) and TIME cells latently infected by a recombinant KSHV BAC36 ( TIME-KSHV ) [37] . While KSHV is inefficient in establishing persistent infection in TIME cells because of the rapid loss of viral episome [38] , BAC36 contains a hygromycin-resistant cassette enabling the selection of stable latently KSHV-infected cultures . BAC36 also contains a green fluorescent protein ( GFP ) cassette facilitating the monitoring of KSHV infection . TIME-KSHV cells were latently infected by KSHV based on the expression of viral latent protein LANA and the lack of expression of lytic proteins K8 . 1 and ORF65 ( Figure S1 ) . Robust C5b-9 deposition was observed on TIME-KSHV cells while only weak or no C5b-9 staining was observed on TIME cells following incubation with medium containing normal human serum , which contained different components of the complement system ( Figure 2A ) . As expected , we did not observe any C5b-9 deposition on TIME-KSHV and TIME cells when heat-inactivated human serum were used ( Figure 2A ) . We further quantified C5b-9 deposition on TIME and TIME-KSHV cells exposed to normal human serum . Ten random images from each cell type were quantified for C5b-9 deposition using the ImageJ's quantification tool ( Figure S2 ) and the average pixels per cell of C5b-9-positive staining were presented ( Figure 2B ) . While TIME cells had no or only few weak tiny C5b-9 particles , which probably reflected the background staining , all TIME-KSHV cells had C5b-9 depositions , many of which had strong large C5b-9-positive areas ( Figure 2B ) . There was no correlation between C5b-9 deposition and GFP intensity of the cells . Flow cytometry analysis also detected weak C3b staining on the TIME cells and a much robust staining on the TIME-KSHV cells ( Figure 2C ) . To determine the cellular location of C5b-9 deposition , we stained integrin α5β3 , which was primarily located in the cell plasma membrane . Z-stacks were acquired with a confocal laser-scanning microscope and used to generate XY 3-dimentional ( 3-D ) projection overview images and the corresponding cross-sectional XZ and YZ images ( Figure 2D and S3 ) . C5b-9 deposition was primarily observed on the outer edges of cell plasma membranes ( arrow ) . In some areas , C5b-9 localization on the cell surface was not obvious on the XY plane albeit their colocalization with α5β3 . However , careful examination of the XZ and YZ planes clearly confirmed their cell surface localization . KSHV lytic replication and the expression of viral lytic proteins can potentially trigger or amplify complement activation . C5b-9 and C3b depositions did not induce KSHV lytic replication as all KSHV-infected cells remained negative for viral early lytic protein ORF59 and late lytic protein ORF65 ( Figure S4 ) . Similar results were also observed in long-term latently KSHV-infected telomerase-immortalized umbilical vein endothelial cells ( TIVE-LTC ) , another KSHV latent infection model [39] . C5b-9 deposition was observed on TIVE-LTC but not on uninfected TIVE cells upon exposure to normal human serum ( Figure S5 ) . Together , these results suggest that KSHV might induce activation of the complement system during latency . C3 is essential for the activation of all three complement pathways [21] . To determine whether C5b-9 deposition on latently KSHV-infected cells was indeed dependent on activation of the complement system , we exposed TIME-KSHV cells to normal human serum depleted of the C3 component to inactivate all the complement pathways . Depletion of C3 component abolished C5b-9 deposition on TIME-KSHV cells ( Figure 3A ) . However , addition of purified C3 proteins to the C3-depleted serum restored C5b-9 deposition . These results indicated that the observed C5b-9 deposition on latently KSHV-infected cells was specific and was indeed mediated by the complement system . To identify the specific complement pathway activated by KSHV-infected cells , we exposed the cells to normal human serum in the presence of 10 mM EGTA and 20 mM MgCl2 , which spared the alternative pathway but inactivated the other pathways , or 20 mM EDTA , which inactivated the alternative pathway [40] , [41] . Addition of EGTA and MgCl2 to normal human serum did not affect the detection of C5b-9 and C3b on KSHV-infected cells ( Figure 3B and 3C ) . However , addition of EDTA abolished the detection of C5b-9 and C3b . C1q is the initiation factor for the classical complement pathway while factor B is required for the initiation of the alternative complement pathway as well as amplification of all three complement pathways [20] , [21] . As expected , depletion of C1q from the normal human serum had no effect on C5b-9 deposition on TIME-KSHV cells while depletion of factor B from the normal human serum abolished C5b-9 deposition ( Figure S6 ) . Together , these results indicated that alternative complement pathway was activated by latently KSHV-infected cells . Because we detected most of the C5b-9 deposition on the spindle tumor cells rather than across the entire tumor section in the immunohistochemical staining ( Figure 1 ) , we focused on the cell surface-expressing complement regulatory proteins . Reverse transcription real-time PCR ( RT-qPCR ) detected strong expression of CD55 and CD59 in TIME or TIVE cells ( Figure 4A ) , which were consistent with the absence of complement activation on these cells upon exposure to normal human serum ( Figure 2 and S5 ) . KSHV infection significantly downregulated the expression of CD55 and CD59 in TIME-KSHV and TIVE-LTC cells ( Figure 4A ) . In contrast , we detected no difference of expression for CD46 between uninfected and KSHV-infected cells ( Figure 4A ) , and no expression of CD35 in any of the cells tested , suggesting that both CD46 and CD35 were not involved in the control of complement activation in these cells . Consistent with the mRNA results , total CD55 and CD59 proteins detected by Western-blotting and their cell surface expression levels detected by flow cytometry were expressed in much lower levels in KSHV-infected endothelial cells than in the uninfected cells ( Figure 4B–4C ) . As expected , there was no difference of CD46 protein expression between uninfected and KSHV-infected cells ( Figure 4B ) . These results indicated that KSHV infection might activate the alternative complement pathway by downregulating the expression of CD55 and CD59 proteins . To further determine the biological relevance of these observations , we examined the expression CD55 and CD59 proteins in KS tumors ( Figure 4D–4E ) . In agreement with the cell culture results , we observed weak or close to no expression of CD55 and CD59 on the typical spindle tumor cells in KS tumors ( red arrows in Figure 4D–4E: a ) . However , CD55 and CD59 were highly expressed in the infiltrated immune cells surrounding the spindle cells ( black arrows in Figure 4D–4E: a ) or in normal blood vessels adjacent to the tumors ( black arrows in Figure 4D–4E: b ) . No staining was observed in the KS tumors stained with isotype-matched control antibodies ( Figure 4D–4E: c ) . C5b-9 induces cell lysis by assembling a pre-forming complex on the cell membrane [18] , [34] . Because we observed C5b-9 deposition on latently KSHV-infected endothelial cells ( Figure 2 ) , we further examined the fate of these cells . Both TIME and TIME-KSHV cells cultured in heat-inactivated human serum had low basal levels of dead cells in the range of 1–4% ( Figure 5A ) . In agreement with the absence of C5b-9 deposition ( Figure 2 ) , there was no significant increase of dead cells in TIME cells exposed to normal human serum ( Figure 5A ) . In contrast , the number of dead cells in TIME-KSHV cells exposed to normal human serum for 1 h was significantly higher than those exposed to heat-inactivated human serum under the same condition ( 7 . 5% vs 3 . 4% , P<0 . 05 ) ( Figure 5A ) . The number of dead cells in TIME-KSHV cells following exposure to normal human serum might vary but was usually in the range of 5–12% depending on the batch of the serum . Extended exposure of the cells for up to 8 h or addition of new normal human serum to the medium to avoid possible complement exhaustion or inactivation in the medium did not further increase the number of dead cells . There was no detectable change of total live cells in both TIME and TIME-KSHV cells cultured in heat-inactivated and normal human serum ( Figure 5B ) . These results indicated that most latently KSHV-infected cells were resistant to complement-mediated cytolysis . Because KSHV lytic proteins ORF59 and ORF65 remained undetectable following exposure to the complement ( Figure S4 ) , we concluded that viral lytic replication did not influence the sensitivity of KSHV-infected cells to complement-mediated cytolysis . KSHV ORF4 encodes a complement inhibitory protein named KCP or kaposica that inhibits complement activation [42] , [43] . ORF4 is a viral lytic protein . We did not detect any expression of ORF4 in KSHV-infected cells before and after complement exposure ( Figure S7 ) , indicating that this viral protein did not mediate the resistance of TIME-KSHV cells to the complement . We also did not detect any changes in CD55 and CD59 expression in KSHV-infected cells following complement exposure by either immunofluorescence staining or Western-blotting ( Figure S8 ) , indicating that these complement regulatory proteins did not mediate the resistance of KSHV-infected cells to the complement-mediated cytolysis . To further determine if the sensitivity of a small fraction of KSHV-infected cells to complement-mediated cytolysis was due to a larger amount of C5b-9 deposition on these cells , we quantified C5b-9 deposition on the individual live and dead cells following their exposure to normal human serum . Examination of 20 randomly selected live or dead cells revealed wide ranges of C5b-9 deposition on the individual cells in both live and dead cells albeit a few strong staining cells were observed on the dead cells ( Figure S9 and S10 ) . Thus , we concluded that the sensitivity of a small fraction of KSHV-infected cells to complement-mediated cytolysis was not due to a larger amount of C5b-9 deposition on these cells . The generation of C3b and C3d as a result of C3 activation leads to the recruitment of soluble factor H and factor I on the cell surface [44] . In particular , C3d binds to factor H forming multimeric factor H-C3d complexes [45] . Indeed , strong factor H staining was detected on KSHV-infected cells but not on uninfected cells following exposure to normal human serum ( Figure 5C ) . Interestingly , the majority of factor H signals were colocalized with those of C5b-9 . Colocalization of factor H with C5b-9 was reported before in de novo membranous glomerulonephritis occurring in patients with renal transplant [46] . Unexpectedly , no factor I signal was detected on KSHV-infected or -uninfected cells following exposure to normal human serum ( Figure 5C ) . Recruitment of factor H protects cells from further complement attack , which is amplified by factor I [20] , [21] . Thus , we examined the roles factors H and I in protecting KSHV-infected cells from complement-mediated cytolysis . Depletion of factor H significantly increased the number of dead cells and reduced the number of live cells while addition of purified factor H to the depleted serum prevented the increase of dead cells ( Figure 5D ) . In contrast , no obvious change in the number of live or dead cells was observed following the depletion of factor I . These results indicated that binding of factor H but not factor I conferred KSHV-infected cells resistance to complement-mediated cytolysis . Sublytic C5b-9/MAC has been associated with enhanced cell survival [19] , [21] . Because most of latently KSHV-infected endothelial cells were resistant to complement-mediated cell killing ( Figure 5A–5B ) , we determined the effect of the activated complement on cell survival . Cells were cultured in medium depleted of growth factors and heat-inactivated or normal human serum . The total number of live cells in TIME cells cultured in both heat-inactivated and normal human sera remained unchanged for up to 24 h , and then decreased by 8–10% at 48 h ( Figure 6A ) . Consistent with these results , the number of dead cells in TIME cells cultured in heat-inactivated and normal human sera increased from the basal 1% and 2% to 15% and 17% at 48 h , respectively ( Figure 6B ) . These results indicated that most of TIME cells could survive for up to 48 h without growth factors . Furthermore , there was no obvious difference between TIME cells cultured in heat-inactivated and normal human sera . In contrast , TIME-KSHV cells cultured in heat-inactivated human serum had a significant decrease in the number of live cells by 25% and 50% at 24 h and 48 h , respectively ( Figure 6A ) . The number of dead cells also increased from the basal 2% to 19% by 24 h and to 48% by 48 h , respectively ( Figure 6B ) . These results indicated that TIME-KSHV cells were more sensitive to growth factor depletion than TIME cells when both types of cells were cultured in heat-inactivated human serum . However , the sensitivity of TIME-KSHV cells cultured in heat-inactivated human serum to growth factor depletion could be rescued by normal human serum . Specifically , TIME-KSHV cells cultured in normal human serum had no detectable change in the number live cells by 24 h and had only a slight decrease by 11% at 48 h ( Figure 6A ) . Following an initial increase from the basal 2% to 6–8% as shown in Figure 5A , the number of dead cells in TIME-KSHV cells cultured in normal human serum remained at 7% at 24 h and was increased to 18% at 48 h , which was significantly lower than the 48% in the same cells cultured in heat-inactivated human serum ( P<0 . 001 in Figure 6B ) . These results suggested that a large portion of TIME-KSHV cells failed to survive without growth factors but normal human serum could protect them from cell death and extend their survival . To exclude possible confounding effect of growth factors in the normal human serum , we cultured the cells in medium with C3-depleted human serum and the same depleted serum reconstituted with purified C3 protein . Similar numbers of live cells were observed for TIME cells cultured in medium with and without C3 protein at 48 h ( Figure 6C ) . However , the number of live cells in TIME-KSHV cells cultured in C3-depleted serum was significantly lower than those cultured in C3-reconstituted serum ( P<0 . 01 in Figure 6C ) . These results confirmed that activation of the complement pathway promotes cell survival of latently KSHV-infected endothelial cells cultured in growth factor-depleted medium . To identify the complement protein ( s ) that regulates the survival of latently KSHV-infected endothelial cells , we cultured the cells in medium with C6-depleted human serum . Similar to depletion of C3 protein , depletion of C6 protein decreased the number of live cells but increased the number of dead cells ( Figure 6D ) . Addition of purified C6 protein to the depleted serum , which reconstituted the complement system , prevented cell death ( Figure 6D ) . These results indicated that the late complement components , C5b to C9 , and their complexes were important for the survival of latently KSHV-infected endothelial cells following growth factor depletion . Binding of the C5b-9 complexes to target cells can trigger acute activation of diverse signaling pathways including ERK1 , JNK1 , p38 , PI3K/AKT , and JAK/STAT3 pathways [21] . To determine the pathway that mediated the enhanced survival of latently KSHV-infected endothelial cells grown in medium without growth factors , we examined the effects of normal human serum in the presence of specific inhibitors of different pathways activated by the C5b-9 complexes . Among all the inhibitors examined , only STAT3 and JAK inhibitors antagonized the enhanced survival effect of complement activation ( Figure 7A and S11 , S12 ) . MEK and PLC inhibitors caused cell morphological changes , which were probably due to their toxicity . However , they did not increase any cell death within the experimental timeframe ( Figure S12 ) . In contrast , STAT3 and JAK inhibitors increased the number of dead cells in TIME-KSHV cells cultured in normal human serum to the levels similar to those cultured in heat-inactivated serum ( Figure 7A and S11 ) . Consistent with these results , treatment with STAT3 and JAK inhibitors reduced the number of live cells in TIME-KSHV cells cultured in normal human serum to the levels similar to those cultured in heat-inactivated serum ( Figure 7A ) . Importantly , there was no change in C5b-9 deposition following treatment with STAT3 inhibitor ( Figure S13 ) . These results suggested that the STAT3 pathway likely mediated the complement enhanced cell survival of TIME-KSHV cells grown in medium without growth factors . We further examined the effect of complement activation on the STAT3 pathway . In full endothelial cell medium containing growth factors , we detected strong STAT3 Y705 phosphorylation in both TIME and TIME-KSHV cells ( 0 min in Figure 7B ) . TIME-KSHV cells also had strong STAT3 S727 phosphorylation but much weaker signal was observed in TIME cells ( 0 min in Figure 7B ) . These results are not surprising because a number of growth factors such as EGF and PDGF in the endothelial cell medium are known to activate STAT3 [47] . When we exchanged the medium for endothelial cell basal media without growth factors containing 10% heat-inactivated or normal human serum , Y705 phosphorylation decreased rapidly within 30 min in both TIME and TIME-KSHV cells ( Figure 7B ) . Weak STAT3 Y705 phosphorylation persisted for up to 24 h in TIME cells cultured in either heat-inactivated or normal human serum . While STAT3 Y705 phosphorylation remained weak in TIME-KSHV cells cultured in heat-inactivated and normal human serum in the first 8 h , a significant increase of STAT3 Y705 phosphorylation was observed in these cells cultured in normal human serum but not those cultured in heat-inactivated serum by 16 h and 24 h ( Figure 7B ) . STAT3 S727 phosphorylation also decreased in both TIME and TIME-KSHV cells by 45 min after the full endothelial cell medium was exchanged to basal medium without growth factors ( Figure 7B ) . The S727 phosphorylation signal in TIME cells grown in heat-inactivated or normal human serum was almost not detectable by 1 h following the depletion of growth factors . Under the same condition , we continued to detect S727 phosphorylation in TIME-KSHV cells grown in heat-inactivated or normal human serum ( Figure 7B ) . These results are consistent with the observation of kaposin B activation of S727 but not Y705 phosphorylation in primary human endothelial cells latently infected by KSHV [48] . To confirm that the increased STAT3 Y705 phosphorylation in TIME-KSHV cells following prolonged culture in normal human serum without growth factors was due to activation of the complement system , we examined the cells cultured for 24 h in medium with C3-depleted serum without growth factors . Depletion of C3 protein abolished the increase of STAT3 Y705 phosphorylation of TIME-KSHV cells while reconstitution of the C3 protein in the depleted serum effectively restored Y705 phosphorylation ( Figure 7C ) , indicating that STAT3 Y705 phosphorylation was indeed mediated by complement activation . Similarly , depletion of C6 protein abolished the increase of STAT3 Y705 phosphorylation in TIME-KSHV cells while reconstitution of the C6 protein in the depleted serum effectively restored Y705 phosphorylation ( Figure 7D ) , indicating that STAT3 Y705 phosphorylation was mediated by the C5b-9 complex . Moreover , when cells were exposed to normal human serum for 1 h and subsequently cultured in endothelial basal media without growth factors and without serum for 24 h , we could still detected the increased STAT3 Y705 phosphorylation in TIME-KSHV cells ( Figure 7E ) , indicating that the effect of complement activation on STAT3 tyrosine phosphorylation was sustained for at least 24 h even without the persistent presence of normal human serum and growth factors . STAT3 tyrosine phosphorylation is mediated by Janus kinases ( JAKs ) in response to activation of cytokine receptors or by Src in response to growth factor receptors [47] . JAK inhibitor but not Src inhibitor blocked complement activation of STAT3 Y705 phosphorylation ( Figure 7F ) , suggesting that JAKs mediated the observed STAT3 tyrosine phosphorylation , most likely through cytokines that were induced upon complement activation . Nevertheless , we cannot exclude the possible direct induction of STAT3 Y705 phosphorylation by the C5b-9 complexes . Our results so far suggested that downregulation of CD55 and CD59 expression might mediate complement activation in latently KSHV-infected endothelial cells ( Figure 4 ) . We therefore generated TIME-KSHV cells with stable overexpression of CD55 or CD59 protein . The levels of CD55 and CD59 proteins in these stable cells were similar to those in TIME cells based on the results of Western-blotting and flow cytometry analysis ( Figure 8A–8C ) . CD55 primarily inhibits C3 activation and amplification of the activated complement system while CD59 inhibits C5b-9 formation [20] , [21] , [29] . As expected , overexpression of either CD55 or CD59 protein was sufficient to significantly decrease C5b-9 deposition on TIME-KSHV cells exposed to normal human serum ( Figure 8D and S14 ) . Overexpression of CD55 also significantly decreased C3b deposition on TIME-KSHV cells; however , overexpression of CD59 , as expected , had minimal effect on C3b deposition on these cells ( Figure 8E ) . Importantly , overexpression of either CD55 or CD59 protein was sufficient to reduce STAT3 Y705 phosphorylation in TIME-KSHV cells cultured for 24 h in growth factor-depleted medium containing normal human serum ( Figure 8F ) . Consistent with these results , TIME-KSHV cells with overexpression of either CD55 or CD59 protein cultured in growth factor-depleted medium containing normal human serum no longer survived better than those cultured in heat-inactivated human serum ( Figure 8G ) . Together , these results indicated that downregulation of CD55 and CD59 proteins mediated complement activation in latently KSHV-infected endothelial cells , which resulted in the activation of STAT3 and prevented cell death induced by growth factor depletion .
Viruses have evolved diverse mechanisms to evade the host immunity including the complement system [49] . During lytic replication , KSHV produces a large number of viral lytic proteins and virions , which are exposed to host immune surveillance . KSHV encodes several proteins to inhibit host immune responses and ensure successful infection and replication [7] . In particular , KSHV encodes a functional homologue of complement regulatory protein KCP [42] , [43] . KSHV KCP has structure and function similar to CD55 , also known as decay accelerating factor ( DAF ) , which inhibits activation of the complement system . KCP is a viral lytic protein , which could protect KSHV virions if it is incorporated , and KSHV-infected cells when it is highly expressed , from complement attack during viral acute infection and lytic replication . Although it encodes an arsenal of immune evasion molecules [7] , KSHV establishes latency with minimal expression of viral proteins in immunocompetent host following acute infection . In KS tumors , most tumor cells are also latently infected by KSHV [5] . Thus , latency is the default program by which KSHV evades the host immunity [7] . In this study , we have unexpectedly found that KSHV activates the complement system during latency . In KS tumors , we have detected C5b-9 and C3d depositions on the LANA-positive spindle tumor cells . In culture , the complement system is activated in latently KSHV-infected endothelial cells upon exposure to normal human serum . Interestingly , most of KSHV-infected endothelial cells are resistant to complement-mediated cytolysis . Thus , there are specific mechanisms for both activating and evading the complement system by KSHV in the latently infected cells . Consistent with these cell culture results , KS spindle tumor cells are healthy , and are spared from complement attack in spite of C5b-9 deposition . Among the three complement pathways , activation of the classical pathway is initiated by the formation of the antigen-antibody complex [18] , [20] , [21] . Binding of antibodies to viral proteins on the surface of virions or cells triggers the activation of the classical complement pathway . In latently KSHV-infected cells , only a few viral latent proteins are expressed , none of which is present on the surface of the infected cells [5] . Although the breakdown of cell membranes and loss of membrane complement regulators in apoptotic cells can activate the classical pathway by recruiting C1q and factor H , this would only initiate the complement cascade and generate C3b but block C3 and C5 convertases , and hence the formation of C5b-9 complexes [20] . We have detected few apoptotic cells ( <3% ) in latently KSHV-infected cells before their exposure to the normal human serum . Furthermore , we have shown that C1q is not required for the complement activation and there is strong C5b-9 deposition following complement activation in latently KSHV-infected cells . These results indicate that the classical complement pathway is unlikely activated during KSHV latent infection . The mannose-binding lectin pathway is activated by the terminal mannose groups present on the microbes , which are absent on latently KSHV-infected cells . Therefore , similar to the classical pathway , the lectin pathway is unlikely activated during KSHV latent infection . Distinct from other pathways , activation of the alternative complement pathway is more complex , which is often involved with more than one factor . Although bacteria , fungi and viruses are the primary initiators , tumor cells can also activate the alternative pathway though the precise mechanism remains unclear [50] , [51] . We have shown that complement activation is not affected by the presence of 10 mM EGTA and 20 mM MgCl2 but abolished by the presence of 20 mM EDTA . Together , these results have shown that latently KSHV-infected cells specifically activate the alternative complement pathway . It is possible that classical complement pathway can be activated in KS tumors if there is active viral lytic replication since most of KS patients have antibodies to KSHV lytic proteins [52] , [53] . However , only a small percentage of the KSHV-infected cells are lytic cells in KS tumors , and in late stage of KS tumors , there is virtually no lytic cell [6] . Our results have shown that most of the spindle tumor cells are LANA-positive with less than 1% of ORF65-positive cells . Furthermore , there is no difference in C5b-9 or C3d staining in KS lesions with and without lytic cells suggesting that the small number of the lytic cells would unlikely be involved in the amplification of the complement cascade . Complement activation is a complex process involving with more than sixty components and activation fragments [17]–[20] . Because complement regulatory proteins are important factors controlling the activation of the complement system , downregulation of these proteins often results in the activation of the complement system [20] , [21] , [24] , [54] . Among them , factor H plays a critical role in regulating the activation of alternative complement pathway as it has been shown in the association of an increased risk of developing both early and late age-related macular degeneration ( AMD ) with a single nucleotide polymorphism in factor H [55]–[58] . However , down-regulation of other complement regulatory proteins such as CD55 and CD59 has also been shown to be involved in complement activation . In fact , downregulation or lack of CD55 and CD59 expression is associated with clinical diseases including paroxysmal nocturnal hemoglobinuria and dysferlin-deficient muscular dystrophy [25] , [26] . In this study , the soluble factors including factor H are provided by the normal human serum rather than from the KSHV-infected cells . Thus , the most likely factors that might mediate complement activation and are also regulated by KSHV in the infected cells are the membrane-associated factors . Furthermore , our immunohistochemistry results show that complement deposition is on the spindle tumor cells but not the adjacent uninvolved tissues , indicating that soluble factors are unlikely to be regulated by KSHV and be involved in the activation of the complement system . Indeed , we have found that complement regulatory proteins CD55 and CD59 are significantly downregulated in latently KSHV-infected endothelial cells and in KS spindle tumor cells . Importantly , we have shown that overexpression of either CD55 or CD59 in latently KSHV-infected cells is sufficient to abolish complement activation . These results are consistent with the facts that CD55 binds to C3b while CD59 binds to C5b-8 complex [21] . We have therefore concluded that KSHV activates the complement system by downregulating complement regulatory proteins during latent infection . Following the initial exposure to normal human sera , most latently KSHV-infected cells are resistant to complement-mediated cytolysis indicating that the complement complexes ( C5b-9 ) might be at sub-lytic dose or have not achieved full cytolytic function on these cells . We have detected deposition of factor H on the KSHV-infected cells , which are in agreement with the observation of C3b deposition on these cells . Factor H deposition cleaves C3b to generate C3d resulting in the formation of multimeric factor H-C3d complexes on the cell surface [45] . While we do not fully understand why the C5b-9 complexes are still formed , factor H deposition on these cells is likely important to provide protection to the cells because depletion of factor H sensitizes KSHV-infected cells to complement attack while reconstitution of the factor H-depleted serum with recombinant factor H rescue the KSHV-infected cells from complement attack . On the other hand , depletion of factor I has no effect on the sensitivity of KSHV-infected cells to complement attack , which is consistent with the lack of deposition of factor I on the KSHV-infected cells . Nevertheless , it is unclear how deposition of factor H might protect latently KSHV-infected cells from complement attack . Activation of the complement system is implicated in chronic inflammation , cell lysis , and wound healing [21] , [59] , [60] . C5b-9 deposition has been detected in tissues of several chronic inflammatory diseases including systemic lupus erythematosus ( SLE ) , diabetes , atherosclerosis , inflammatory bowel disease [17] , [18] , [20] , [21] . C5b-9 deposition is also present in several types of cancer [21] , [61]–[63] . Inflammatory cells can induce genomic instability , promote angiogenesis , and establish a favorable tumor microenvironment to facilitate tumor growth and survival through the production of pro-inflammatory and pro-angiogenic cytokines [64] , [65] . Inflammatory cells can also promote neoplastic spread and metastasis of tumor cells by producing matrix metalloproteinases and chemokines [64] , [65] . Because KS tumor is highly angiogenic containing vast inflammatory infiltration of immune cells [5] , [66] , it is likely that activation of the complement system could contribute to the pathological features of KS and the development of KS tumors . We have shown that activation of the complement system activates the STAT3 pathway , which promotes the survival of latently KSHV-infected cells cultured in growth factor-depleted medium . Importantly , KSHV downregulation of CD55 and CD59 is required for C5b-9 deposition , STAT3 activation and the enhanced cell survival . KS tumors harbor high levels of pro-inflammatory and pro-angiogenic cytokines , some of which including IL-6 and oncostatin M , can induce STAT3 activation [67] , [68] . It has also been shown that C5b-9 deposition on endothelial cells can release basic fibroblast growth factor and platelet-derived growth factor [69] , both of which can activate STAT3 [70] , [71] . Both basic fibroblast growth factor and platelet-derived growth factor are abundant in KS tumors and have been implicated in the pathogenesis of KS [72]–[75] . However , our results have shown that STAT3 tyrosine phosphorylation is involved with JAKs , which primarily mediates the activation of cytokine receptors , but not with Src , which primarily mediates the activation of growth factor receptors . Whether activation of the complement system induces pro-inflammatory and pro-angiogenic cytokines leading to STAT3 activation and enhanced cell survival remain to be further investigated [5] . A previous study has shown acute induction of STAT3 phosphorylation in endothelial cells within 30 min of contact with the C5b-9 complexes [76] . We did not observe increased STAT3 tyrosine phosphorylation until 16 h after the treatment with normal human serum . Thus , the mechanism of STAT3 activation described in our study is likely distinct from that of the previous study . Acute KSHV infection induces STAT3 tyrosine phosphorylation [16] but its effect on long-term latently KSHV-infected cells is unclear . We have shown that long-term latent TIME-KSHV cells also have higher levels of STAT3 serine phosphorylation than TIME cells when cultured in full endothelial cell medium containing growth factors . When cultured in growth factor-depleted medium , only weak signal of tyrosine phosphorylation was detected in both TIME and TIME-KSHV cells . While weak constitutive serine phosphorylation was detected in TIME-KSHV but not TIME cells , which could be induced by kaposin B [48] , it does not confer survival advantage for TIME-KSHV cells . In contrast , our results have shown that complement activation is required for a higher level of STAT3 tyrosine phosphorylation and for the enhanced cell survival in growth factor-depleted condition . In summary , we have identified a distinct mechanism by which KSHV subverts the alternative complement pathway by downregulating complement regulatory proteins , which results in the activation of the STAT3 pathway and enhanced cell survival . The deregulation of the complement system might promote KSHV latency and contribute to persistent infection and development of KS tumors . Future studies should investigate the effect of the activated complement system on inflammation and angiogenesis in KS tumors .
Telomerase-immortalized human umbilical vein endothelial cells ( TIVE ) and long-term KSHV-infected TIVE cells ( TIVE-LTC ) were obtained from Dr . Rolf Renne [39] . Telomerase-immortalized human microvascular endothelial cells ( TIME ) were obtained from Dr . Don Ganem [38] . KSHV BAC36-infected TIME ( TIME-KSHV ) cells were obtained by infection of TIME cells with BAC36 [37] . The infected cells were selected with hygromycin to achieve 100% stable latent infection based on the expression of LANA and other viral lytic proteins ( Figure S1 ) . This process usually took several weeks . TIME-KSHV cells were used after they had fully established latency but within less than 10 weeks following the initial establishment of latency . The cells were grown in medium without hygromycin for at least 1 week before the experiments . TIVE , TIVE-LTC , TIME and TIME-KSHV were grown in VascuLife VEGF Cell Culture Medium containing 2% FBS , L-glutamine , and growth factors including rhEGF , rhFGF basic , rhIGF-1 , ascorbic acid , hydrocortisone , and heparin sulfate ( Lifeline Cell Technology , Frederick , MD ) . KS lesions and other tissues were previously described [77] . Pooled complement human serum was purchased from Innovative Research , Inc ( Novi , MI ) . C1q-depleted human serum , C3-depleted human serum , C6-depleted human serum , factor B-depleted human serum , purified C3 protein , and purified C6 protein were purchased from Quidel Corporation ( San Diego , CA ) . Factor H-depleted human serum , factor I-depleted human serum , purified factor H protein were obtained from CompTech ( Tyler , TX ) . Stattic ( STAT3 inhibitor ) , JAK inhibitor I , LY294002 ( PI3K inhibitor ) , SB203580 ( p38 inhibitor ) , U0126 ( MEK inhibitor ) , U-73122 ( Phospholipase C inhibitor ) , and Src inhibitor I were purchased from Calbiochem ( San Diego , CA ) . Formalin-fixed 3- or 4-µm serial sections from paraffin-embedded , formalin-fixed human KS lesions were deparaffinized in xylene , washed with 100% ethanol , and then rehydrated in 95% ethanol . Hydrogen peroxidase ( 3% ) in absolute methanol was used to quench endogenous peroxidase . Antigen retrieval was performed by microwaving the tissue sections in citrate buffer ( pH 6 . 0 ) for 30 min followed by cooling at room temperature for 20 min . After blocking with normal serum , the slides were incubated with primary antibodies . A rat monoclonal antibody to LANA ( LNA-1 ) used at 1∶100 dilution was purchased from Advanced Biotechnologies Inc ( Columbia , MD ) . A rabbit polyclonal antibody to CD55 ( sc-9156 ) was obtained from Santa Cruz ( Santa Cruz , CA ) . A mouse monoclonal antibody to CD59 ( MEM-43/5 ) and rabbit polyclonal antibodies to C5b-9 ( ab55811 ) and C3d ( ab15981 ) were from Abcam ( Cambridge , MA ) . All primary antibodies were used at 1∶100 dilution . After washing with PBS , slides were incubated with peroxidase-conjugated secondary antibodies , and signals were revealed with 0 . 03% diaminobenzidine as chromogen and counterstained with hematoxylin . Cell monolayers were fixed in 4% paraformaldehyde for 10 min and washed with PBS . The fixed cells were permeabilized with 0 . 25% Triton X-100 in PBS for 15 min . After blocking in PBS containing 3% BSA for 30 min at 4°C , samples were incubated overnight at 4°C with primary antibody at 1∶200 in PBS containing 3% BSA . After washing with PBS containing 0 . 05% Tween ( PBS-T ) , samples were incubated for 15 min with AlexaFluor conjugated secondary antibodies at 1∶500 in PBS containing 3% BSA , washed again and incubated with 0 . 5 µg/ml 4- , 6-diamidino-2-phenylindole ( DAPI ) in PBS for 1 min . Samples were mounted in FluorSave Reagent ( Calbiochem , San Diego , CA ) . Pictures were obtained using an IX71 Olympus Fluorescence Microscope equipped with a digital camera or a Nikon ECLIPSE Ti Confocal Laser-Scanning Microscope . Nikon NIS Elements Ar Microscope Imaging Software was used for image analysis and 3-D rendering . In addition to antibodies to LANA , C5b-9 , CD55 and CD59 , mouse monoclonal antibodies to C3b ( 755 , Abcam ) , K8 . 1 ( 13-213-100 , Advanced Biotechnologies , Inc ) , ORF59 ( 13-211-100 , Advanced Biotechnologies , Inc ) , factor H ( OX-24 , Abcam ) , factor I ( OX-21 , Abcam ) , and integrin αVβ3 ( LM609 , Millipore , Billerica , MA ) were also used as primary antibodies . A mouse monoclonal antibody to CD55 ( MEM-118 , Abcam ) was used for dual staining with C5b-9 . A mouse monoclonal antibody to ORF65 was previously described [37] . Secondary antibodies included AlexaFluor 568 anti-rabbit IgG , AlexaFluor 568 anti-rat IgG , AlexaFluor 568 anti-mouse IgG , AlexaFluor 647 anti-mouse IgG , and AlexaFluor 647 anti-mouse IgG1 , all from Invitrogen ( Carlsbad , CA ) . Cells at 50 , 000 cells per well were seeded in 24-well plates with 12-mm glass coverslip overnight . Human complement serum were mixed with VascuLife VEGF Cell Culture Medium and the mixture was applied to the cells . Heat-inactivation was performed at 56°C for 30 min . For reconstitution of complement factor-depleted human serum , the complement-depleted human serum was mixed with the purified complement factor protein . Based on the certificate of analysis of the serum from the manufacturer , appropriate amounts of the purified complement factor was added to the complement factor-depleted human serum to achieve the functional activity ratio of CH50/ml that is equivalent to normal human serum . To identify the complement pathway , complement activation was also performed in the presence of 10 mM EGTA and 20 mM MgCl2 or 20 mM EDTA . After treatment of human complement serum , the cover slip was washed once with PBS then stained by immunofluorescence assay to detect C5b-9 deposition . Images were quantified for C5b-9 deposition using the particle analyzing function of the ImageJ software ( National Institute of Health , Bethesda , MD ) . To detect C3b deposition , cells were grown in 6-well plates . Following complement treatment , cells were detached and quantified by flow cytometry analysis . Total RNA from cultured cells was isolated with NucleoSpin RNA II as recommended by the manufacturer ( MACHEREY-NAGEL Inc . , Bethlehem , PA ) . Total RNA of 1 µg was reverse-transcribed in a total volume of 20 µl to obtain first-strand cDNA using the Superscript III first-strand synthesis system ( Invitrogen ) , according to the manufacturer's instructions . Real-time PCR was performed using Power SYBR Green PCR Master Mix ( Applied Biosystems , Foster City , CA ) and a RealPlex thermal cycler ( Eppendorf , New York , NK ) . The following PCR program was used: 95°C for 10 min , 40 cycles of 95°C for 15 s , 60°C for 1 min . All samples , including a control without the template were examined in triplicate for each primer pair . Amplification for human glyceraldehyde 3-phosphate dehydrogenase ( GAPDH ) was used as a loading control . Data analysis was performed as previously described [78] . The primers used in this study were hGAPDHs: 5′-TGACAACAGCCTCAAGAT-3′ and hGAPDHas: 5′-GAGTCCTTCCACGATACC-3′ for GAPDH; hCD59s: 5′-AAGAAGGACCTGTGTAACTT-3′ and hCD59as: 5′ GAGTCACCAGCAGAAGAA-3′ for CD59; hCD55s: 5′-GGCAGTCAATGGTCAGATA-3′ and hCD55as: 5′-GGCACTCATATTCCACAAC-3′ for CD55; and hCD46s: 5′ TTTGAATGCGATAAGGGTTT-3′ and hCD46as: 5′ GAGACTGGAGGCTTGTAA-3′ for CD46 . The primers were synthesized by Integrated DNA Technologies ( Coralville , IA ) . Cells were lysed in RIPA buffer containing 10 mM Tris-HCl at pH 8 . 0 , 1 mM EDTA , 140 mM NaCl , 0 . 1% SDS , 0 . 1% sodium deoxycholate , 1% Triton X-100 and a protease inhibitor cocktail ( AMRESCO LLC , Solon , OH ) . The cell suspension was incubated at 4°C for 15 min and then centrifuged at 14 , 000 g for 15 min at 4°C . The supernatant was collected and the protein concentration was measured by BCA assay ( Pierce , Rockford , IL ) . The protein was separated by electrophoresis on SDS-PAGE and transferred onto a nitrocellulose membrane ( GE Healthcare , Piscataway , NJ ) . Immunodetection was performed with the mouse monoclonal antibodies to CD46 ( MEM-258 , Abcam ) and β-tubulin ( 7B9 , Sigma , St . Louis , MO ) , rabbit polyclonal antibodies to STAT3 ( #9132 , Cell Signaling Technology , Danvers , MA ) and phospho-STAT3 Ser727 ( 9134 , Cell Signaling Technology ) , and a rabbit monoclonal antibody to phopho-STAT3 Tyr705 ( D3A7 , Cell Signaling Technology ) in addition to the antibodies to CD55 and CD59 , all used at 1∶1000 dilution . Cells detached from the plate with 5 mM EDTA in Dulbecco's phosphate-buffered saline were fixed with 4% paraformaldehyde in PBS for 20 min and incubated with primary antibodies at 1∶50 dilution ( CD55 ) or 1∶500 ( C3b and C59 ) for 30 min at 4°C . For the detection of C3b , complement activation was carried as described above before cell detachment . After washing in PBS , cells were incubated with APC-conjugated goat anti-mouse or rabbit antibodies . Flow cytometry was performed with a FACS Canto II flow cytometer and analyzed with CellQuest Pro software ( Becton Dickinson , Bedford , MA ) . Prior to analysis , all samples were gated to eliminate dead cells . Besides antibodies to CD55 and CD59 , a mouse monoclonal antibody to C3b ( 10C7 , Abcam ) was used for the analysis . After washing the cells with Dulbecco's phosphate-buffered saline , 5 µM EthD-1 ( Invitrogen ) in EGM was applied . After incubation for 30 min at 37°C , the total numbers of live cells and the labeled dead cells were observed and counted under an IX71 Olympus Fluorescence Microscope . Cells at 5 , 000 cells/well were seeded in 96-well plates overnight . Following treatment with human serum complement with and without the presence of chemical inhibitors , cells were incubated in 0 . 5 mg/ml of MTT solution ( Sigma ) at 37°C for 4 h . The solution was then replaced with DMSO . The optical densities were determined at 540 nm and 630 nm using a Synergy TM 2 Multi-Mode Microplate Reader ( BioTek , Winooski , VT ) . Lentiviral plasmids expressing CD55 ( h-CD55 Lentivirus vector , #LV112276 ) , CD59 ( h-CD59 Lentivirus vector , #LV112288 ) and the blank vector ( pLenti-GIII-CMV , #LV587 ) were purchased from Applied Biological Materials Inc ( Richmond , BC ) . Infectious Lentiviruses were produced using ViraPower Lentiviral Packaging Mix ( Invitrogen ) . Specifically , 293T cells were seeded at 8×106 cells in a 150 cm2 flask overnight . DNAs from 6 µg of pLP1 , 6 µg of pLP2 , 6 µg of pLP/VSVG and 9 µg of the target gene plasmid were transfected into cells using Lipofectamine 2000 Transfection Reagent according to the instructions of the manufacturer ( Invitrogen ) . The supernatant containing Lentivirus was harvested 48 h later , filtered through a 0 . 45-µm-pore-size filter , and concentrated by centrifugation at 24 , 000 rpm in a Beckman SW32 rotor for 2 h at 4°C . The pellet containing the virus was resuspended in Opti-MEM reduced serum medium ( Invitrogen ) . Viruses were then stored at −80°C for long-term use or 4°C for short-term use . To generate stable cells expressing CD55 or CD59 , TIME-KSHV cells were infected with ∼10 MOI of the Lentivirus in the presence of 8 µg/ml of polybrene . Two days after infection , the infected cells were selected with 1 µg/ml of puromycin for 2 weeks . The cells were then cryo-frozen or used for other experiments . Results are shown as mean ± SD ( standard deviations ) where appropriate . The 1-tailed Student's test was used to compare data between the different groups . Statistical significance assumed at P values less than 0 . 05 , 0 . 01 or 0 . 001 is represented by “*” , “**” or “***” respectively .
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The complement system is an important part of the innate immune system . Pathogens have evolved diverse strategies to evade host immune responses including attack of the complement system . Kaposi's sarcoma-associated herpesvirus ( KSHV ) is associated with Kaposi's sarcoma ( KS ) , primary effusion lymphoma and a subset of multicentric Castleman's disease . KSHV encodes a number of viral proteins to counter host immune responses during productive lytic replication . On the other hand , KSHV utilizes latency as a default replication program during which it expresses a minimal number of proteins to evade host immune detection . Thus , the complement system is expected to be silent during KSHV latency . In this study , we have found that the complement system is unexpectedly activated in latently KSHV-infected endothelial cells and in KS tumor cells wherein KSHV downregulates the expression of CD55 and CD59 complement regulatory proteins . More interestingly , most of latently KSHV-infected cells not only are resistant to complement-mediated cell killing , but also acquire survival advantage by inducing STAT3 tyrosine phosphorylation . These results demonstrate a novel mechanism by which an oncogenic virus exploits the host innate immune system to promote viral persistent infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"oncology",
"infectious",
"diseases",
"medicine",
"and",
"health",
"sciences",
"clinical",
"immunology",
"biology",
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2014
|
Exploitation of the Complement System by Oncogenic Kaposi's Sarcoma-Associated Herpesvirus for Cell Survival and Persistent Infection
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Trypanosoma cruzi , the causative agent of Chagas disease , displays significant genetic variability revealed by six Discrete Typing Units ( TcI-TcVI ) . In this pathology , oral transmission represents an emerging epidemiological scenario where different outbreaks associated to food/beverages consumption have been reported in Argentina , Bolivia , Brazil , Ecuador and Venezuela . In Colombia , six human oral outbreaks have been reported corroborating the importance of this transmission route . Molecular epidemiology of oral outbreaks is barely known observing the incrimination of TcI , TcII , TcIV and TcV genotypes . High-throughput molecular characterization was conducted performing MLMT ( Multilocus Microsatellite Typing ) and mtMLST ( mitochondrial Multilocus Sequence Typing ) strategies on 50 clones from ten isolates . Results allowed observing the occurrence of TcI , TcIV and mixed infection of distinct TcI genotypes . Thus , a majority of specific mitochondrial haplotypes and allelic multilocus genotypes associated to the sylvatic cycle of transmission were detected in the dataset with the foreseen presence of mitochondrial haplotypes and allelic multilocus genotypes associated to the domestic cycle of transmission . These findings suggest the incrimination of sylvatic genotypes in the oral outbreaks occurred in Colombia . We observed patterns of super-infection and/or co-infection with a tailored association with the severe forms of myocarditis in the acute phase of the disease . The transmission dynamics of this infection route based on molecular epidemiology evidence was unraveled and the clinical and biological implications are discussed .
Chagas disease caused by Trypanosoma cruzi is considered a zoonotic and neglected disease that represents an important public health problem in the Americas . This parasite is mainly transmitted by the faeces of triatomine insects and shows tremendous genetic variability reflected in at least six Discrete Typing Units ( DTU's ) classified as T . cruzi I – T . cruzi VI [1] , [2] . Some authors have demonstrated intraspecific genetic diversity within T . cruzi I suggesting the existence of genotypes associated to the domestic ( TcIa ) , peridomestic ( TcIb ) and sylvatic ( TcId ) transmission cycles [3] . Other routes of disease transmission , such as blood transfusion , vertical transmission , organ transplantation and accidental laboratory contamination are considered relevant routes [4] . Trypanosoma cruzi transmission by vertical vias and by transfusion of contaminated blood products has become the main mechanisms of transmission in non-endemic countries , including the USA and Spain [5] , [6] . Currently , it is estimated that 7 , 694 , 500 people are infected with this parasite in South , Central American countries and Mexico where control initiatives are being conducted to interrupt T . cruzi transmission by triatomines and the transfusion of blood products [4] . Transmission via oral route is a relevant and emerging scenario of Chagas disease . This via displays a habitual character in the primitive and endemic cycle of the parasite occurring through consumption of contaminated food and/or beverages by dejection of triatomines faeces [4] . Also by ingestion of uncooked meat , food or beverages contaminated with urine or anal secretions of infected marsupials [7] . The emergence of Chagas disease from oral routes of transmission , especially in the Amazon Region are based on the consumption of food contaminated by the failure to adopt adequate hygiene practices in food handling and human establishment in sylvatic habitats , which increases the risks associated with the proximity of sylvatic vectors and reservoirs [7] . Oral outbreaks of Chagas disease were first reported in the Brazilian Amazon basin in 1965 , followed by reports in Argentina , Bolivia , Colombia , Ecuador and in Venezuela where specific outbreaks have occurred in urban areas [8] . The previously mentioned cases of T . cruzi oral transmission resulted from consumption of sugarcane ( Saccharum spp . ) juice , açai ( Euterpe oleracea ) juice , Guava ( Psidium guajava ) juice and meat from hunting animals . The majority source of contamination has been attributed to T . cruzi infected insects that are macerated with the sugarcane or the fruits used for juice preparation [8]–[13] . All of these acute Chagas disease outbreaks associated with food/beverage consumption display severe clinical features in comparison with those of patients that have been infected with T . cruzi by other transmission routes [4] , [11] , [14] . In Colombia , six cases of acute Chagas disease outbreaks attributed to food/beverages consumption and catalogued as cases of oral transmission according to the National Health Institute ( NHI ) harboring four municipalities have been reported . The first outbreak occurred in a group of soldiers in the municipality of Tibú ( Norte de Santander ) in 1992 . Six cases of acute Chagas disease myocarditis were confirmed . The NHI studied a group of 144 soldiers , of which 24 ( 17% ) were confirmed as serologically positive by Immunofluorescent Assay ( IFAT ) ; Fifty-two percent of the seropositive patients presented electrocardiographic abnormalities [15] . The second outbreak was reported in the municipality of Guamal ( Magdalena ) in 1999 . The surveys provided information from 607 patients; of these , 9 ( 3 . 2% ) presented fevers . Sera samples were taken from 102 patients and 13% ( 13/102 ) of them were IFAT positive with cardiac alterations [16] . The third outbreak took place in Lebrija ( Santander ) in 2008 , two patients died . Diagnosis was confirmed in 10 cases , which were 100% reactive to ELISA and IFAT . In addition , three cases presenting severe myocarditis were confirmed by histopathology [17] . The fourth outbreak took place in the city of Bucaramanga in 2009 , when one child died due to severe myocarditis attributed to T . cruzi ethiology and a total of 5 cases were confirmed in the same family . The NHI found that the most frequent symptoms were fever ( 100% ) , abdominal pain ( 60% ) , and cardiomegaly ( 40% ) . Pericardial effusion was detected in 80% of the cases in the 2009 outbreak in Bucaramanga . The diagnosis was confirmed in 80% of the cases using serological tests ( ELISA and IFAT ) . The two last outbreaks were reported in San Vicente de Chucurí ( Santander ) and Aguachica ( Cesar ) in 2010 , when no deaths were reported but serological diagnosis confirmed that the symptoms were a result of Chagas disease . In the outbreak of Aguachica , 12 cases were confirmed by serological diagnosis using ELISA and IFAT; two cases presented pericardial effusion ( Figure 1 ) . There is scarce available information regarding T . cruzi DTU's detected in the oral cases of Chagas disease . In studies developed by Marcili ( 2009 ) , T . cruzi genotypes associated with food consumption were characterized from wild primates , triatomines and humans in the Brazilian Amazon; all isolates were genotyped as TcI and TcIV [18] . Andrade ( 2011 ) examined T . cruzi strains isolated from oral Chagas disease patients in Santa Catarina , Brazil and reported the presence of DTU's mixtures ( TcI , TcII , TcV ) [19] . Despite these efforts , there is not an evidence-based link between the severe clinical features of food-borne Chagas disease and T . cruzi genotypes [20]–[22] . The objective of this work was to develop a high-throughput analysis using polymorphic microsatellite markers based on a Multilocus Microsatellite Typing strategy ( MLMT ) and gene sequencing of the spliced leader intergenic region of mini-exon gene ( SL-IR ) and a mitochondrial Multilocus Sequence Typing ( mtMLST ) strategy to understand the molecular epidemiology of the clones isolated from six oral Chagas disease outbreaks in Colombia .
Eight T . cruzi isolates from humans ( Tibú , Lebrija , Bucaramanga and San Vicente de Chucurí outbreaks ) and two from triatomines ( Guamal and Aguachica outbreaks ) were cloned by a poisson-distributed limiting dilution assay , obtaining five clones from each isolate ( a total of 50 clones analyzed ) [23] ( Table 1 ) . Blood in guanidine buffer ( GEB ) from six patients ( Lebrija outbreak ) were collected and submitted to molecular characterization analysis by five genomic regions in order to discriminate T . cruzi DTU's [22] , parasitic load quantification using a SYBR Green quantitative real-time PCR assay ( qPCR ) , using methods previously reported [24] and Nested PCR of seven polymorphic microsatellite markers previously reported by following the amplification conditions described by Duque ( 2011 ) to determine the T . cruzi populations circulating in the patients [25] , [26] . These microsatellite markers were only applied on this set of samples in terms of the sensitivity obtained since working with blood samples the number of parasites is scarce . An automated capillary sequencer ( AB3730 , Applied Biosystems , UK ) was employed to obtain the allelic products using a fluorescent-tagged size standard . The metadata was checked manually for errors and all samples were typed in blind to avoid user bias . Available sera samples from patients collected in the different outbreaks ( four from Bucaramanga , two from San Vicente de Chucurí and four from Lebrija ) were tested by TESA-blot . TESA-blot analysis was performed on sera previously positive by IFAT and ELISA . Briefly , TESAs from T . cruzi II strain Y were obtained from the supernatant of infected LLC-MK2 cells and used for immunoblotting . Membrane strips ( 5 mm ) were later incubated with serum diluted 1∶200 in Tris-buffered saline ( TBS ) –1% milk for 2 h with mechanical agitation . After four 5-min washes in TBS , the bound antibodies were detected by using peroxidase-conjugated anti-human immunoglobulin G ( Sigma ) diluted 1∶2 , 500 in TBS–1% milk for 2 h . After a new cycle of washes , the immune complexes were revealed by the addition of H2O2 and 4-chloro-1-naphthol . The reaction was stopped with deionized water [27] . All of the appropriate ethical clearance was considered and approval of the ethics committee from Universidad de Los Andes under the form number 066/2006 . Written consent was obtained in all human patients included as part of the epidemiological surveillance developed by NIH and Universidad de Los Andes under the same form number 066/2006 . Fifty clones corresponding to ten stocks were harvested until they reached logarithmic phase and 200 µL aliquots were taken for DNA extraction using the mini prep Qiagen kit ( Table 1 ) . We always used paired samples in order to compare DNA sequences and microsatellite allele profiles . The molecular characterization of the clones obtained was performed by amplifying the SL-IR and domain ( D7 ) of the 24Sα region [28] . In order to detect genotypes within TcI , direct sequencing of SL-IR region and ten mitochondrion maxicircle DNA fragments was performed [28] , [29] . Primers flanking variable regions of the pre-edited ( 12S rRNA and 9S rRNA ) , 5′ edited ( Cytochrome b ( Cytb ) , MUF1 ( MurfA ) , NADH Dehydrogenase 1 ( ND1 ) , MURF2 ( MurfB ) ) , internal editing ( Cytochrome oxidase II ( COII ) ) and the non-edited regions , ( NADH dehydrogenase 4 ( ND4 ) and NADH dehydrogenase 5 ( ND5a and ND5b ) , were amplified [29] . The amplification of the SL-IR and the ten maxicircle gene fragments was performed in a final volume of 20 µL using 1× Buffer ( Corpogen , COL ) , 50 mM MgCl2 , 10 µM of each primer , 5 U/µL of Taq Tucan ( Corpogen , COL ) and 10 ng of DNA . The mix was submitted to 29 cycles of amplification and the amplicons were visualized in 2% agarose gels stained with ethidium bromide . The PCR products were cleaned up by isopropanol precipitation and sequenced by the dideoxy-terminal method in an automated capillary sequencer ( AB3730 , Applied Biosystems , UK ) . The resulting sequences were edited in MEGA 5 . 0 [30] . All edited sequences were deposited in GenBank and assigned accession numbers KC282902–KC282951 ( Table S1 ) . The final sequences were concatenated in SeaView 4 . 0 according to the orientation of the kDNA maxicircle [31] , [32] . The sequences of the maxicircle molecule were aligned and a matrix was constructed in Nexus format to develop a haplotype network analysis including reference strains from domestic and sylvatic mitochondrial haplotypes ( EM – Homo sapiens-TcIa and YDm1M – Didelphis marsupialis-TcId ) , using the median-joining method and the default parameters on Network 2 . 0 to observe the polymorphism differences among the sequences . Twenty-four microsatellite loci were amplified as previously described [33] . These markers are spread over eight different chromosomes . An automated capillary sequencer ( AB3730 , Applied Biosystems , UK ) was used to obtain the allelic products using a size standard with a fluorescent tag . The metadata was checked manually for errors and all samples were typed in blind to avoid user bias . Finally , individual level pair-wise distances were calculated using the DAS algorithm ( 1-proportion of shared alleles at all loci/n ) and estimated using MICROSAT to construct a genetic distances Neighbor-joining tree ( NJ ) .
Molecular typing was performed in clones from the stocks , which resulted in the presence of T . cruzi I in 49 ( 98% ) clones and T . cruzi IV in 1 ( 2% ) clone ( FCHcl5 ) . When the sequencing of SL-IR was performed , occurrence of 11 ( 22% ) clones as TcIa , 7 ( 14% ) clones as TcIb and 31 ( 64% ) clones as TcId was observed . According to the sequences of the ten gene fragments from the maxicircle molecule , a network was developed based on a median-joining algorithm , which allowed us to observe 32 different haplotypes among the dataset . From the network , we could establish six mitochondrial haplotypes associated to the domestic cycle and 24 mitochondrial haplotypes associated to the sylvatic cycle of transmission based on reference strains ( TcIa and TcId ) , demonstrating the features displayed by each clone ( Figure 2A ) . Based on the microsatellite patterns , a Neighbor-Joining tree was constructed using the genetic distances of shared alleles . We determined the genetic relationships between clones from the same oral outbreak , observing specific alleles groups in each oral outbreak ( evidenced by the different number of multilocus genotypes ) , displaying that independent populations are the causative agents of each outbreak ( Figure 2B; Table S1 ) . The molecular characterization of GEB samples resulted in the detection of different genotypes within the same patient and absolute parasitic loads ranging from 110 to 250 parasites/mL ( Table 2 ) . In the cases of AM and EH , a co-infection with genotypes TcIa and TcId ( SL-IR ) was observed and also presenting the same allelic profile based on microsatellite data . Hence , patients JR and EB were found infected with the TcIa genotype and the same T . cruzi population . In the cases of patients FM and WM , they were infected with only the TcId genotype and they had the same allele profile based on microsatellite data . All of the samples analyzed by TESA-blot showed bands between 130–200 kDa , which corresponds to the SAPA antigen only detected in the acute phase of Chagas disease .
To our knowledge , this is the first report of a set of high-resolution molecular markers being applied to a group of clones isolated from cases of oral Chagas disease transmission . There are few reports where molecular discrimination of DTU's has been performed . In Brazil , there are reports of 14 isolates typed as TcI and TcIV in the Amazonian region [18] . In Santa Catarina , Brazil , a full study using several markers allowed the authors to find TcI , TcII , TcV and mixed infections of the isolates obtained from an oral outbreak in 2005 [19] . In Bolivia , a recent outbreak allowed the authors to find TcI and TcIV [34] . This suggests that our results showing a high prevalence of TcI and one clone typed as TcIV , are in accordance with the genotypes found in stocks isolated from other oral transmission cases . These findings are also in accordance with the biological and ecological distributions of TcI and TcIV , where these genotypes are related to the sylvatic transmission cycles and also display an interesting intersection feature being isolated from domestic and sylvatic hosts in a same niche [2] , [33] , [35] , [36] . Information regarding the epidemiological surveillance was obtained in the cases of Lebrija , Bucaramanga and Aguachica . In Lebrija , the community collected two triatomines ( Panstrongylus geniculatus and Rhodnius pallescens ) from the sylvatic cycle where T . cruzi infection was detected in P . geniculatus . Regarding the reservoirs , one D . marsupialis was collected and not infected with trypanosomatids . As a result , we could determine those cases as oral transmission outbreaks due to the absence of domiciliated vectors . In Bucaramanga , the outbreak ( nine cases ) occurred in the same house during a citrus harvesting , in which the source of infection could be attributed to mandarine and/or orange juice . There was no evidence of domiciliated triatomines; P . geniculatus and R . pallescens were collected and P . geniculatus was found infected with T . cruzi . There are fruits that are sold in the area in little shops on the streets , where P . geniculatus vectors could infect the fruits by dejection of faeces , however further studies are required to validate this premise . The molecular characterization using SL-IR in the isolates and in the GEB samples showed that all clones from the Lebrija patients were typed as TcI . In addition , isolates from P . geniculatus have been found infected with TcI in the sylvatic foci , which may support that it could be the responsible vector in the outbreaks , including the similar multilocus genotypes evidenced by MLMT [23] , [36]–[38] . These results are in accordance with the reported cases of acute oral Chagas disease in Venezuela , where P . geniculatus was the vector incriminated and TcI infection also confirmed [13] , [39] . A significant frequency of TcI among the clones studied was found as previously reported in Colombia [28] , [37] . In the samples collected , TcIa , TcIb and TcId were detected in the clones analyzed as mixed infections within stocks . Based on the analysis of SL-IR genotypes , a pattern of super-infection and/or co-infection within the same patient was observed . It is interesting to highlight the definition of super-infection in the acute phase of Chagas disease; in this context this might be suggesting that a composite of T . cruzi populations ( from different triatomines and/or infected mammals ) are causing the acute infection in the patients sampled . Hence , in terms of multiclonality the acute phase shows the lowest percentage of population diversity but this case is not ruled out in the oral transmission where at least two distinct genotypes were detected within the same patient . Therefore , the infection of two distinct genotypes was corroborated in the stocks LER and EH by microsatellites , demonstrating that certain alleles are associated to the domestic cycle of infection and some alleles associated with the sylvatic cycle residing within the same patient . This suggests that triatomines infected with a composite of T . cruzi populations are a source of infection or that the presence of more than one triatomine is involved in each outbreak . The TcIa genotype , which is associated with the domestic cycle of Chagas disease in Colombia , was detected but was not the most frequent . The TcIb genotype is associated with the peridomestic cycle , while TcId is associated with the sylvatic cycle and the most frequent in our dataset , which supports that the origin of infection was possible triatomines from sylvatic foci . The hypothesis about the origin of infection from sylvatic triatomines is supported by the presence of P . geniculatus and R . pallescens in the dwellings and because these triatomines were found to be mostly infected with genotypes TcIb and TcId [39]–[41] . A strong association across different haplotypes and the outbreaks was observed as well as the high genetic diversity among these clones represented in 32 different haplotypes , observing the occurrence of domestic and sylvatic haplotypes based on the reference strains sequences employed ( Figure 2A ) that correlates with the TcIa/TcIb ( domestic genotypes ) and TcId ( sylvatic genotype ) genotypes . The topology of the network suggests that the population affecting the two patients in Lebrija is similar and that the infection is harbored by a composite of T . cruzi populations , including a unique clone that has a hybrid maxicircle mosaic [37] . The network allows to observe the majority occurrence of sylvatic mitochondrial haplotypes and the low frequency of domestic mitochondrial haplotypes corroborating the premise of the likely incrimination of T . cruzi sylvatic DTU's in the oral infection outbreaks . P . geniculatus has been found naturally infected in Colombia with TcI , TcII and TcIII [23] , [25] , [42] . The presence of these DTU's in P . geniculatus is of paramount importance to understand the dynamics of T . cruzi DTUs in oral transmission outbreaks . The topology of the NJ tree based on polymorphic microsatellite data showed a strong association between each outbreak and the allelic profile of the clones obtained from each stock ( Figure 2B ) . We did find defined clusters in most of the outbreaks with some outliers as seen in the San Vicente de Chucurí outbreak showing that the composite of T . cruzi populations causing the oral infection are quite alike and display a marked genetic variability pattern . There were two fatal cases in the Bucaramanga outbreak , which may suggest that the composition of multiclonal infections in oral outbreaks is closely related to the clinical manifestations of cardiomyopathy in acute cases of Chagas disease . Microsatellite markers were able to show the high multiclonality events observed in the stocks analyzed ( a significant number of distinct allelic multilocus genotypes within hosts ) , which brings up the question whether the source of infection is the result of a single group of triatomines infected with the same T . cruzi population , or a composite of T . cruzi populations from the sylvatic cycle of transmission of Chagas disease in the region [35] , [43] . The molecular characterization in GEB samples showed co-infections in two patients ( AM and EH ) with TcIa and TcId which supports the findings observed in the high-resolution molecular characterization performed in the clones from these patients ( Table 2 ) . In addition , the co-infection patterns could not be confirmed with the microsatellite markers employed . This premise emerges in the light of the absence of triple peaks among the loci studies or heterozygosis status; only locus TcATT14 showed heterozygosis and the rest of loci employed were homozygous , this could be explained by a low resolution power displayed by the microsatellite markers employed since parasite DNA yield was high ( Table 2 ) . Additionally , the multi-copy arrangement that SL-IR displays and the presence of null alleles and/or aneuploidy could explain these premises but further testing is required [44] . In conclusion , we developed a high-resolution molecular typing of the stocks isolated from cases of Chagas disease transmitted by an oral infection route in Colombia . We determined that the prevalent DTU in the stocks was TcI , with one clone typed as TcIV . Based on our results , the T . cruzi populations causing acute infections are those associated with the sylvatic foci and vectored by P . geniculatus and R . pallescens . The DTU discrimination in the oral infection outbreaks allowed us to highlight the significant impact of the DTU's from the sylvatic cycle , TcI and TcIV , in the outbreaks studied , which implies that oral transmission is a relevant epidemiological scenario that has emerged in the natural life cycle of T . cruzi . This suggests that , in areas where vectorial transmission has been interrupted , new acute cases of Chagas disease may emerge as a potential problem in public health .
|
Chagas disease represents a serious health problem affecting more than 10 million people in the Americas . The oral transmission route has emerged as a new epidemiological scenario that needs to be considered in prevention and control strategies . Herein was developed a high-resolution molecular characterization using mtMLST and MLMT tools in order to unravel the molecular epidemiology and transmission dynamics drivers in six well-characterized human oral outbreaks in Colombia . We observed the majority of clones typed as TcI and one clone as TcIV . The analysis of mitochondrial haplotypes allowed us to observe a high frequency of sylvatic haplotypes and a low proportion of domestic haplotypes . Likewise , a tailored allelic profile by each outbreak was observed . Our results suggest that sylvatic populations of T . cruzi are the causative agents of Chagas disease oral outbreaks and these findings should help to pursue new initiatives of control and prevention in those areas where domiciliated vectorial transmission has been interrupted .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
[
"medicine",
"infectious",
"diseases",
"public",
"health",
"and",
"epidemiology",
"chagas",
"disease",
"molecular",
"epidemiology",
"epidemiology",
"genetics",
"molecular",
"genetics",
"biology",
"evolutionary",
"biology",
"parasitic",
"diseases",
"evolutionary",
"systematics",
"genetics",
"and",
"genomics"
] |
2013
|
Molecular Epidemiology of Human Oral Chagas Disease Outbreaks in Colombia
|
The second messenger , cyclic diguanylate ( c-di-GMP ) , regulates diverse cellular processes in bacteria . C-di-GMP is produced by diguanylate cyclases ( DGCs ) , degraded by phosphodiesterases ( PDEs ) , and receptors couple c-di-GMP production to cellular responses . In many bacteria , including Vibrio cholerae , multiple DGCs and PDEs contribute to c-di-GMP signaling , and it is currently unclear whether the compartmentalization of c-di-GMP signaling components is required to mediate c-di-GMP signal transduction . In this study we show that the transcriptional regulator , VpsT , requires c-di-GMP binding for subcellular localization and activity . Only the additive deletion of five DGCs markedly decreases the localization of VpsT , while single deletions of each DGC do not impact VpsT localization . Moreover , mutations in residues required for c-di-GMP binding , c-di-GMP-stabilized dimerization and DNA binding of VpsT abrogate wild type localization and activity . VpsT does not co-localize or interact with DGCs suggesting that c-di-GMP from these DGCs diffuses to VpsT , supporting a model in which c-di-GMP acts at a distance . Furthermore , VpsT localization in a heterologous host , Escherichia coli , requires a catalytically active DGC and is enhanced by the presence of VpsT-target sequences . Our data show that c-di-GMP signaling can be executed through an additive cellular c-di-GMP level from multiple DGCs affecting the localization and activity of a c-di-GMP receptor and furthers our understanding of the mechanisms of second messenger signaling .
Second messengers are small diffusible signaling molecules that are produced or degraded in response to external stimuli and relay information to a receptor to elicit a specific cellular response [1] . The cyclic nucleotide cyclic diguanylate ( c-di-GMP ) is a bacterial second messenger that controls the transition between a free living and biofilm lifestyle [2] , [3] . C-di-GMP is produced by diguanylate cyclases ( DGCs ) , containing GGDEF domains , and degraded by phosphodiesterases ( PDEs ) , containing EAL or HD-GYP domains . Cellular c-di-GMP is sensed by receptors that interact with downstream targets to affect cellular functions . C-di-GMP signaling often involves numerous GGDEF , EAL or HD-GYP domain containing proteins and receptors [4] , and previous reports suggest that the compartmentalization of c-di-GMP signaling components could facilitate the activation of specific cellular processes [3] , [5] , [6] . However , it is currently unclear whether compartmentalization is required to mediate c-di-GMP signal transduction in bacteria . Recent advances in the identification of c-di-GMP receptors have helped define the mechanisms by which c-di-GMP mediates downstream processes . These receptors include riboswitches [7] and proteins that contain various binding domains . PilZ domains are known to bind c-di-GMP and proteins harboring these domains modulate cellular processes such as motility through protein-protein interactions with the flagellar motor complex [8]–[10] . Proteins containing degenerate GGDEF or EAL domains , which have lost their enzymatic activity , are also known to be c-di-GMP receptor proteins . In Pseudomonas fluorescens , LapD binds c-di-GMP through a degenerate EAL domain and modulates the cell surface association of an adhesin through direct interactions with a periplasmic protease [11]–[13] . The degenerate GGDEF domain containing protein CdgG was shown to regulate biofilm formation in Vibrio cholerae [14] . C-di-GMP can also regulate gene expression by binding transcriptional regulators such as the Crp homolog Clp [15] or FleQ [16] . Although the identities of many c-di-GMP receptor proteins are known , the mechanisms of c-di-GMP-mediated signal transduction and gene regulation are not fully understood . In V . cholerae , the bacterial pathogen that causes the disease cholera , c-di-GMP regulates biofilm formation , motility and virulence [17]–[19] . The V . cholerae genome contains 31 genes encoding proteins with GGDEF domains , 11 genes encoding proteins with EAL domains , 10 genes encoding proteins with both GGDEF and EAL domains and 9 genes encoding proteins with HD-GYP domains [14] , [20] . Recently , we characterized VpsT , which is a key c-di-GMP receptor known to regulate biofilm formation in V . cholerae [21] . Biofilm formation in V . cholerae requires the biosynthesis of Vibrio polysaccharide ( VPS ) [22] , [23] , and VpsT activates vps expression through direct binding of the vpsL promoter [21] , [24] . VpsT is a novel member of the FixJ , LuxR and CsgD family of transcriptional regulators that contains a c-di-GMP binding motif and a 6th alpha helix at its N-terminal receiver domain that stabilizes homodimerization [21] . These features make VpsT unique compared to other response regulators and c-di-GMP binding proteins . In this study , we report that VpsT requires c-di-GMP binding and subcellular localization to regulate gene expression . The wild-type VpsT localization pattern is dependent on c-di-GMP binding , c-di-GMP-stabilized dimerization , and the VpsT DNA binding domain . We also show that VpsT does not co-localize or interact with DGCs . Instead , multiple DGCs contribute additively to a cellular c-di-GMP concentration , which affects the localization and activity of the c-di-GMP receptor protein , VpsT .
We hypothesized that the c-di-GMP receptor protein , VpsT , is subcellularly localized , and this localization facilitates c-di-GMP signal transduction . To determine whether VpsT is subcellularly localized , we constructed an N-terminal tagged green fluorescent protein ( GFP ) -VpsT fusion . Expression of gfp-vpsT recovered vpsL expression in a ΔvpsT strain ( Figure 1A ) . vpsL is the first gene in the vps-II operon and VpsT directly binds to the upstream regulatory region of this gene [21] , [22] . Expression of vpsL was similar between strains expressing gfp-vpsT or vpsT alone indicating that our fusion protein is functional . When observed by fluorescence microscopy , GFP-VpsT formed a pattern of localization within the cell ( Figure 1B ) , while a strain expressing GFP exhibited homogenous fluorescence throughout the cytoplasm . We confirmed that this localization was not due to different cellular protein concentrations , as levels of GFP-VpsT were similar to levels of GFP alone ( Figure S1 ) . A census of more than 150 cells per treatment showed that cells expressing GFP-VpsT contained more spots per cell when compared to cells expressing GFP alone when quantified using MicrobeTracker software ( Figure 1C ) [25] . GFP-VpsT localization also exhibited a higher ratio of maximum to average fluorescence intensity across the length of individual cells when compared to cells expressing GFP alone ( Figure S1 ) . These results indicate that GFP-VpsT is subcellularly localized . The striking number of GGDEF , EAL and HD-GYP domain containing proteins present in many bacteria is thought to generate flexibility in signal transduction , allowing multiple sensory inputs to be fed through a single diffusible signaling molecule [4] . Since VpsT is a c-di-GMP binding protein and is subcellularly localized , we wondered whether specific DGCs or PDEs are important for this localization pattern . We therefore measured expression of the vpsL promoter in wild-type V . cholerae and 52 strains containing in-frame deletions of each gene in the V . cholerae genome encoding proteins with GGDEF , EAL or GGDEF and EAL domains . Of the strains examined , 5 DGC deletion strains showed a 2-fold or greater decrease in expression of vpsL ( Figure 1D and S2 ) , namely the previously characterized genes encoding DGCs cdgA ( VCA0074 ) , cdgH ( VC1067 ) , cdgK ( VC1104 ) and cdgL ( VC2285 ) [14] , [26] , [27] , and a predicted DGC , VC1376 , which we name here , cdgM . Furthermore , c-di-GMP levels decreased between 86% and 54% in each single DGC deletion strain when compared to wild type ( Figure 1E ) . These results show that multiple DGCs are involved in vps regulation and thus identified likely candidate DGCs important for VpsT localization . We then observed VpsT localization in strains lacking each of the 5 DGCs important for vpsL expression . VpsT localization was not markedly altered in any strain containing a single DGC deletion ( Figure S1 ) . We then reasoned that VpsT localization may not be dependent on a single DGC , but instead , multiple DGCs contribute additively to VpsT localization . Therefore , we created a strain where all 5 DGCs are deleted in combination , designated Δ5DGC . Δ5DGC exhibited a lower vpsL expression than any single DGC mutant strain ( Figure 1D ) . Moreover , c-di-GMP levels were significantly decreased ( 17% ) in the Δ5DGC strain compared to wild type ( Figure 1E ) . In the Δ5DGC strain , GFP-VpsT localization was reduced and the number of spots per cell and ratio of maximum to average fluorescence intensity were markedly lower compared to wild type expressing the same fluorescent fusion protein ( Figure 1B , 1C and S1 ) . This change in GFP-VpsT localization was not due to different cellular protein concentrations , as GFP-VpsT levels were similar to levels of GFP alone in the Δ5DGC strain ( Figure S1 ) . These results indicate that no single DGC is sufficient to cause VpsT mis-localization , and instead , multiple DGCs additively impact the GFP-VpsT localization pattern . The number of spots per cell in the Δ5DGC strain was not completely diminished , and we speculate that a low level of c-di-GMP is still present in the cell due to remaining DGCs , which facilitate VpsT localization . Alternatively , a range of VpsT target promoters that differ in their affinities for the active regulator could cause this localization pattern . Above observations of VpsT localization and activity suggest that VpsT function is dependent on reaching a critical cellular c-di-GMP threshold . Thus we wondered whether a single DGC could rescue vpsL expression in the Δ5DGC strain . When cdgA was expressed on a plasmid in the Δ5DGC mutant , vpsL expression was recovered in the Δ5DGC strain when compared to the Δ5DGC mutant harboring the vector alone ( Figure S3 ) . These results suggest that one DGC can rescue a cellular level of c-di-GMP for the activation of vpsL expression in the Δ5DGC strain . In our survey of DGC and PDE mutants , we also observed multiple PDEs to be negative regulators of vps expression ( Figure S2 ) , consistent with previous work [26] , [28]–[30] . However , strains harboring deletions of three of these genes encoding PDEs , mbaA , rocS and cdgC individually or in combination , exhibited no significant alteration in GFP-VpsT localization pattern ( Figure S4 ) . Therefore , an upper c-di-GMP concentration limit may exist , after which , further VpsT localization is not observable . Alternatively , the experimental system might be saturated , and no further localization can be observed . VpsT as a response regulator is not unique in its capacity to subcellularly localize in response to specific stimuli or modification . CsgD from Salmonella enterica was shown to form foci associated with the membrane in a subpopulation of cells in response to cell aging [31] . WspR from Pseudomonas aeruginosa was shown to localize to foci in response to phosphorylation [32] . OmpR from Escherichia coli subcellularly localizes in response to the presence and activity of its cognate histidine kinase , EnvZ [33] . Whereas typical response regulators , such as OmpR , are activated by a single major cognate histidine kinase [34] , VpsT localization and activity is modulated in response to c-di-GMP produced by multiple DGCs . These results are consistent in the context of second messenger signaling , where multiple independent inputs can be fed through a single diffusible signaling molecule to elicit a specific cellular response [1] . It is proposed that the subcellular compartmentalization of c-di-GMP signaling components might allow c-di-GMP to act locally on specific cellular processes such as motility or biofilm formation [5] , [35] . C-di-GMP signaling proteins could exert their effects by participating in complexes that include signal producers ( DGC ) , removers ( PDE ) , receptors , and/or targets [3] , [6] . To determine if co-localization occurs between DGCs activating VpsT and the c-di-GMP receptor , VpsT , we analyzed their subcellular localization . We chose CdgA and CdgH , two DGCs that affect vps expression ( Figure 1D ) and have demonstrated DGC activity ( Shikuma and Yildiz , unpublished data ) [14] . To observe the subcellular localization of CdgA and CdgH we constructed C-terminal tagged CdgA-GFP and CdgH-GFP fusions . Both cdgA-gfp and cdgH-gfp were able to complement in-frame deletions of cdgA and cdgH , respectively ( Figure S5 ) , indicating that our fusion proteins are functional . When observed by fluorescence microscopy , CdgA-GFP and CdgH-GFP both appeared to localize to the cell membrane ( Figure 2A ) . Consistent with these results , both CdgA and CdgH are predicted to contain 2 and 1 transmembrane domains , respectively [36] . To corroborate these results , we performed cellular fractionation and western blot analysis to identify the subcellular location of VpsT , CdgA and CdgH . We therefore created strains containing an N-terminal HA tagged vpsT , a C-terminal HA tagged cdgA or a C-terminal HA tagged cdgH in their native chromosomal loci . Strains containing each fusion protein exhibited similar vpsL expression when compared to wild type ( Figure S5 ) . Both CdgA-HA and CdgH-HA localized to the total membrane fraction , as predicted ( Figure 2B ) . In contrast , HA-VpsT localized mostly to the cytoplasmic fraction , but a lower level also consistently appeared in the total membrane fraction . To determine whether VpsT localization is dependent on the presence of specific DGCs or c-di-GMP levels , we performed a cellular fractionation of wild-type and Δ5DGC strains and probed for HA-VpsT levels . HA-VpsT localization was not different between wild-type and Δ5DGC strains ( Figure S6 ) , suggesting that the 5 DGCs or c-di-GMP levels are not important for the localization of VpsT to specific cellular fractions . Although VpsT resides mainly in a different subcellular region of the cell when compared to CdgA or CdgH , it is possible that transient interactions between these proteins contribute to specificity in c-di-GMP signaling . To address whether VpsT can interact with CdgA or CdgH directly , we performed a bacterial two-hybrid analysis using a system suited to identify protein-protein interactions , even under the condition where one or both proteins are membrane bound [37] . Using bacterial two-hybrid vectors , VpsT , CdgA and CdgH were fused to the T18 or T25 complementary fragments of Bordetella pertussis adenylate cyclase ( CyaA ) . Interaction between co-expressed proteins of interest in E . coli reconstitute a functional CyaA , leading to cAMP production [38] . As expected , a signal indicative of interaction of VpsT with itself was observed by colorimetric blue production on LB agar containing bromo-chloro-indolyl-galactopyranoside ( X-gal ) , as well as quantitatively using β-galactosidase assays ( Figure 2C and S7 ) . Interaction of CdgA with itself and CdgH with itself was also observed ( Figure 2C and S7 ) . These results were expected as DGCs from other bacteria were shown previously to catalyze c-di-GMP production as dimers [39] , [40] . Interestingly , E . coli containing CdgA and CdgH on complementary plasmids exhibited increased β-galactosidase production , suggesting that these DGCs might interact , however the physiological relevance of this observation is unclear at this point . Importantly , strains expressing both VpsT and CdgA or VpsT and CdgH did not exhibit increased cAMP production , even when the reciprocal exchange of fusion domains was performed ( Figure 2C and S7 ) . These results suggest that VpsT does not interact directly with CdgA or CdgH . We next wondered whether VpsT localization is dependent on specific domains and/or interfaces important for VpsT function . Mutations in residues required for c-di-GMP binding ( VpsTR134A ) or c-di-GMP-stabilized dimerization ( VpsTI141E ) were unable to complement a ΔvpsT mutation ( Figure 3A ) , consistent with our previous findings [21] . When observed by fluorescence microscopy , both GFP-VpsTR134A and GFP-VpsTI141E mutants exhibited a homogenous fluorescence throughout the cytoplasm , possessed almost no spots per cell , and showed a significantly lower maximum to average fluorescence intensity ratio when compared to strains expressing a wild-type GFP-VpsT fusion ( Figure 3B , 3C and S8 ) . VpsT contains a C-terminal helix-turn-helix ( HTH ) DNA binding domain and H193 of VpsT aligned with other histidine residues in the LuxR/FixJ superfamily shown previously to be required for DNA binding ( Figure S8 ) [41] , [42] . A strain harboring GFP-VpsTH193A was unable to induce vps expression ( Figure 3A ) and appeared to localize to foci that were more dispersed throughout the cell when compared to wild type GFP-VpsT ( Figure 3B ) . The number of spots per cell and the ratio of maximum to average fluorescence intensity of the GFP-VpsTH193A expressing strain were decreased compared to wild-type GFP-VpsT ( Figure 3C and S8 ) . Therefore , VpsT localization , albeit different than that of the wild-type localization pattern , can still occur in the absence of DNA binding . The subcellular localization patterns were not due to differential protein levels , as cellular concentrations of wild-type GFP-VpsT were similar to GFP-VpsT with R134A , I141E or H193A point mutations ( Figure S8 ) . Taken together , our results indicate that the wild-type VpsT localization pattern is dependent on c-di-GMP binding and DNA binding . These results suggest that VpsT forms oligomers on DNA binding sites distributed on the V . cholerae chromosomes and the localization pattern is due to binding of VpsT to its target sequences on the genome . To determine whether there are other factors responsible for VpsT localization in V . cholerae , we expressed GFP-VpsT in E . coli . GFP-VpsT was surprisingly homogenous throughout the cytoplasm when expressed in E . coli in contrast to the same construct expressed in V . cholerae ( data not shown ) , suggesting that the localization of VpsT requires cellular components or a cellular environment provided by the V . cholerae cell . We then hypothesized that the localization of VpsT might either require increased levels of c-di-GMP or specifically require a DGC important for biofilm formation in V . cholerae . A compatible plasmid that expresses cdgA from an IPTG inducible promoter was therefore introduced into E . coli containing GFP-VpsT . Strains expressing CdgA showed a marked decrease in motility when compared to strains containing vector alone ( Figure 4C ) , indicating that CdgA is functional as a DGC in E . coli . When observed by fluorescence microscopy , GFP-VpsT formed foci in the presence of CdgA in E . coli ( Figure 4A ) . This strain exhibited an increase in the number of spots per cell and a significantly increased ratio of maximum to average fluorescence intensity compared to a strain with GFP-VpsT and an empty compatible plasmid ( Figure 4A , 4B and S9 ) . To determine whether VpsT localization is dependent on the catalytic activity of CdgA , we also expressed CdgA containing a point mutation converting the conserved GGDEF motif to GADEF ( cdgAG287A ) in cells also expressing GFP or GFP-VpsT . Expression of CdgAG287A in E . coli was not able to recover VpsT localization , in contrast to wild type CdgA ( Figure 4A , 4B and S9 ) . Furthermore , the motility zone diameter of a strain expressing CdgAG287A was similar to that of a strain with vector alone ( Figure 4C ) . As expected , strains expressing GFP alone with the same compatible plasmids showed no localization pattern ( Figure 4A , 4B and S9 ) . These results suggest that the catalytic activity of CdgA as a DGC is required for VpsT localization . We show above that the wild-type VpsT localization in V . cholerae is dependent on an intact DNA binding domain . To test whether VpsT requires DNA binding in E . coli , we expressed GFP-VpsT with a plasmid harboring the vpsL promoter ( vpsLp ) . However , this strain did not exhibit a VpsT localization pattern ( Figure 4A , 4B and S9 ) . To determine whether VpsT requires both CdgA and a native DNA binding region , we expressed GFP-VpsT in cells containing a plasmid with both cdgA and the vpsL promoter . In this strain , GFP-VpsT appeared to form a more discrete pattern , exhibited an increased number of spots per cell , and a higher maximum to average intensity ratio when compared to GFP-VpsT cells co-expressing only CdgA ( Figure 4A , 4B and S9 ) . E . coli co-expressing GFP alone with the same compatible plasmids showed no localization pattern ( Figure 4A , 4B and S9 ) . To further determine whether GFP-VpsT activity requires c-di-GMP in E . coli , we quantified the expression of vpsL in the presence and absence of CdgA . Only E . coli co-expressing GFP-VpsT and CdgA activated vpsL expression while a strain expressing only GFP-VpsT did not show vpsL activation ( Figure 5 ) . These results suggest that VpsT localization is enhanced by DNA binding and requires elevated c-di-GMP levels to activate gene expression . We then wondered whether CdgA , as a V . cholerae DGC , is required for VpsT localization or if a heterologous DGC could induce VpsT to localize . We therefore expressed adrA , a previously characterized gene encoding a DGC from Salmonella typhimurium [43] , in strains also containing GFP or GFP-VpsT . Strains expressing AdrA showed a marked decrease in motility ( Figure 4C ) , indicating that AdrA is functional in E . coli . In E . coli , AdrA caused GFP-VpsT to localize to foci , similar to foci induced by CdgA ( Figure 4A , 4B and S9 ) . As expected , co-expression of GFP and AdrA showed no localization . These results indicate that VpsT localization depends on the cellular level of c-di-GMP , and not on the presence of a specific V . cholerae DGC . Altogether , our results suggest that a direct interaction is not required for c-di-GMP signal transduction between DGCs and c-di-GMP receptors . Recently , the subcellular localization of other c-di-GMP receptors was found to be dependent on c-di-GMP binding . C-di-GMP controls the subcellular localization of the PilZ domain containing c-di-GMP receptor YcgR in E . coli , where interaction of a YcgR-c-di-GMP complex with the flagellar motor leads to decreased motility and counter-clockwise rotational bias [8]–[10] . Moreover , multiple DGCs were shown to contribute additively to these motility phenotypes [8] . In Caulobacter crescentus , c-di-GMP binding to a conserved I-site of PopA mediates the sequestration of this protein to the cell pole , where PopA facilitates cell cycle progression [44] . No single deletion of a GGDEF or EAL domain containing protein was sufficient to alter PopA localization [44] . However , the combined activity of two DGCs , PleD and DgcB , was shown to alter cell cycle dynamics [45] . The subcellular localization of YcgR and PopA appears to be modulated by the additive activity of multiple DGCs in combination , similar to our findings with VpsT . This study is the first account of the subcellular localization of a c-di-GMP binding transcriptional regulator . Results presented here suggest that adequate levels of c-di-GMP contributed by multiple DGCs modulate VpsT activity and not a physical interaction or compartmentalization of c-di-GMP signaling components ( Figure 6 ) . This study identifies the requirements for signal transduction , localization and activity of a c-di-GMP receptor protein and furthers our understanding of the mechanisms of second messenger signaling .
The bacterial strains and plasmids used in this study are listed in Table S1 . In-frame deletion , chromosomal fusion and point mutation strains were generated according to previously published protocols [46] . All V . cholerae and E . coli strains were grown aerobically , at 30°C and 37°C , respectively , unless otherwise noted . Growth medium consisted of LB media ( 1% Tryptone , 0 . 5% Yeast Extract , 1% NaCl ) , pH 7 . 5 . LB-agar and soft agar plates contained 1 . 5% and 0 . 3% ( wt/vol ) granulated agar ( Difco ) , respectively . Concentrations of antibiotics used , where appropriate , were as follows: ampicillin ( 100 µg/ml ) , rifampicin ( 100 µg/ml ) , chloramphenicol ( E . coli 20 µg/ml , V . cholerae 5 µg/ml ) , kanamycin ( 50 µg/ml ) and gentamicin ( 30 µg/ml ) . All strains were verified by PCR . Plasmid sequences were verified by DNA sequencing by Sequetech Corporation ( Mountain View , CA ) . Primers used in the present study were purchased from Bioneer Corporation ( Alameda , CA ) and sequences are available upon request . V . cholerae cells harboring the indicated plasmid were grown overnight ( 15 to 17 h ) aerobically in LB medium supplemented with ampicillin . Cells were then diluted 1∶1000 in fresh LB medium and grown aerobically for 2 h , at which point arabinose was added at a final concentration of 0 . 05% and cells were harvested at exponential phase 2 h later ( optical density at 600 nm ( OD600 nm ) of 0 . 2 to 0 . 4 ) . E . coli cells containing the indicated plasmid were grown overnight in LB medium containing 2% glucose , kanamycin and ampicillin . Cells were then diluted 1∶50 in fresh LB medium containing 0 . 1% arabinose and 100 µM IPTG and cells were harvested 3 h later . Cell culture was spotted onto 1% agarose pads prepared with phosphate-buffered saline ( PBS ) , pH 7 . 4 . Images were acquired using a Zeiss Axiovert 200 microscope equipped with a 63× Plan-Apochromat objective ( numerical aperture , 1 . 4 ) , and were recorded with a Cool-Snap HQ2 camera ( Photometrics ) . Images were minimally processed using Adobe Photoshop 11 . 0 and ImageJNIH software . MicrobeTracker [25] was employed , using the alg4ecoli parameter to identify cell outlines , the spotFinderZ tool to determine the number of spots per cell and the intprofile tool to determine the maximum and average fluorescence intensities of single cells . Data were acquired from at least 3 independent experiments and quantification was performed on at least 150 cells per treatment . All statistics were calculated using Graphpad Prism 4 . Overnight cultures were diluted 1∶200 , grown to an OD600 nm of 0 . 3 to 0 . 4 , and diluted again 1∶200 . Cells were harvested at an OD600 nm of 0 . 3 to 0 . 4 by centrifugation ( 10 , 000× g ) and fractionation was carried out as described previously [47] . Protein levels were quantified using a bicinchoninic acid ( BCA ) kit ( Thermo Fisher Scientific Inc . ) and normalized between fractions . Proteins were separated on a 12% SDS-polyacrylamide gel and electroblotted onto a nitrocellulose membrane with a Mini Trans-Blot Cell ( Bio-Rad ) as described previously [47] . Rabbit polyclonal antiserum against V . cholerae OmpU ( provided by K . Klose ) was used at a dilution of 1∶100 , 000 . Mouse monoclonal antibody against GFP ( Santa Cruz Biotechnology ) and rabbit polyclonal antibody against the HA epitope ( Santa Cruz Biotechnology ) were used according to the manufacturer's instructions . Horseradish peroxidase-conjugated goat anti-rabbit secondary antibody ( Santa Cruz Biotechnology ) or goat anti-mouse secondary antibody ( Santa Cruz Biotechnology ) was used according to the manufacturer's instructions . Immunoblot analyses were conducted with at least three biological replicates . β-galactosidase assays were performed and Miller units calculated as described previously [48] . The assays were repeated with three biological replicates and six technical replicates . V . cholerae or E . coli cells harboring the indicated plasmid were grown overnight ( 15 to 17 h ) aerobically in LB medium supplemented with the appropriate antibiotics . Cells were then diluted 1∶1000 in fresh LB medium and harvested at exponential phase at an OD600 nm of 0 . 3 to 0 . 4 . E . coli were grown in the presence of 0 . 1% arabinose and 100 µM IPTG for protein expression . Luminescence was measured using a Victor3 Multilabel Counter ( PerkinElmer ) and Lux expression is reported as counts min−1 ml−1/OD600 nm . Assays were repeated with at least three biological replicates and four technical replicates . Cellular c-di-GMP levels were measured in the indicated strains grown to exponential phase in LB medium . Protein concentration was determined using a BCA kit according to the manufacturer's instructions . C-di-GMP extraction , analysis by high-performance liquid chromatography-tandem mass spectrometry ( HPLC-MS/MS ) and c-di-GMP standard curve generation were carried out as described previously [26] . C-di-GMP quantification was performed with at least three biological replicates . Bacterial two-hybrid assays were performed as described previously [38] . Translational fusions were created with proteins of interest and T18 or T25 fragments of B . pertussis adenylate cyclase ( CyaA ) . All constructs were confirmed by DNA sequencing . Plasmids pKT25-zip and pUT18C-zip , each containing translational fusions to the leucine zipper of GCN4 , were used as positive controls . Production of cAMP by reconstituted CyaA was observed in the E . coli strain BTH101 , lacking a native cyaA gene . Protein-protein interactions were observed by growing cells for 48 to 72 h at 30°C on LB agar containing ampicillin ( 100 µg/ml ) , kanamycin ( 50 µg/ml ) , X-gal ( 40 µg/ml ) and IPTG ( 10 to 500 µM ) , or quantified by performing β-galactosidase assays with cells grown overnight at 30°C in LB medium containing ampicillin ( 100 µg/ml ) , kanamycin ( 50 µg/ml ) and IPTG ( 10 µM ) . GenBank accession numbers are as follows: VpsT , NP_233336 . 1; VpsL , NP_230581 . 1; CdgA , NP_232475 . 1; CdgH , NP_230712 . 1; CdgK , NP_230749 . 1; CdgL , NP_231916 . 1; CdgM , NP_231020 . 1; MbaA , NP_230352 . 1; RocS , NP_230302 . 1; CdgC , NP_233171 . 1 .
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C-di-GMP is a ubiquitous intracellular signaling molecule in bacteria and controls diverse cellular processes including biofilm formation , motility and virulence . The genomes of many bacteria often contain numerous genes encoding proteins predicted to produce and degrade c-di-GMP . However , it is currently unclear how a bacterial cell orchestrates multiple c-di-GMP signaling proteins to elicit a specific cellular response . The microbial pathogen , Vibrio cholerae , contains a multitude of c-di-GMP proteins and c-di-GMP signaling is likely important for the bacterium to cause the deadly diarrheal disease called cholera . In the present study , we define the requirements for c-di-GMP signal transduction in V . cholerae . We identify specific c-di-GMP proteins that additively stimulate the subcellular localization and activity of the c-di-GMP binding protein and transcriptional regulator , VpsT . We further show that c-di-GMP signaling does not require the interaction of c-di-GMP signaling components . However , a common cellular level of c-di-GMP contributes to VpsT localization and activity . This is the first account of the subcellular localization of a transcriptional regulator modulated by c-di-GMP binding . Furthermore , this study establishes that c-di-GMP signal transduction can act at a distance through a common cellular level of c-di-GMP and defines how an intracellular second messenger can regulate cellular processes in bacteria .
|
[
"Abstract",
"Introduction",
"Results/Discussion",
"Materials",
"and",
"Methods"
] |
[
"genetics",
"biology",
"microbiology",
"genetics",
"and",
"genomics"
] |
2012
|
Cellular Levels and Binding of c-di-GMP Control Subcellular Localization and Activity of the Vibrio cholerae Transcriptional Regulator VpsT
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Mechanisms that generate transcript diversity are of fundamental importance in eukaryotes . Although a large fraction of human protein-coding genes and lincRNAs produce more than one mRNA isoform each , the regulation of this phenomenon is still incompletely understood . Much progress has been made in deciphering the role of sequence-specific features as well as DNA-and RNA-binding proteins in alternative splicing . Recently , however , several experimental studies of individual genes have revealed a direct involvement of epigenetic factors in alternative splicing and transcription initiation . While histone modifications are generally correlated with overall gene expression levels , it remains unclear how histone modification enrichment affects relative isoform abundance . Therefore , we sought to investigate the associations between histone modifications and transcript diversity levels measured by the rates of transcription start-site switching and alternative splicing on a genome-wide scale across protein-coding genes and lincRNAs . We found that the relationship between enrichment levels of epigenetic marks and transcription start-site switching is similar for protein-coding genes and lincRNAs . Furthermore , we found associations between splicing rates and enrichment levels of H2az , H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H3K9me3 , H3K27ac , H3K27me3 , H3K36me3 , H3K79me2 , and H4K20me , marks traditionally associated with enhancers , transcription initiation , transcriptional repression , and others . These patterns were observed in both normal and cancer cell lines . Additionally , we developed a novel computational method that identified 840 epigenetically regulated candidate genes and predicted transcription start-site switching and alternative exon splicing with up to 92% accuracy based on epigenetic patterning alone . Our results suggest that the epigenetic regulation of transcript isoform diversity may be a relatively common genome-wide phenomenon representing an avenue of deregulation in tumor development .
Molecular processes such as alternative splicing and transcription start-site switching are primary drivers of transcript diversity . About 95% of the ∼23 , 000 human genes are estimated to produce more than one mRNA isoform [1] . Beyond the genes with protein-coding potential , recent discoveries suggest that the approximately 8 , 000 large intergenic noncoding RNAs ( lincRNAs ) found in the human genome generate on average 2 . 3 isoforms per lincRNA locus [2] . The analysis of transcript diversity regulation has traditionally focused on splicing factors and RNA sequence features such as splicing enhancers and silencers [3] , [4] . In recent years , however , experimental studies have expanded to include other regulatory factors such as histone modifications , suggesting that epigenetic features may have the ability not only to determine when and in which tissues certain genes are expressed , but also to influence how these transcripts are processed . Genome-wide analyses indicate that nucleosomes and histone modifications are not randomly distributed , but often coincide with exon boundaries [5]–[7] . This observation , combined with recent evidence that most events of alternative splicing in human cells occur co-transcriptionally [8] , [9] , strongly suggest a regulatory potential of histone marks [2] , [10] . While the connection of epigenetic regulation with overall gene expression has largely been elucidated [11]–[14] , it is much less clear whether and how epigenetic marks determine relative isoform abundance . Qualitative and quantitative models have been built to predict expression on the level of genes using histone modification enrichment information alone [15] . Interestingly , a quantitative prediction model based on histone modification enrichment outperforms models based on transcription factor binding [15] . However , a systematic evaluation of the association of epigenetic marks with transcription start-site switching and splicing frequency is still lacking in the literature . Work by Ernst et al . [16] , [17] , who classified chromatin states to functionally annotate the genome , identified a combination of histone modifications , which were associated with transcription start site and spliced exons . However , since in this work , the histone mark ChIP-seq tag counts were processed into binary presence and absence calls and since isoform abundance was not estimated from the expression data , the critical question remains whether different levels of epigenetic enrichment are associated with the rates of transcription start-site switching and splicing . In addition to elucidating the epigenetic regulation of transcript diversity , further open questions remain . These questions pertain for instance to the genome-wide prevalence of epigenetic regulation of transcript diversity generated via alternative splicing or transcription start-site switching . Furthermore , it is unclear to what extent the involvement of epigenetic marks in the regulation of transcript diversity is gene-specific , ie . whether individual genes respond to different histone marks or whether there is a “universal” set of marks for alternative splicing . Several studies aimed at deciphering the association between histone modifications and alternative splicing on a genome-wide scale [18]–[22] but relied solely on gene annotation for the assignment of alterative splicing events rather than on a comprehensive transcription analysis [22] , or with no more than three cell lines lacked the breadth of conditions analyzed [18] , [19] , [21] . Finally , the association of epigenetic patterning with transcript diversity in cancer cells has not been analyzed methodically in a genome-wide manner; however , understanding the prevalence of this phenomenon is of particular importance in cancer where cells are known to undergo vast epigenetic aberrations [23] . Indeed , epigenetically divergent regions in cancer cell lines are enriched for cancer-associated genes ( Module S1 in Text S1 ) . Here , we sought to perform a detailed study investigating the association between histone modification enrichments and the processes that influence isoform abundance – transcription start-site switching and splicing – on a genome-wide level ( Fig . 1A and Table 1 ) . We further developed a novel approach that identified a set of 840 genes for which transcription start-site switching and splicing was strongly associated with at least one epigenetic mark . We also showed that histone modification enrichment alone can predict exon splicing and transcription start-site switching with up to 92% accuracy in an independent sample set . Our work strongly suggests a broad-scale involvement of epigenetic factors in transcription start-site switching and alternative splicing .
We examined RNA-seq data from nine human cell lines ( Gm12878 , Hsmm , Huvec , Hepg2 , Helas3 , K562 , H1hesc , Nhek , Nhlf ) ( http://genome . ucsc . edu/ENCODE/ ) , of which six were normal ( Gm12878 , Hsmm , Huvec , H1hesc , Nhek , Nhlf ) and three were cancer cell lines ( Hepg2 , Helas3 , K562 ) . For all nine cell lines , we obtained information of the genome-wide patterns of the following twelve histone marks: H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H3K9me1 , H3K9me3 , H4K20me1 , H3K27ac , H3K27me3 , H3K36me3 , H3K79me2 , H2az . Our analysis of the association between histone enrichment and transcript diversity utilized two different approaches: ( i ) a genome-wide approach , and ( ii ) an exon-specific approach . The genome-wide method analyzes each cell line individually and investigates all exons with a given characteristic ( i . e . spliced , not spliced , transcription start site exon , etc . ) at once , irrespective of the gene of origin . The exon-specific approach , in contrast , analyzes one exon at a time across multiple cell lines . The latter approach is able to identify candidate exons or genes with potential epigenetic regulation of transcription diversity and is analogous to an experimental setup in which each cell line represents an experimental condition ( i . e . varying levels of histone modification enrichment ) resulting in a particular exon inclusion or transcription start site outcome . The genome-wide approach requires a set of assumptions ( see Discussion section ) ; however , due to the large sample size of exons , it may uncover associations that would otherwise not be significant at a single gene level . With sufficiently many samples and sequencing depth , the patterns of associations uncovered by both approaches converge . To assess the level of transcript diversity in the human genome , we analyzed RNA-seq data from nine human cell lines and quantified the abundance of specific mRNA isoforms for each protein-coding gene and lincRNA . We mapped and assembled the transcriptome of each cell line using the TopHat2 and Cufflinks2 softwares [24] , [25] , respectively , using merged UCSC reference annotation with lincRNA annotation from Cabili and colleagues [2] as a set of assembly models ( see Methods ) . In order to minimize confounding issues , for instance with the misalignment of RNA-seq reads , we excluded paralogs that were more than 95% identical on the DNA sequence level . Exons were grouped into four categories: transcription start site , internal , transcription end site , or overlapping exons . Only internal and transcription start site exons were used for further analysis . The level of expression of an internal and transcription start site exon was quantified by calculating the splicing exon inclusion rate ( SEIR , ranging from 0 to 1 ) and transcription start site inclusion rate ( TSSIR , ranging from 0 to 1 ) respectively , both of which reflect the proportion of transcripts containing a given exon at a given gene locus ( Fig . 1B ) . An SEIR of 0 implies that a given exon is always spliced in all expressed isoforms of a gene , whereas an SEIR of 1 implies that a given exon is always retained . A TSSIR of less than 1 signifies that a given exon occasionally represents the first exon of an expressed isoform , whereas a TSSIR of 1 indicates that a given exon serves as the transcription start site for all expressed isoforms . The SEIR and TSSIR measures therefore identify exons contributing to transcript diversity of a given gene . We hypothesized that , if histone modification enrichment patterns play a significant role in transcript diversity , then the levels of transcription start-site switching and splicing should correlate with the enrichment levels of certain histone modifications within each cell line analyzed . We therefore investigated the transcriptome-wide association between histone mark enrichment and TSSIR and SEIR within each cell line . To address the possibility that transcript diversity in cancer cell lines is regulated differently as compared to that in normal cell lines , we quantified the level of association in the normal cell lines first and then assessed the degree of similarity in this pattern between normal and cancer cell lines . To this end , we determined the expression profiles as well as histone modification enrichment for all annotated exons of protein-coding genes and lincRNAs in the normal cell lines ( Methods ) . Out of the twelve histone marks examined , seven ( H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H3K27ac , H3K79me2 , and H2az ) showed a strong positive association with transcription start-site switching for both protein-coding genes and lincRNAs ( Fig . 1C and 1D ) . Although the involvement of H3K4me2 and H3K4me3 , H3K9ac , and H3K27ac in transcription initiation was expected given the findings of previous studies [16] , [17] , the presence of H3K79me2 and H2az was not anticipated . These results suggest that the transcription initiation of both protein-coding genes and lincRNAs is probably regulated via similar molecular mechanisms . The transcription profiles of the nine cell lines revealed that many protein-coding genes as well as lincRNAs undergo alternative splicing . Given the fact that transcription start-site switching occurs in a similar epigenetic background for protein coding genes as well as lincRNAs , we then sought to investigate whether splicing in protein-coding genes and lincRNAs is also associated with a similar set of histone marks . We found that splicing in protein-coding genes was most strongly positively correlated with the enrichment of H3K36me3 and negatively correlated with H3K4me2 and H3K4me3 ( Fig . 2A ) . H3K36me3 has been previously found to mark actively transcribed regions and to regulate the splicing of FGFR2 [26] , thus confirming our results . However , splicing of lincRNAs did not reveal any association with histone mark enrichment ( Fig . 2B ) , suggesting that splicing of non-coding RNAs is either independent of the epigenetic background , involves sequence-specific regulation , and/or occurs post-transcriptionally . We then aimed to investigate whether this pattern was consistent when taking into account exon number per gene , gene expression patterns , and genomic features such as simple repeats , microsatellites , and conserved elements . Controlling for these factors , the correlations between TSSIR and H3K4me2 as well as H3K9ac were very robust , varying for instance in the Gm12878 cell line between 0 . 35<ρ<0 . 37 for H3K4me2 ( uncontrolled correlation ρ = 0 . 37 ) and between 0 . 35<ρ<0 . 38 for H3K9ac ( uncontrolled correlation ρ = 0 . 37 ) . Similarly , controlling for H3K9ac enrichment reduced the correlation between TSSIR and H3K4me2 by only 0 . 5% , and controlling for H3K4me2 enrichment reduced the correlation between TSSIR and H3K9ac by only 3 . 18% . These observations suggest that , while the interplay between transcript diversity and epigenetics probably involves many other factors , which might occlude the signal , the association between the SEIR and specific histone marks is genuine . Recently , a study examining the alternative splicing of CD45 showed that molecular interactions as far as 1 kb downstream of exon 5 affected its inclusion rate [27] . To investigate how epigenetic marks at a distance from exons influences transcript diversity on a genome-wide scale , we analyzed histone enrichment profiles at distances of 1 kb , 2 kb , and 5 kb immediately upstream and downstream of the exon locus ( Methods ) . We identified pronounced differences in spatial patterns of correlation strength between the previously identified histone marks H3K4me1 and H3K79me2 and the TSSIR of protein-coding genes in normal cells ( Fig . 1C ) . For example , the correlation between TSSIR and H3K4me1 at the exon locus was very weak ( z0 kb = 0 . 09 ) but rose to much higher levels as close as 1 kb upstream and downstream of the spliced exon ( z−1 kb = 0 . 28 , z1 kb = 0 . 28 ) ; this level of correlation was also observed for distances of 2 kb and 5 kb upstream and downstream of the exon ( z−5 kb = 0 . 22 , z−2 kb = 0 . 29 , z2 kb = 0 . 33 , z5 kb = 0 . 30 ) . Interestingly , a very different spatial pattern was observed for the histone mark H3K79me2 , for which the correlation between TSSIR and histone enrichment upstream and at the exon locus was weak ( z−5 kb = 0 . 03 , z−2 kb = 0 . 07 , z−1 kb = 0 . 08 , z0 kb = 0 . 15 ) , but became much stronger at distances of 1–5 kb downstream of the exon ( z1 kb = 0 . 26 , z2 kb = 0 . 27 , z5 kb = 0 . 26 ) . The spatial pattern of correlation between H3K4me1 enrichment and TSSIR for lincRNAs was less pronounced ( Fig . 1D ) , showing lower levels of correlation at the exon locus compared to up- and downstream regions ( z−5 kb = 0 . 17 , z−2 kb = 0 . 18 , z−1 kb = 0 . 15 , z0 kb = 0 . 13 , z1 kb = 0 . 19 , z2 kb = 0 . 20 , z5 kb = 0 . 19 ) . The only spatial pattern evident for an association between histone enrichment and SEIR was observed for H3K36me3 ( Fig . 2A ) . While the correlation outside the exon boundaries ranged from 0 . 30<z<0 . 36 , the correlation at the exon locus itself was slightly diminished to z0 kb = 0 . 26 . It remains unclear which factors drive the spatial distribution of H3K36me3; for example , Luco et al . showed that H3K36me3 interacts with the FGFR2 pre-mRNA via the MRG15/PTB chromatin-adaptor complex , which regulates the inclusion rates of alternatively spliced IIIb and IIIc exons [28] . Work by others has further showed that additional proteins can act as “chromatin-adaptors” [29]–[32] . The question remains to what extent different chromatin adaptor complexes regulate splicing and which nucleosomes they interact with . A possible explanation of why the correlation of H3K36me3 with SEIR is diminished at the exon locus may lie in the position , relative to the exon , where different chromatin adaptors assemble and interact with H3K36me3 to regulate splicing . Further complicating the situation is a recent report demonstrating opposite causality , where alternative splicing was shown to modulate the levels of H3K36me3 enrichment [33] , [34] . We observed no obvious spatial patterns between histone enrichment and splicing for lincRNAs ( Fig . 2B ) . Overall , our observations suggest that histone mark enrichment is associated with transcription start site exon inclusion and splicing and has a strong spatial signature . In addition to these analyses , we performed several control studies to establish that our results are genuine . First , our findings were robust even after controlling for gene expression , exon number , and genomic features such as simple repeats , microsatellites , and evolutionary conservation . Although the overall correlation between both TSSIR and SEIR and various histone modifications was moderate transcriptome-wide , the rapid change of correlation over short distances from exons and consistent patterns across multiple cell lines suggest an authentic relationship . Since cells accumulate many genetic and epigenetic aberrations during tumorigenesis [23] , [35]–[37] , normal and cancer cells may differ substantially in their epigenetic regulation of transcript diversity . To investigate this possibility , we studied whether the association between TSSIR , SEIR and histone modifications in cancer cell lines followed similar patterns as those observed in the normal cells . We thus repeated the analyses described above using the cancer cell line data and tested for significant differences between the results using normal and cancer cell data for both protein-coding genes as well as lincRNAs . Remarkably , protein-coding genes in cancer cell lines displayed very similar patterns of association between the TSSIR and histone modifications as normal cell lines; the histone marks H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H3K27ac , H3K79me2 , and H2az , which we previously found to be highly correlated in normal cell lines , were also highly correlated with TSSIR in cancer cells ( Fig . 2C and 2D ) . Their correlation profiles across upstream and downstream exon regions also did not significantly differ from those of normal cell lines ( T-test , 0 . 13>p>0 . 89 across all −5 kb , −2 kb , −1 kb , 0 kb , 1 kb , 2 kb , and 5 kb regions ) . Similarly , the other comparisons between normal and cancer cells , for both protein-coding genes and lincRNAs , did not show significant differences either ( see Fig . 2 , Table S1–S4 in Text S1 , and Figure S5 in Text S1 ) . These findings imply that the same histone modifications are associated with transcript diversity in both normal and cancer cells and that perturbation of the epigenetic environment via experimental manipulation in normal cells would potentially be informative of cancer cells . So far , our transcriptome-wide and within-cell line approach identified an association between TSSIR , SEIR and histone enrichment across all exons but was unable to identify individual candidate genes with epigenetically regulated transcript diversity . We thus aimed to complement our investigation with a method that analyzes each exon individually across multiple cell lines . This approach is able to determine candidate genes with potential epigenetic regulation of transcript diversity and is analogous to an experimental setup where each cell line represents an experimental condition ( i . e . varying levels of histone modification enrichment ) resulting in a particular exon inclusion outcome . For example , the gene HPS4 ( Hermansky-Pudlak syndrome gene 4 ) is expressed in all nine cell lines; its 3rd exon is always excluded ( SEIR = 0 ) in all HPS4 isoforms in H1hesc , Helas3 , Hsmm , Huvec , and Nhlf cells , but is only occasionally included ( 0 . 03<SEIR<0 . 15 ) in Gm12878 , Hepg2 , K562 , and Nhek cells ( Fig . 3 ) . Interestingly , the cell lines that always exclude this exon do not show a significant enrichment for H3K4me2 within exon boundaries ( Fig . 3 ) , whereas the remaining cell lines do and the difference between these two groups is significant ( T-test , FDR-corrected p<0 . 003 , Methods ) . We thus analyzed all exons across all cell lines in a similar fashion , first only taking into account histone enrichment at the exon locus . Given the TSSIR and SEIR values across cell lines , each exon may be constitutively excluded ( TSSIR = 0 and SEIR = 0 ) , occasionally excluded ( TSSIR>0 and SEIR<1 ) , or retained ( TSSIR = 1 and SEIR = 1 ) . We then directly compared the histone modification levels for the inclusion pattern of a given exon across all available cell lines . The three possible two-way comparisons are: i ) cell lines in which a given exon is always excluded versus retained ( TSSIR = 0 vs . TSSIR = 1 or SEIR = 0 vs . SEIR = 1 ) , ii ) cell lines in which a given exon is retained versus occasionally excluded ( TSSIR = 0 vs . 0<TSSIR<1 or SEIR = 0 vs . 0<SEIR<1 ) , and iii ) cell lines in which a given exon is occasionally excluded versus retained ( 0<TSSIR<1 vs . TSSIR = 1 or 0<SEIR<1 vs . SEIR = 1 ) . Unfortunately , since the number of cell lines with available histone modification was limited , the power of this test was low . Nonetheless , given our stringent criteria ( Methods ) , we identified 840 genes for which transcript diversity was significantly associated with histone modification enrichment at the exon locus ( Supplementary Dataset S1 ) . Specifically , 399 and 473 genes displayed a significant association between splicing and transcription start-site switching , respectively . Note that a single gene can be significant for the association between epigenetic patterning and both splicing and transcription start-site switching . To understand whether obtaining 840 candidate genes was a result of chance , we performed 1000 permutations by randomly reassigning exon labels for TSSIR and SEIR while keeping the epigenetic background of a gene constant . Observing 840 candidate genes in total was significantly higher ( p<0 . 001 ) as compared to what was expected by chance ( Fig . 4 ) . These 840 genes were enriched for several GO terms ( Table S6 in Text S1 ) including the regulation of the response to stimulus and development process . Thirty three of these genes were cancer-associated genes ( Supplementary Dataset S1 ) ( http://www . sanger . ac . uk/genetics/CGP/Census/ ) . We then aimed to predict exon inclusion patterns in an independent sample set . Specifically , given the histone enrichment levels and the inclusion pattern in the nine previously studied cell lines , we sought to determine , in independent cell lines , whether a given exon was always retained ( SEIR = 1 ) , always excluded ( SEIR = 0 ) , or occasionally excluded ( 0<SEIR<1 ) with regard to splicing or transcription start-site switching ( TSSIR = 1 , TSSIR = 0 , or 0<TSSIR<1 , respectively ) . These predictions were performed in the Hmec and Monocytes CD14 cell lines , for which more complete epigenetic information became available ( http://genome . ucsc . edu/ENCODE/downloads . html ) . We limited our predictions to the 840 candidate genes identified above , since the cell lines previously analyzed provided evidence for an involvement of epigenetic marks in transcript diversity for only 840 candidate genes; attempting to predict exon inclusion based on epigenetic information for genes that are not epigenetically regulated would thus not be appropriate . To illustrate our approach , consider exon 5 of the ETV1 gene in the Hmec cell line; for this exon , we generated a matrix containing enrichment values for all histone modifications , which were significantly associated with SEIR ( in this case H3K9ac , H3K4me3 , H3K4me2 , and H3K27ac ) for the original cell line set ( Gm12878 , Hsmm , Huvec , Hepg2 , Helas3 , K562 , H1hesc , Nhek , and Nhlf ) , and identified the SEIR of this exon in each cell line . All ETV1 isoforms in Gm12878 and Hepg2 cell lines lacked exon 5 ( SEIR = 0 ) whereas some isoforms expressed in H1hesc , Hsmm , Huvec , K562 , Nhek , and Nhlf cell lines contained exon 5 ( SEIR range 0 . 43–0 . 69 ) ( Fig . 5A ) . The difference in histone enrichment between these groups was striking: the Gm12878 and Hepg2 cell lines completely lacked enrichment in H3K9ac , H3K4me3 , H3K4me2 , and H3K27ac while the remaining cell lines were strongly enriched in those marks ( Fig . 5A ) . We then calculated the pairwise Euclidean distance between all cell lines and the first validation line , Hmec , and determined the three nearest-neighbor cell lines signified by the smallest Euclidean distance ( Methods ) . Since Hmec was enriched for all four histone marks in exon 5 , its epigenetic profile was closest to that of the Nhlf , K562 , and Huvec cell lines . We therefore predicted that in Hmec , exon 5 of ETV1 was occasionally excluded from some fraction of isoforms ( 0<SEIR<1 ) , which was validated by the finding that in this cell line , SEIR = 0 . 74 . When extending this approach to all candidate genes , we predicted the correct exon inclusion category with an accuracy of 91 . 82% and 84 . 65% for Hmec and Monocytes CD14 cell lines , respectively ( Fig . 5B ) . To establish whether such high prediction accuracy can be established across all cell lines , we performed leave-one-out cross-validation following the approach described above . The accuracies for individual cell lines ranged from 72 . 1% in the Helas3 cell line to 91 . 8% in the Nhek cell line , with an average accuracy of 87 . 2% ( Fig . 6 ) . We also calculated the overall accuracy separately for splicing and for transcription start-site switching , which was 90 . 16% and 85 . 81% , respectively . Although the 0<EIR<1 vs . EIR = 1 comparison is the most frequent ( 76% ) , the accuracy for all comparisons consistently were high , at 90 . 00% , 95 . 00% , and 87 . 28% for EIR = 0 vs . 0<EIR<1 , EIR = 0 vs . EIR = 1 , and 0<EIR<1 vs . EIR = 1 , respectively . Details regarding the fraction of genes that could be assigned into comparative groups and the number of significant genes for each validation step are displayed in Table S7 in Text S1 . These findings suggest that the histone modification enrichment levels alone can be used to predict the inclusion pattern of an exon .
In this study , we analyzed the association between transcription start-site switching , spliced exon inclusion rates and histone modification patterns across multiple normal and cancer cell lines for protein-coding genes and lincRNAs . Unlike previous studies [8] , [16] , [17] , which established the relationship between epigenetic patterning and gene expression levels , we addressed the association of the epigenetic background of a gene with its transcript isoform diversity . The main difference between ours and previous investigations therefore is that our study investigates relative isoform diversity of expressed genes , and not actual expression levels . We used two approaches to address this issue . The first approach correlated transcriptome-wide ( ie “within cell line” ) transcription start site inclusion rates and spliced exon inclusion rates with histone enrichment levels . The second approach investigated gene-specific associations between transcription start site inclusion rates , spliced exon inclusion rates and histone enrichment levels . The shortcomings and assumptions made by each method are discussed below . Overall , our study led to four main findings . ( i ) The role of epigenetic patterning in transcription start-site switching is likely to be common across the genome for both protein-coding genes as well as lincRNAs . ( ii ) The role of epigenetic patterns in splicing is likely gene-specific , with the exception of H3K36me3 ( discussed below ) . ( iii ) Our gene-specific approach led to the identification of 840 candidate genes whose exon inclusion rates for transcription start-site switching and splicing were strongly associated with patterns of histone modifications . ( iv ) Lastly , histone modification data alone can be used to predict the inclusion pattern of an exon . Our first and second findings are based on the observation that both transcriptome-wide and gene-specific approaches identified a common set of histone marks that were associated with transcription start-site switching ( H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H3K27ac , and H2az ) , whereas the results of these two methods differed for the case of splicing . Transcriptome-wide analysis for splicing showed a pronounced association of splicing inclusion rates with H3K36me3 whereas the gene-specific approach identified H2az , H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H3K9me3 , H3K27ac , H3K27me3 , H3K36me3 , H3K79me2 , and H4K20me1 as significantly associated marks . This discrepancy is likely a result of a bias by the transcriptome-wide approach to detect common genome-wide trends and the gene-specific approach to identify unique relationships for each exon . Observing both common and gene-specific histone marks associated with splicing is in line with the proposed models of epigenetic regulation of splicing: the kinetic model and the chromatin-adaptor model [38] . According to the kinetic model , chromatin structure affects the elongation rate of RNA polymerase , which in turn influences the competition between weak and strong splice sites for the recruitment of splicing factors [38] . The chromatin-adaptor model , on the other hand , describes an interaction between specific histone marks and pre-mRNA molecules through a chromatin-adaptor complex , which aids in the recruitment of splicing factors to pre-mRNA splicing sites [26] , [30] , [39] . Since these two models are not mutually exclusive , one can imagine H3K36me3 , known to be associated with transcription elongation [16] , [17] , to act as a common factor in splicing genome-wide , while other histone marks can act in a gene-specific manner . Interestingly , histone marks traditionally associated with transcription initiation and transcription repression , such as H3K4me3 and H3K9me3 , respectively , were also found in our study to be associated with splicing gene-specifically . This observation is in line with experimental studies describing splicing chromatin-adaptor complex for H3K4me3 [40] and for H3K9me3 [41] . Further extending the realm of epigenetic regulation of transcript diversity is a recent work by Mercer and colleagues , which presented evidence for the role of 3-dimensional DNA conformation in splicing [42] . According to this study , exons sensitive to DNase I are spatially located close to transcription factories near promoter regions containing initiating Pol II as well as other general transcription and splicing factors . Interestingly , a large fraction of alternatively spliced exons are DNase I sensitive [42] . This finding suggests that the epigenetic background of an exon cannot only interact with splicing factors via chromatin adaptor complexes , but potentially also induce 3-dimensional DNA conformation changes that enhance the likelihood of interactions with general transcription factors , and perhaps thus influence the splicing frequency . This 3-dimensional conformation is likely enhanced via particular sets of histone modifications . Interestingly , our second analysis , testing individual exon across all cell lines , revealed that alternatively spliced exons were frequently associated with different enrichment levels of histone marks well known to be associated with promoters and enhancers , such as H3K4me1 , H3K4me2 , H3K4me3 , H3K27ac , and H3K9ac [16] , [17] ( Fig . 7 ) . Accounting for such a 3-dimensional model could further strengthen the association found between histone modification enrichment and transcription start-site switching and splicing , There are however shortcomings to both approaches . The transcriptome-wide method makes two assumptions that may be violated in cells . First , correlating transcription start site inclusion rates and spliced exon inclusion rates with histone mark enrichment assumes that ( i ) transcript diversity of all genes is associated with their epigenetic background , and additionally ( ii ) these rates are associated with the same histone modification . Likely , it is for these reasons that the correlations between exon inclusion rates and histone mark enrichment are rather moderate . As mentioned above , however , because of the rapid change of these correlations over short distances from exons and the consistent patterns across multiple cell lines , these associations suggest a genuine relationship . The shortcoming of the gene-specific approach lies in the low statistical power of eleven cell lines analyzed and the natural tendency to miss tissue specific exon behavior . This is particularly the case for lincRNAs , of which 30% , according to recent estimates , have tissue specific expression [2] . Since a large body of experimental data indicates that aberrant splicing of gene transcripts significantly contributes to many areas of cancer biology , including metabolism , apoptosis , cell cycle control , invasion and metastasis [43]–[45] , it is imperative to further our understanding of the regulatory and/or potentially disruptive role of epigenetic patterning in alternative splicing and transcription start site selection in tumorigenesis . Significant effort has been devoted to the discovery of DNA aberrations that drive cancer progression [35]–[37] , [46]; surprisingly , however , there is only a small number of recurrent genomic changes within and across cancer types , with few prominent exceptions [47]–[49] . While the identification of affected pathways rather than individual genes affected by DNA mutations might lead to more informative results , the possibility remains that aberrant phenotypes in cancer are largely driven by the epigenetic component of gene expression and transcript deregulation [23] , [50] , [51] . Our study identified several histone modifications ( H3K4me1 , H3K4me2 , H3K4me3 , H3K9ac , H4K27ac , H3K36me3 , and H3K79me2 ) that are strongly associated with transcript diversity across multiple independent cell types as well as 840 candidate genes for which there is evidence of epigenetic co-regulation of transcript diversity . Our work represents a step towards identifying the functional consequences of histone modifications on transcript diversity and suggests a rational methodology for the analysis of modern , large-scale datasets , which can be applied to any sample sets .
Exons were grouped into four categories: transcription start site , internal , transcription end site , or overlapping exons . We then quantified the presence of each exon type . Only internal and transcription start site exons were used for further analysis . The relative presence of transcription start site exons ( TSSIR – transcription start site inclusion rate ) and spliced exons ( SEIR – splicing exon inclusion rate ) was calculated from the Cufflinks . gtf output file and reflects the fraction of all isoforms from a given gene that contain a given exon . The inclusion rates therefore have ranges of 0<TSSIR≤1 and 0≤SEIR≤1 . Using raw signal read counts of histone marks and reference samples ( input DNA ) for each cell line , we calculated the presence of histone mark enrichment using a Fisher's test statistic and considered enrichment significant [17] if p<0 . 0001 . The level of enrichment was calculated as . RPKM is defined as , where r represents the number of reads mapped to a given exon , R is the total number of reads mapped , and L defines the length of a given exon . RPKM therefore denotes the number of reads per kilobase of exon per million reads mapped . Prior to further analysis , we filtered our exon set to contain only internal exons and exons of genes that express more than one isoform in at least one normal or cancer cell line . In order to avoid potential problems with mapping RNAseq reads to closely related genes , we further excluded genes with paralogs more than 95% identical on the DNA level to generate the final curated exon dataset . We then calculated the Spearman rank correlation ( which is more robust for asymmetrical distributions of TSSIR and SEIR and a large fraction of ties than Pearson's correlation ) between TSSIR and SEIR and histone enrichment values , excluding all exons for which Fisher's test for histone enrichment was not significant ( p>0 . 0001 ) . To assess the spatial patterns of correlation between histone modifications and SEIR as well as TSSIR , we calculated the extent of histone enrichment inside 1 kb , 2 kb , and 5 kb blocks immediately upstream or downstream of exons . The upstream 1 kb , 2 kb , and 5 kb regions extended from the upstream exon coordinate a given distance whereas the downstream 1 kb , 2 kb , and 5 kb regions extended from the downstream exon coordinate for a given distance . The Spearman rank correlation was then determined between each upstream or downstream block and the corresponding exon TSSIR or SEIR . To allow for direct comparisons between correlation coefficients of different cell lines and histone modifications , we transformed the Spearman p using the Fisher transformation formula , . To identify genes with epigenetically regulated transcript diversity , we analyzed each exon in the context of the nine cell lines ( Gm12878 , Hsmm , Huvec , Hepg2 , Helas3 , K562 , H1hesc , Nhek , Nhlf ) . We categorized the exon inclusion rate into three groups: SEIR = 0 , 0<SEIR<1 , and SEIR = 1 . We followed the same approach for TSSIR . Next , we tested whether any histone modification displayed a statistically significant difference in its enrichment in any possible two-group comparison , given an exon's SEIR values across the nine cell lines . For example , if the pattern of SEIR values for a given exon allowed us to separate the nine cell lines into two groups that showed either SEIR = 0 or SEIR = 1 , we used T-test to determine whether the respective histone modification enrichment among the two groups of cell lines was statistically different . All p-values were corrected for false discovery rate ( FDR ) [54] . To discover cell-specific events , we allowed for comparisons where only one cell line versus many could be assigned to an SEIR or TSSIR group . Naturally , given the lower power of this test , most of these did not pass our 5% FDR cutoff . This approach identified 840 genes , for which at least one exon showed a statistically significant association between SEIR and at least one histone modification ( ie . statistically significant difference in histone modification enrichment between two SEIR groups for a given exon ) . We limited our predictions of exon exclusion or retention in the Hmec and Monocytes CD14 cell lines to the 840 candidate genes that showed significant association between the TSSIR or SEIR and histone modification enrichment in the original set of nine human cell lines ( Gm12878 , Hsmm , Huvec , Hepg2 , Helas3 , K562 , H1hesc , Nhek , Nhlf ) . For a given exon , we constructed a Euclidean distance matrix with the formerly identified set of histone modifications for all cell lines , including Hmec and Monocytes CD14 . Next , we determined the three closest neighbors of Hmec and Monocytes CD14 from among the original set of nine cell lines ( Gm12878 , Hsmm , Huvec , Hepg2 , Helas3 , K562 , H1hesc , Nhek , and Nhlf ) . Because the exon inclusion rates for a given exon were known in the original set of nine cell lines , we separated these cell lines into three comparison groups: i ) cell lines in which a given exon was always excluded versus retained ( SEIR = 0 vs . SEIR = 1 ) , ii ) cell lines in which a given exon was retained versus occasionally excluded ( SEIR = 0 vs . 0<SEIR<1 ) , and iii ) cell lines in which a given exon was occasionally excluded versus retained ( 0<SEIR<1 vs . SEIR = 1 ) . The inclusion status - retained , occasionally excluded , or always excluded - of a given exon in the Hmec or Monocytes CD14 cell lines was then determined based on what comparison group the majority of the three closest neighbors belonged to . For example , if the majority of Hmec's three closest neighbors ( based on the Euclidian distance matrix ) belonged to the group SEIR = 1 , then we would predict that particular exon in the Hmec cell line was always retained , ie . a given gene was expressing only those isoforms that included our exon of interest . We applied the same approach to transcription start site exons and their respective TSSIR values .
|
Traditionally , the regulation of gene expression was thought to be largely based on DNA and RNA sequence motifs . However , this dogma has recently been challenged as other factors , such as epigenetic patterning of the genome , have become better understood . Sparse but convincing experimental evidence suggests that the epigenetic background , in the form of histone modifications , acts as an additional layer of regulation determining how transcripts are processed . Here we developed a computational approach to investigate the genome-wide prevalence and the level of association between the enrichment of epigenetic marks and transcript diversity generated via alternative transcription start sites and splicing . We found that the role of epigenetic patterning in alternative transcription start-site switching is likely to be the same for all genes whereas the role of epigenetic patterns in splicing is likely gene-specific . Furthermore , we show that epigenetic data alone can be used to predict the inclusion pattern of an exon . These findings have significant implications for a better understanding of the regulation of transcript diversity in humans as well as the modifications arising during tumor development .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"genomics",
"genetics",
"biology",
"and",
"life",
"sciences",
"epigenomics",
"computational",
"biology"
] |
2014
|
Histone Modifications Are Associated with Transcript Isoform Diversity in Normal and Cancer Cells
|
The current Japanese encephalitis ( JE ) vaccine derived from G3 JE virus ( JEV ) can induce protective immunity against G1–G4 JEV genotypes . However , protective efficacy against the emerging G5 genotype has not been reported . Using in vitro and in vivo tests , biological phenotype and cross-immunoreactions were compared between G3 JEV and G5 JEV ( wild strains ) . The PRNT90 method was used to detect neutralizing antibodies against different genotypes of JEV in JE vaccine-immunized subjects and JE patients . In JE vaccine-immunized mice , the lethal challenge protection rates against G3 and G5 JEV wild strains were 100% and 50% , respectively . The seroconversion rates ( SCRs ) of virus antibodies against G3 and G5 JEV among vaccinated healthy subjects were 100% and 35% , respectively . All clinically identified JE patients showed high levels of G3 JEV neutralizing antibodies ( ≥1:10–1280 ) with positive serum geometric mean titers ( GMTs ) of 43 . 2 , while for G5 JEV , neutralizing antibody conversion rates were only 64% with positive serum GMTs of 11 . 14 . Moreover , the positive rate of JEV neutralizing antibodies against G5 JEV in pediatric patients was lower than in adults . Low levels of neutralizing/protective antibodies induced by the current JE vaccine , based on the G3 genotype , were observed against the emerging G5 JEV genotype . Our results demonstrate the need for more detailed studies to reevaluate whether or not the apparent emergence of G5 JEV can be attributed to failure of the current vaccine to induce appropriate immune protectivity against this genotype of JEV .
Japanese encephalitis ( JE ) , probably the world’s most frequently occurring viral encephalitis , is a neurological infectious disease caused by Japanese encephalitis virus ( JEV ) , transmitted via mosquito bite [1] . The mortality rate of JE patients is 30–35% and 50% of JE survivors live with neurological sequelae . Therefore , JE is considered a disease with significant public health and economic burdens [2 , 3] . JE , prevalent in 24 Asia-Pacific countries , is a mosquito-borne zoonotic natural focal disease with an estimated 67 , 900 cases each year . Approximately , 30 million people live in JE-endemic areas [4] . In addition , with increased international travel and business to these areas , more people are at risk of JE infection [5 , 6] , presenting a potentially serious international public health problem . Since there is no effective therapeutic antiviral treatment , JE vaccination is the most effective prevention and control measure [7] . Studies have shown that the current vaccine derived from the G3 JEV can protect against G1–G4 JEV infections [8] . However , G5 JEV , first discovered in 1951 , has not been epidemic over the last 60 years but reemerged in 2009 and simultaneously occurred on the Asian continent in East Asia ( Korea ) and southern Asia ( Tibet ) [9 , 10 , 11] , presenting new challenges for JE prevention and control . Importantly , G5 JEV and G1–G4 JEV differ significantly in their molecular biological characteristics [12 , 13 , 14] . Nevertheless , a recent report demonstrated protective effects of the current JE vaccine against G5 JEV in animals [14] . However , whether or not humans immunized with the current G3 JEV-based vaccine can produce protective antibodies against the emerging G5 JEV is currently unknown . Moreover , it is not known if JE-infected patients have protective antibodies against G5 JEV . Here , using wild-type strains of G3 and G5 JEV genotypes , we report comparative studies of neutralizing antibody levels against G5 JEV in both JE-vaccinated subjects and clinically diagnosed JE patients .
BHK-21 cells ( newborn hamster kidney cells ) were maintained at 37°C with 5% CO2 and cultured in minimum essential medium ( MEM ) ( 11095–080 , GIBCOTM , Invitrogen , USA ) supplemented with 10% fetal bovine serum ( FBS ) ( 10099–141 , GIBCOTM , Invitrogen , Australia ) and Penicillin ( 1000 unit/mL ) -Streptomycin ( 100 μg/mL; PS ) ( 15070–063 , GIBCOTM , Invitrogen , USA ) . JEV-infected BHK cells were cultured in MEM containing 2% FBS and PS . All JEV strains used in this study were isolated from field samples using cell culture and stored at low passage level in our laboratory: Department of Viral Encephalitis and Arbovirus , Institute for Viral Disease Control and Prevention , Chinese Center for Disease Control and Prevention ( IVDC , China CDC ) . G1 JEV was GZ56 strain ( GenBank: HM366552 ) [15] , G3 JEV was P3 strain ( GenBank: JEU47032 ) [16] , and G5 JEV was XZ0934 strain ( GenBank: JF915894 . 1 ) [9] . BHK-21 cells were inoculated at a multiplicity of infection ( MOI ) of 0 . 01 and the cytopathic effects ( CPE ) of the cells were observed . Simultaneously , aliquots of the infected media were collected every 12 h and measured using plaque assays to generate a viral reproduction curve [14] . Aliquots of 10-fold diluted virus suspension ( from 10−1 to 10−6 ) were added to BHK-21 cells in 6-well plates ( 0 . 1 mL/well ) . After 1 h of adsorption at 37°C , the cells were overlaid with 1 . 3% methylcellulose-MEM medium containing 2% FBS ( 5 mL/well ) . After culturing for 3 ~ 5 days , the cells were stained with crystal violet and virus titres expressed as plaque-forming units ( pfu ) were calculated . For each virus , the diameter of 8 plaques was measured and the mean plaque size in mm and standard error ( SEM ) was calculated . Serum samples from JE-vaccinated children ( 3 mL of blood ) were collected from two-year-old children 28 days before and after vaccination SA14-14-2 JE live attenuated vaccine ( LAV ) , ( Wuhan Institute of Biological Products Co . Ltd Liability , Wuhan , China ) . Serum samples ( 5 mL of blood ) were collected from patients diagnosed with JE . All serum samples were obtained from whole blood after clotting at room temperature and centrifuged at 5 , 000 rpm for 5 min . Aliquots of serum were stored at -80°C until use . The implementation agencies of the present study were the National Reference Laboratory of Japanese Encephalitis and the World Health Organization JE Regional Reference Laboratory , China ( WHO-JE-RRL , China ) . Therefore , all the human serum samples used in this study were from those collected and maintained during the JE epidemiological monitoring period by these JE reference laboratories . All adult subjects provided written informed consent , and a parent or guardian of any child participant provided informed consent on their behalf . This research project was approved by the Ethics Committee of the IVDC , China CDC ( No . 2014112509 ) . Two kits were used to duplicate test serum samples collected from JE patients: the JE-Dengue IgM Combo ELISA ( PanBio , Brisbane , Australia ) , and the JEV IgM-Capture ELISA kit ( Shanghai B & C Enterprise Development Co . Ltd , Shanghai , People’s Republic of China ) . Methods and result interpretation were performed according to manufacturers’ instructions [17] . Both detection kits were Capture ELISA . BALB/c mice were purchased from Beijing Vital River Laboratory Animal Technology Co . , Ltd . ( quality qualifier SYXK Beijing 2012–0022 ) and were female except for the neonatal mice . All mice were housed under pathogen-free conditions at the China CDC animal facility . All animal experiments were conducted in strict compliance with the regulations set by the Animal Ethics Committee of China CDC ( No . 2014112509 ) . Serum neutralizing antibody to JEV was detected using the plaque reduction neutralization test ( PRNT ) method . The inactivated serum was diluted two-fold ( from 1:5 to 1:1280 ) and mixed with an equal volume of 200 pfu JEV , incubated in 37°C for 1 h . The mixture was then added to 6-well BHK-21 plates for 1 h followed by overlaying with 1 . 3% methylcellulose-MEM medium containing 2% FBS for 3 ~ 5 days . The plaques were stained with crystal violet and counted . Neutralizing antibody titers were calculated as the reciprocal of the highest dilution resulting in 90% plaque reduction ( PRNT90 ) compared to an unvaccinated control serum [19] . In this study , the positive cut-off value of neutralizing antibody titer was defined as PRNT90 ≧1:10 . Seropositive subjects were defined as those with a titer above or equal to the cut-off value and when negative , the result was given an arbitrary value of 5 for calculating the geometric mean titer ( GMT ) . All data were processed and drawn using GraphPad Prism 5 . 0 software ( GraphPad , La Jolla , CA , USA ) , Student’s t-tests were used for all analyses and a P-value <0 . 05 was considered statistically significant .
CPE due to virus infection showed that G5 JEV ( XZ0934 strain ) and G3 JEV ( P3 strain ) can cause BHK cells to shrink and shed ( Fig 1A ) . The plaque diameter of G5 JEV was smaller than that of G3 JEV ( Fig 1B ) . Virus infectivity generated from BHK-21 cells inoculated with MOI of 0 . 01 showed that G3 JEV and G5 JEV proliferated and reached their highest titers in 48 h and 60 h , respectively ( Table 1 and Fig 1C ) , indicating that the two viruses had substantially similar multiplication capacities in BHK-21 cells . The 1 ~ 2-day-old BALB/c neonatal mice i . c . inoculated with the two JEV genotypes ( 103 pfu/mouse; 12/group ) all died in the first 5 days . The 5 ~ 6-week-old BALB/c adult mice were i . p . inoculated with the two JEV genotypes ( 5/group ) and the LD50 of each virus was calculated to assess the virulence of JEV . The LD50 values of the G5 and G3 virus titers ( logarithmic ) were 3 . 5 and 4 . 1 , respectively , demonstrating no significant difference in virulence ( Table 1 ) . To compare the relative immunogenicities between G3 and G5 JEV , we measured the degree of cross-immunoreaction between the two JEV genotypes using PRNT . The results showed that the PRNT90 titer of G3 JEV immune serum against G3 JEV was higher than 1:320 and only 1:10 against G5 JEV . The PRNT90 titer of G5 JEV immune serum against G5 JEV was 1:40 , and 1:10 against G3 JEV ( Table 1 ) . Both JEV genotypes showed strong immunoreactions against the homologous JEV genotype , but lower cross-immunoreactions against the heterologous JEV genotypes . Mice were i . p . injected with the JE vaccine at high , medium or low dilution LAV/SA14-14-2 at 2510 pfu , 251 pfu and 25 pfu , IPV/P3 at 1:5 , 1:25 and 1:125 , respectively . After 14 days from initial immunization , they were then challenged i . p . with 500 LD50 of G5 or G3 JEV . The results showed that high and medium doses of LAV completely protected against G3 JEV challenge , but high , medium and low doses of LAV provided only a 50% protection rate against G5 JEV challenge . All IPV doses completely protected against challenge with G3 JEV , while protection rates against challenge with G5 JEV were 80% for high and medium doses in the IPV group ( 1:5 and 1:25 dilution , respectively ) and 60% in the low dose group ( 1:125 dilution; Table 1 and Fig 2 ) . In this study we compared neutralizing antibody titers against G1 , G3 and G5 JEV of 26 pairs of serum samples before and after LAV ( SA14-14-2 ) vaccination . Among the 26 serum samples collected before immunization , one showed 1:10 neutralizing antibody titer against the G1 JEV strain and two showed 1:10 against the G3 JEV strain but all were negative against the G5 JEV strain . After LAV vaccination , neutralizing antibodies against G3 JEV showed 100% positive seroconversion ( GMT = 125 . 9 ) , with the highest neutralizing antibody titer reaching 1:1280 ( Fig 3A , S1 Table ) and the seroconversion rate ( SCR; only one sample <1:10 ) was 96% against G1 JEV ( GMT = 48 . 21 ) , with the highest neutralizing antibody titer reaching 1:640 ( Fig 3B , S1 Table ) . However , only 35% ( 9/26 ) SCR ( 9 samples ≥1:10 ) was observed against G5 JEV ( GMT = 7 . 7 ) , including four samples reaching 1:10 , three samples reaching 1:20 and two samples reaching a peak antibody titer of 1:40 ( Fig 3C , S1 Table ) . In serum samples after immunization with the current JE vaccine , neutralizing antibody titers estimated using PRNT90 ( expressed as GMTs ) against G3 JEV and SCRs were analyzed and the results showed that when neutralizing antibodies against G3 JEV serum were ≥ 1:40 , SCRs against G1 JEV were as high as 100% , but none were seropositive against G5 JEV ( 0% SCRs ) . When neutralizing antibodies against G3 JEV serum were 1:160–1:320 , SCRs against G5 JEV were only 50% . Protective antibodies were produced against G5 JEV ( SCRs up to 100% ) only when the dilution of G3 JEV serum was higher than 1:320 . The results are shown in Table 2 . This study further examined levels of neutralizing antibody against G5 JEV in serum samples from clinically diagnosed JE patients . All 45 serum samples were confirmed IgM-positive when using two JEV IgM antibody detection kits . Neutralizing antibodies against G1 , G3 and G5 JEV were detected in all 45 serum samples . The results showed that neutralizing antibodies ( ≥ 1:10–1280 ) against G3 JEV were detected in all serum samples from JE patients with serum GMT of 43 . 2 . Neutralizing antibodies ( ≥ 1:10–80 ) against G1 JEV were detected in 87% ( 39/45 ) of serum samples with serum GMT of 16 . 37 . Additionally , neutralizing antibodies against G5 JEV were detected in only 64% ( 29/45 ) of serum samples with serum GMT of 11 . 14 . Evaluation of JE patient’s age and neutralizing antibodies against G5 virus showed that 41% ( 9/22 ) of JE patients 1–15 years of age and 87% ( 20/23 ) of patients over 16 years of age had positive neutralizing antibodies against G5 JEV ( Table 3 ) .
G5 JEV and G3 JEV wild-type isolates were used in this study . Comparative studies of wild strains showed that the biological characteristics of G5 JEV , such as CPE , virus titers and virus lethality to animals , were similar to those of G3 JEV . However , cross-neutralization studies showed that antigenic cross-reactivity between G3 and G5 JEV was low ( Table 1 ) and this was also reflected in the low cross-protectivity studies . A study of a G5 JEV infectious molecular clone ( the infectious molecular clone was prepared from the full-length cDNA of G5 JEV XZ0934 strain ) showed similar results [20] as did the use of G5 JEV wild strains isolated from viral JE patients in 1951 [14] . Further animal experiments also showed that the protection capacity of the current JE vaccine against G5 JEV challenge on animals was only 50% ( Table 1 ) . These results indicate that G3 and G5 JEV were significantly different in terms of their capacity to stimulate cross-protective immune responses to the heterologous virus . Our present study about molecular characterization of full-length genome of G5 JEV ( SA14-14-2 strain ) shows that G5 JEV is significantly different from that of the known G3 JEV ( SA14-14-1 ) [12] . The open reading frame ( ORF ) of G5 JEV ( 10302 nucleotides ( nt ) ) was 3 nt longer than that of G3 JEV ( 10299 nt ) , which encoding an additional amino acid ( aa ) Ser residue in the NS4A gene of G5 JEV . What is more , They share low identity of 90 . 7% in nt and 79 . 3% in aa . The envelope protein ( E protein ) encoded by the E gene plays an important role in eliciting protective neutralizing antibodies and is crucial for the neurovirulence of JEV . Except the similar 8 key aa residues in E protein for virulence of JEV , the aa identity of E protein between G5 and G3 JEV is only 89 . 6% . These heterologous differences may involve in the induction of genotype-specific neutralizing antibodies and led to poor cross-immunogenicity between heterologous G3 and G5 JEV . To date , regardless of whether attenuated or inactivated JEV vaccines are used , they are all currently based on JEV strains representing the single genotype 3 ( G3 ) [21] . Previous studies showed these vaccines can protect against G1–G4 JE virus infection [8 , 18 , 19] . In this study , PRNT90 assays were used to detect neutralizing antibodies against JE viruses in specimens collected from JE-vaccinated healthy children . The results showed that after receiving JE vaccines , SCRs of neutralizing antibodies against G3 , G1 and G5 JEV in the serum samples were 100% , 96% and 35% , respectively ( Fig 3 ) . SCRs of neutralizing antibodies against G3 and G1 JEV in this study were similar to those observed in previous research; G3 was 100% and G1 slightly lower at 97% ( 45/47 ) [8 , 18 , 19] . However , in this study , neutralizing antibodies against G5 JEV were detected in only 35% of the healthy children after they received the JE vaccination and 100% SCRs against G5 were detected only when the titer of neutralizing antibodies against G3 JEV was as high as 1: 320 ( Table 2 ) . This study is the first to report the low SCR of G5 JEV after administration of the current JE vaccine . Although a larger number of post-vaccination serum samples needs to be evaluated , the results of this study indicate that the protective efficacy of the current JE vaccine is very limited against G5 JE virus infection , regardless of the SCRs or protective neutralizing antibody titers . In this study , JEV IgM-positive serum samples ( n = 45 ) collected from clinically diagnosed JE patients were used to evaluate them for the presence of G5 JEV-specific neutralizing antibodies . The positive rates of neutralizing antibodies against G3 and G1 JEV in the serum were 100% ( 45/45 ) and 89% ( 39/45 ) , respectively . However , the positive rate of neutralizing antibodies against G5 JEV was only 64% ( 29/45 ) . Further analysis showed that the positive rates of neutralizing antibodies against G5 JEV in JE patients 1–15 years of age were 41% ( 9/22 ) and 87% ( 20/23 ) in JE patients over 15 years of age , indicating that JE patients of different ages showed different levels of G5 JEV protective antibodies . This possibly reflects the greater number of exposures to JEV in the older age-group . Additionally , in this study , the serum sample of a 9-year-old child collected on the 26th day after onset of JE ( S2 Table , the 1st case ) and serum samples of two children collected on the 11th day after onset of JE ( S2 Table , the 5th and 6th cases ) , showed detectable seroconversion antibodies against G3 JEV ( PRNT90≥1:10 ) . However , antibodies against G5 were all negative ( PRNT90<1:10 ) . These results indicate that within 11–26 days after being infected with JEV , patients failed to produce protective antibodies against G5 JEV . Therefore , pediatric patients with natural JEV infection still had significant potential risk of G5 virus re-infection . Based on our results , whether patients infected with JEV can produce protective antibodies against G5 JEV in the recovery period was inconclusive . The results did , however , imply that JE pediatric patients may not produce protective antibodies against G5 JEV after infection with non-G5 strains of JEV . JE is a vaccine-preventable disease and widespread and long-standing vaccination programmes have significantly reduced JE cases in traditional endemic areas such as Japan and Korea . However , since the discovery of the G5 virus in South Korea in 2009 [11] , JE cases in Korea have been reported yearly ( 26 in 2010 , 3 in 2011 , 20 in 2012 , 14 in 2013 and 26 in 2014 ) [22] . Moreover , six G5 JEVs have been recently detected in local Korean orientalis and Culex pipiens mosquitoes , suggesting that , in addition to the dominant Culex tritaeniorhynchus , other species of mosquito can spread G5 JEV in Korea [23] . The Chinese government included the JE vaccine in their EPI management programme in 2008 , allowing school-age children to receive the JE vaccination for free . However , thousands of JE cases still occurred yearly after 2008 [24 , 25] . Therefore , research on whether JE patients in Korea or China were related to the emerging G5 JEV infection needs to be carried out . To evaluate in detail the protective efficacy of the current JE vaccine against G5 JEV infection , increasing the surveillance of G5 JEV in vectors in endemic areas , detecting levels of G5 JEV protective antibodies across different age groups in JE-endemic areas , and finding clinical JE cases due to G5 JEV infection should be implemented .
|
The human disease Japanese encephalitis ( JE ) can be prevented by vaccination , although it is not entirely clear if the emerging JEV G5 genotype can be controlled using the vaccine based on the G3 genotype . Consequently , we systematically compared G3 and G5 cross-neutralizing immune responses in vaccinated humans and , separately , cross-protective immune responses in mice using the current G3 JE vaccine to induce the immunity . Based on these results , we propose that the current JE vaccine derived from G3 JE virus ( JEV ) does not provide adequate levels of protection against the emerging G5 JEV genotype .
|
[
"Abstract",
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"Methods",
"Results",
"Discussion"
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2016
|
Low Protective Efficacy of the Current Japanese Encephalitis Vaccine against the Emerging Genotype 5 Japanese Encephalitis Virus
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In F . graminearum , the transcriptional regulator Tri6 is encoded within the trichothecene gene cluster and regulates genes involved in the biosynthesis of the secondary metabolite deoxynivalenol ( DON ) . The Tri6 protein with its Cys2His2 zinc-finger may also conform to the class of global transcription regulators . This class of global transcriptional regulators mediate various environmental cues and generally responds to the demands of cellular metabolism . To address this issue directly , we sought to find gene targets of Tri6 in F . graminearum grown in optimal nutrient conditions . Chromatin immunoprecipitation followed by Illumina sequencing ( ChIP-Seq ) revealed that in addition to identifying six genes within the trichothecene gene cluster , Tri1 , Tri3 , Tri6 , Tri7 , Tri12 and Tri14 , the ChIP-Seq also identified 192 additional targets potentially regulated by Tri6 . Functional classification revealed that , among the annotated genes , ∼40% are associated with cellular metabolism and transport and the rest of the target genes fall into the category of signal transduction and gene expression regulation . ChIP-Seq data also revealed Tri6 has the highest affinity toward its own promoter , suggesting that this gene could be subject to self-regulation . Electro mobility shift assays ( EMSA ) performed on the promoter of Tri6 with purified Tri6 protein identified a minimum binding motif of GTGA repeats as a consensus sequence . Finally , expression profiling of F . graminearum grown under nitrogen-limiting conditions revealed that 49 out of 198 target genes are differentially regulated by Tri6 . The identification of potential new targets together with deciphering novel binding sites for Tri6 , casts new light into the role of this transcriptional regulator in the overall growth and development of F . graminearum .
Fusarium graminearum Schwabe [telemorph Gibberella zeae ( Schwein . ) Petch] is the causal agent of Fusarium head blight ( FHB ) , one of the most destructive crop diseases in temperate climes throughout the world . In addition to yield reduction , FHB is often associated with the accumulation of the secondary metabolite DON in grain [1] . DON belongs to the trichothecene family of secondary metabolites; it binds to the peptidyltransferase of ribosomes thereby inhibiting protein synthesis [2] . DON accumulates in infected plant tissues , is phytotoxic , and poses considerable health risk to consumers [3] . Although considerable effort has been expended to both detect and regulate the amount of this mycotoxin in the infected cereals , there is less information with regard to the regulation of DON biosynthesis . Our knowledge of mechanisms involved in the biosynthesis of DON and other secondary metabolites comes largely from in vitro culture studies . A considerable amount of evidence gathered over many years suggested that the physiological status of the fungus and the availability of nutrients are the main contributors for secondary metabolite production [4] , [5] . Other growth conditions such as pH have also been shown to influence the production of secondary metabolite in numerous fungi including F . graminearum [6] , [7] . Recent studies have assessed the role of various carbon and nitrogen sources in the induction of DON [5] , [8] . For example , while the products of the polyamine biosynthesis pathway such as agmatine and putrescine strongly influenced DON biosynthesis , the study also revealed negative effects of other nitrogenous compounds on the induction of DON [5] . Other studies have also demonstrated the importance of carbon sources in the regulation of DON biosynthesis [8] . Growth conditions modified by the addition of salt solutions , hydrogen peroxide , and various phytochemicals and fungicides have also been shown to influence DON production [9] . In addition to the physiological conditions , factors affecting fungal developmental also impact the synthesis of secondary metabolites [4] . In Aspergillus species , the canonical heterotrimeric G protein/cyclic AMP/protein kinase A signalling pathway involved in diverse cellular responses including cell division , morphogenesis and pathogenic development affect the production of the secondary metabolites penicillin and sterigmatocystin . For example , mutations in fadA , a gene encoding for the Gα subunit of the heterotrimeric G protein , negatively impacts aflatoxin biosynthesis [10] , [11] . Conversely , a dominant active fadA mutant inhibited expression of the transcription factor AflR , resulting in the blockage of sterigmatocystin synthesis . Interestingly , introduction of the same dominant active fadA mutant in F . sporotrichioides resulted in elevated levels of T-2 toxin , suggesting conservation of signalling pathways between filamentous fungi in the regulation of secondary metabolite synthesis [12] . This level of complexity , integrating various environmental inputs to fungal development leading to the activation of secondary metabolic gene clusters , has led to the current working model which proposes a multilevel regulation of secondary metabolism by both global and pathway-specific transcription factors [6] . In this scenario , the global transcription factors would respond and integrate disparate environmental cues such as temperature , pH and various carbon and nitrogen sources . Examples include AreA which mediates nitrogen catabolite repression in Aspergillus , and PacC which mediates pH regulation of the penicillin and trichothecene gene clusters in Aspergillus , and F . graminearum , respectively [13] , [14] . One of the characteristic features of the global regulators is that they possess Cys2His2 zinc-finger domains , important for DNA binding and regulating gene expression [6] . The pathway-specific regulators on the other hand have a characteristic Zn ( II ) 2Cys6 zinc binuclear cluster and positively regulate expression of a specific gene cluster . This is best exemplified by AflR , which regulates the sterigmatocystin biosynthetic gene cluster in Aspergillus , [15] . In F . graminearum and F . sporotrichioides , the transcriptional regulator Tri6 is encoded within the trichothecene gene cluster and regulates expression of structural genes involved in the synthesis of DON and T-2 toxin , respectively [16]–[18] . Targeted disruption of Tri6 in both Fusarium species established its role as a positive regulator of trichothecene genes [16] , [18] , [19] . Although this criterion designated Tri6 as a pathway-specific transcriptional regulator , evidence accumulated over the past few years have suggested that Tri6 may be representative of a global transcription factor whose expression is influenced by a variety of environmental factors . In addition to possessing Cys2His2 zinc-finger domains , Tri6 is influenced by the pH of the growth media and by a large range of nitrogen and carbon compounds [5] , [8] . For example , polyamines such as agmatine and putrescine induced novel genes regulated by Tri6 [20] . Additionally , expression profiling of FHB-infected tissues identified more than 200 genes that are not part of the trichothecene gene cluster differentially regulated by Tri6 [16] . This included genes in the isoprenoid biosynthesis pathway which produces farnesyl pyrophosphate , an immediate precursor for trichothecenes , and genes involved in transport and virulence [16] . These observations suggested that genes outside of the trichothecene gene cluster are subject to Tri6 regulation . To investigate the possibility that Tri6 is a global transcriptional regulator responsive to both environmental and developmental cues , a genome wide ChIP-Seq experiment was undertaken to identify potential new targets of Tri6 . Therefore , ChIP-Seq was performed with Fusarium grown in nutrient-rich conditions , a condition optimal to detect targets involved in both growth and development . We identified 198 potential new targets of Tri6 and functional categorization associated them with energy , metabolism and other cellular processes . Expression profiling of Fusarium grown in nitrogen-deprived conditions , a condition optimal for the production of trichothecenes showed that 47 of 198 targets were differentially regulated in the tri6Δ strain . The over expression of Tri6 in the tri6Δ strain confirmed that Tri6 can auto-regulate its own expression under nutrient rich conditions . Detailed analysis of the Tri6 promoter revealed a new tandem GTGA DNA binding site , located adjacent to the previously described binding site for Tri6 . This finding , together with the identification of new targets , signifies a broader regulatory role for Tri6 .
Tri6 has been defined as a pathway-specific transcription factor that regulates genes of the trichothecene gene cluster under nitrogen-deprived conditions . However , to characterize Tri6 as a global transcriptional regulator , we sought to identify targets of Tri6 by performing a genome wide ChIP-Seq in F . graminearum grown in nutrient-rich conditions . The ChIP-Seq was performed in the Tri6-HA complemented strain and was compared to the Tri6Δ strain . It should be noted that the addition of the HA epitope to the C-terminus of Tri6 did not compromise its function [21] . Moreover , the presence of Tri6 protein in the Tri6-HA complemented strain was confirmed by immunoblot blot analysis using HA antibodies ( Fig . S1A ) . ChIP DNA samples from the Tri6-HA and the Tri6Δ strains were sequenced by Illumina Genome Analyzer as 38 base tags . The software Novoalign was used to map the tags/reads to the reference genome ( F . graminearum , PH-1; NRRL 31084 ) and the software Site Identification from Short Sequence Reads ( SISSRs ) was used to identify potential binding sites [22] . A browser shot of the output from the SISSRs analysis is displayed in Fig . 1 . Among the 1491 enriched binding sites in the Tri6-HA complemented strain , we identified a total of 198 protein-coding genes with at least one binding site 1 Kb upstream of the ORF as potential targets of Tri6 , distributed in all four chromosomes ( Fig . 1 ) . The binding site was defined by a high stringent criterion with a minimum of 120 tags and the number of tags per given target is proportional to the affinity of Tri6 to its target genes [22] . This is highlighted by the substantial enrichment of region in chromosome 2 , where Tri6 is located ( dotted box , Fig . 1 ) . The 198 target genes with their tags are listed in Table S1 . The analysis of the 198 target genes by the MIPS F . graminearum FunCat database ( http://mips . helmholtzuenchen . de/genre/proj/DB/Search/Catalogs/searchCatfirstFun . html ) and Kyoto encyclopaedia of genes and genomes ( http://www . genome . jp/kegg/kegg1 . html ) categorized them into various aspects of metabolism and cellular processes ( Table 1 ) . For example , genes involved in nitrogen metabolism , such as pyridoxal decarboxylase ( FGSG_08249 ) which decarboxylates L-glutamate into GABA and ornithine aminotransferase ( FGSG_02304 ) which transaminates L-ornithine into glutamate- γ -semialdehyde were identified ( Table S2 ) [23] , [24] . Genes involved in lipid metabolism were also identified as potential targets of Tri6 . For example , triacyl glycerol lipase ( FGSG_02082 ) and acyl-CoA thioesterases ( FGSG_03286 and FGSG_02848 ) yield free fatty acids , which are used in the β-oxidation pathway to produce energy [25] . In addition , acetyl-CoA , the by-product of thioesterase activity , is assimilated into the energy generating TCA cycle ( Table S2 ) [25] . The data also revealed that Tri6 has the highest affinity towards its own promoter and to other genes of the trichothecene biosynthesis pathway , namely Tri1 , Tri14 , Tri3 , Tri12 and Tri7 ( Table 2 ) . Since the Tri genes are normally induced in nutrient-limiting conditions , the discovery of these genes as targets of Tri6 in nutrient-rich conditions suggested a new role for Tri6 . In addition to the structural genes involved in metabolism , the targets of Tri6 also included genes involved in regulatory functions and signal transduction processes ( Table S2 ) . Many of the transcription factors are classified as zinc-binding proteins and some are known to be involved in nitrogen regulation , including two genes ( FGSG_05942 and FGSG_10774 ) with NmrA domains . Genes with NmrA domains with Rossman fold structures can act as negative regulators of nitrogen catabolite repression [26] , [27] . Two members of the RAS family of GTP binding proteins ( FGSG_01649 and FGSG_06209 ) and a homologue of GIT1 , a member of the adenyl cyclase associated family of proteins ( FGSG_01923 ) , were identified as targets of Tri6 . RAS has been shown previously to regulate growth and pathogenesis in Fusarium while GIT1 in S . pombe is an essential component of the cAMP signalling pathway that primarily responds to glucose [28] , [29] . In summary , the genome-wide ChIP-Seq performed in nutrient-rich conditions identified new targets involved in various aspects of metabolism . The targets encompassed not only regulatory genes , but also genes involved in primary and secondary metabolism , energy , and transport . The analysis also identified genes of the trichothecene gene cluster . This was particularly interesting given the fact that these genes are activated only in nutrient-deprived conditions . This suggested that that under nutrient-rich conditions , Tri6 could potentially exert transcriptional control over itself and other Tri genes . The ChIP-Seq data suggested that Tri6 had high affinity to its own promoter so we were interested to know if Tri6 would bind to its own promoter and self-regulate its expression . To demonstrate that Tri6 protein binds to its own promoter , the DNA-Tri6 complex was immunoprecipitated with HA antibodies from both the Tri6Δ and the Tri6-HA complemented strains grown in nutrient-rich conditions and PCR was performed using the primers spanning the upstream region of Tri6 ORF . As shown in Fig . 2 , the primer set Tri6-Prom F/R ( Table S3 ) amplified a product of 1 . 2 kb only from the samples immunoprecipitated from the Tri6-HA complemented strain ( Lanes 1-3 , Tri6-HA , Fig . 2 ) . We could not amplify a 1 . 2 kb band in the samples immunoprecipitated from the tri6Δstrain ( Lanes 1-3 , tri6ΔFig . 2 ) , even from 25 ng of input DNA ( Lane 1 , tri6ΔFig . 2 ) . Genomic DNA was used as control to monitor the size of the PCR fragment ( Lanes 1–3 , Genomic , and Fig . 2 ) . These in vivo results validated the Chip-Seq results and indicated that Tri6p can bind to its own promoter . To demonstrate that Tri6 can bind to its own promoter and regulate its expression in nutrient-rich conditions , Tri6 expression was monitored in the wildtype strain , the tri6Δstrain , and the strain that over expressed Tri6 in the tri6 mutant background strain ( tri6ΔTri6 ) . We designed two distinct primer sets ( Table S3 ) to monitor Tri6 transcripts . The first primer set ( Tri6-ORF F/R ) was designed in the coding region of Tri6 ( vertical open box , Fig . 3A ) and as shown , over expression of Tri6 in the tri6Δ strain ( tri6ΔTri6 ) led to a significant increase of Tri6 transcripts compared to the wildtype strain ( 52±4 , Tri6-ORF , Fig . 3B and 77±7; Tri6-ORF , Fig . 3C ) . As expected , no expression of Tri6 was detected with these primers in the tri6Δstrain ( Fig . 3B and 3C ) . The second primer set was designed to overlap the 5′UTR region and the coding region of Tri6 ( Dotted vertical box , Fig . 3A ) which allowed us to monitor Tri6 transcripts originating only in the wildtype and the tri6Δstrains . As shown in the Fig . 3B and Fig . 3C , a significant increase of Tri6 expression ( Tri6-5′UTR , 4 . 4±0 . 4 , Fig . 3B and Tri6-5′UTR , 7±0 . 9 , Fig . 3C ) was observed in the tri6Δstrain , compared to the wildtype strain . However , over expression of Tri6 in the tri6Δstrain ( tri6ΔTri6 ) resulted in decreased Tri6 expression ( Tri6-5′UTR , 0 . 72±0 . 1 , Fig . 3B and Tri6-5′UTR , 1±0 . 06 , Fig . 3C ) . This suggested that Tri6 acts as a repressor , regulating its own expression in nutrient-rich conditions . We did not observe any significant change in the expression of other Tri genes in the tri6ΔTri6 strain ( tri6ΔTri6; Fig . 3B and 3C ) , suggesting that additional factors are required for the expression of these genes . A previous study performed in F . sporotrichioides suggested TNAGGCC as a DNA binding site for Tri6 protein [17] . A recent study that examined the promoters of genes differentially regulated by Tri6 during the F . graminearum infection process also suggested a similar DNA binding motif [16] . The results described here confirmed that Tri6 is able to bind its own promoter in vivo ( Fig . 2 ) and regulate its own expression ( Fig . 3 ) . Since the promoter of Tri6 ( −836 to −768 ) harbours two RNAGGCC ( where R = G or A ) binding sites ( Fig . 4A ) , we employed EMSA analyses to further delineate the binding site for Tri6 . All the EMSA assays were performed with purified recombinant Tri6 protein ( Fig . S1B ) . First , we tested the probe which contained two of the RNAGGCC motifs and as the results indicated , Tri6 did not bind to this probe ( Tri6-1 , Fig . 4B ) . This prompted us to examine the region that surrounds this motif . The probe Tri6-2 which included sequences proximal to the binding sites ( Fig . 4A ) also did not bind the Tri6p ( Fig . 4B ) . However , a probe ( Tri6-3 ) which included sequences distal to the binding sites was able to bind Tri6 protein . The specificity of the binding to the Tri6-3 probe was confirmed by the addition of 10-fold excess non-labelled Tri6-3 probe in the EMSA assays ( Tri6-3 , competitor , ‘+’ , Fig . 4B ) . In addition , we also used a probe which did not contain this consensus sequence as a negative control ( Tri6-NS , Fig . 4B ) . These results suggested that RNAGGCC motif is not involved in Tri6 binding in vitro . To further confirm this , nucleotides GGCC within the motif were mutated in the Tri6-3 probe and the results indicated that the mutations did not abolish Tri6 binding ( Tri6-3-1 , Fig . 2 ) . These results confirmed that the YNAGGCC motif is not required for binding of Tri6 , but suggested that nucleotides outside of this motif in the Tri6-3 probe are involved in Tri6 binding . Outside of the RNAGGCC motif , three domains in the Tri6-3 probe were recognized that could potentially bind Tri6 ( Fig . 5A ) . We designated CTGA sequence which partially overlaps the AGGCC site as Domain I and the two GTGA repeats separated by six nucleotides as Domain II and III , respectively ( Fig . 5A ) . As the EMSA results indicated , individual nucleotide mutations within Domain I did not have any noticeable effect on Tri6 binding ( Fig . 5B ) . However , individual mutations in Domain II and Domain III of the GTGA sequences , respectively , dramatically decreased Tri6 binding ( Fig . 5C ) . Furthermore , combined mutations in both Domain II and III completely abolished the Tri6 binding ( Fig . 5D ) . These results suggested that either a single GTGA sequence or GTGA repeats in the promoter of Tri6 are required for Tri6 binding . The 198 Tri6 targets identified in nutrient-rich conditions included several genes of the trichothecene gene cluster ( Table 2 ) . Since the Tri genes are expressed only under nitrogen-limiting conditions , we were interested to know how many of the non-Tri gene targets are co-regulated with the Tri genes . To address this , we performed a genome-wide expression analysis of wildtype and tri6Δstrains grown in nitrogen-limiting conditions . As the microarray analysis indicated , we identified a total of 1614 genes that were differentially regulated in the tri6Δstrain ( 2-fold cut off; Table S4 ) . Among the 870 down-regulated genes , 18 of the Tri6 targets were represented and another eight were represented in the 744 up-regulated genes ( Fig . 6 ) . Top five genes from each of the up and -down-regulated genes from the microarray analyses were selected for validation by RT-qPCR analyses ( Fig . 6 ) . If the expression threshold was set at 1 . 5 , 49 of the 198 target genes ( ∼25% of the ChIP targets ) were shown to be differentially regulated by Tri6 in this nutrient-limiting condition ( Table S5 ) . Out of 49 targets , 23 genes or ∼53% were annotated as unclassified by the MIPS functional annotation program and although others were classified into four major groups , only one category associated with cellular transport comprised of eight target genes were enriched to a significant level ( enrichment of 19% vs 10% in the genome , p-value 0 . 06 ) . Thus expression profiling provided a strong evidence to suggest that Tri6 extends its regulatory control beyond the trichothecene cluster and additionally , Tri6 can act both as a positive and negative regulator .
Nitrogen catabolite repression , or NCR , refers to genes that are repressed when a preferred source of nitrogen such as ammonia or glutamine are present in the environment [24] . NCR is mediated by the action of global nitrogen regulators which regulate the expression of structural genes required to metabolize alternate nitrogen sources . AreA is a prototypic NCR gene regulator and has been identified in many fungi , including A . nidulans , homologues Nut1 from M . grisea and AreA-GF from F . fujikuroi [30]–[33] . Under nutrient-rich conditions , expression of AreA is repressed by the binding of the repressor protein NmrA to the promoter of AreA [31] , [32] . However , under nitrogen-starving conditions , AreA repression is relieved and target genes involved in the utilization of non-preferred sources of nitrogen are expressed [31] , [32] . Coincidentally , some of the known AreA target genes such as the branched amino acid transferase ( FGSG_05696; ∼2 . 2 –fold , Table S4 ) and the general amino acid permease ( FGSG_05574; ∼4-fold , Table S4 ) that are normally expressed in the wildtype Fusarium strain under nitrogen-deprived conditions are repressed in the tri6Δstrain [34] . This leads one to speculate that Tri6 , similar to AreA , is involved in NCR . Studies in F . fujikuroi have also shown that AreA , in addition to regulating those genes involved in NCR , also regulates expression of genes that synthesize secondary metabolites like gibberellins and the pigment bikaverin [35] , [36] . An additional feature that is shared between Tri6 and AreA is that they are both subject to auto-regulation [31] . Taken together , our evidence suggests one possible scenario where Tri6 regulates functions of AreA through NmrA in F . graminearum . In support , we identified two genes ( FGSG_05942 and FGSG_10774 , Table S2 ) with Rossman-fold domains as targets of Tri6 . Rossman-folds are distinguishing features of NmrA proteins [26] . A further link between NmrA and virulence was recently established in F . oxysporum where the deletion of the transcription factor MeaB , which regulates Nmr1 , an orthologue of NmrA resulted in the repression of the virulence gene Six1 [37] . The EMSA studies demonstrated that mutations in either one of the GTGA elements in the promoter of Tri6 reduced the binding of Tri6 . However , combined mutations in both the GTGA elements completely abolished this binding ( Fig . 5D ) . This suggested that the presence of two GTGA elements in close proximity to each other in the Tri6 promoter likely contributes to the affinity of Tri6 to this site . Studies with other global regulators , specifically those responding to nitrogen , such as AreA in A . nidulans or its counterpart Nit2 in N . crassa showed that binding sites located within 30bp of each other in either orientation enhances their DNA binding affinity [38] . When these criteria were applied to the analysis of Tri6 target genes , 109 of the 198 target genes harboured multiple GTGA/TCAC binding sites in their promoters , separated by eight nucleotides or less , suggesting a common mechanism of binding and regulation by Tri6 ( Fig . 7 ) . It should be noted that GTGA/TCAC motifs separated by more than eight nucleotides are represented in the promoters of all the Tri6 target genes ( Table S1 ) . The GTGA/TCAC motif described in this study is distinct from the previously reported YNAGGCC for Tri6 binding [17] . Unlike this study , Hohn et al . did not use purified Tri6 protein and furthermore , their EMSA analysis with regions of the Tri3 promoter which contained the putative YNAGGCC consensus binding site did not result in a shift [17] . This led them to speculate an alternate binding site for Tri6 . It is noteworthy to indicate that Tri3 is one of the genes identified as targets of Tri6 with the GTGA repeats in its promoter . Studies with global regulators have outlined several mechanisms that influence both binding affinity and specificity [31] . For example , proteins that binds to direct repeats most likely bind as dimers . As an example , Dal80 protein in S . cerevisiae , involved in nitrogen catabolism , binds to two closely spaced GATA elements as a dimer in either a tail-to-tail or head-to-head orientation [39] . Interactions between global and pathway-specific regulators also influence both DNA binding specificity and affinity . For example , some of the genes involved in nitrate assimilation are regulated by the interaction between the global regulators AreA and NirA in A . nidulans , while other genes are regulated by the global regulator Nit2 and the pathway-specific regulator Nit4 in N . crassa [24] . Since we observed closely spaced GTGA repeats in the Tri6 promoter of F . graminearum , we could envisage a scenario , where Tri6 could function as a dimer and repress the expression of Tri6 in nutrient-rich conditions . However , under nutrient-deprived conditions , where the expression of Tri6 increases , Tri6 could interact with other known regulators such as Tri10 or PacC to provide specificity and regulate expression in condition-specific manner [14] , [19] . This interaction may also provide a platform for the Tri6-complexes to bind to an alternate site , such as the YNAGGCC proposed in several studies . Such a scenario could account for the differences between the genes regulated by Tri6 in this study from those seen in a recent study of F . graminearum infection in planta [16] . It is noteworthy to mention that the authors in that study also observed stark differences between the genes regulated by Tri6 in culture and in planta , albeit the comparison was made between two different Fusarium strains . One of the intriguing findings from the in planta study was that the promoters of genes , specifically the genes of the isoprenoid pathway essential for trichothecene production in both in planta and culture , showed enrichment of the YNAGGCC motif only in F . graminearum and not in other Fusarium species unable to make trichothecenes or in other related fungi [16] . It was proposed that co-regulation of the isoprenoid genes and the trichothecene genes represent an evolutionary adaptation specific to F . graminearum . A logical extension of this argument is that the source of nutrition , determined by the environment such as culture conditions or the type of host that this fungus infects , is the driving force behind this adaptation . In conclusion , this study has identified new or additional role for the transcriptional regulator , Tri6 . The findings from this study together with earlier studies have led us to conceive a new mode of action for Tri6 . In this model , Tri6 recognizes and binds the GTGA/TCAC elements under one condition such as the nutrient-rich condition where it regulates itself and other genes involved in various aspects of metabolism . However , when the environmental conditions change , be it in culture or in planta , activation of other regulators including Tri10 and PacC may change the dynamics of Tri6p-complex and initiate new interactions with the DNA , which could involve recognition of an alternate site such as the YNAGGCC motif . Although , we have no evidence to show that Tri6 directly interacts with either Tri10 or PacC , isolation and identification of Tri6 and Tri10 protein complexes in vivo will shed more light on both the dynamics and the links between these regulators .
Fusarium graminearum wildtype strain GZ3639 ( NRRL 38155 ) was provided by C . Babcock of the Canadian Collection of Fungal Cultures ( CCFC ) , Agriculture and Agri-Food Canada , Ottawa . F . graminearum and transformants were grown on PDA ( Sigma Chemical Co . USA ) plates . Constructs for the tri6Δand Tri6-HA complement strains have been described ( Fig . S1; http://apsjournals . apsnet . org/doi/suppl/10 . 1094/MPMI-09-10-0210 ) . To construct the Tri6 over expression vector , we first PCR amplified Tri6 ORF with the primer set Tri6-GUE-F/ Tri6-GUE-R ( Table S2 ) and F . graminearum genomic DNA as template . The PCR fragment was cloned into the vector pSW-GU . The backbone of pSW-GU vector is identical to pRF-HUE [40] except that the selection marker Hygromycin gene was replaced with Geneticin , encoded by the gene neomycin phosphotransferase [40] . Transformation of the tri6Δstrain with the Tri6 over expression vector was performed according to Rasmus et al [40] . The transgenic Fusarium strains were verified by PCR ( Fig . S2 ) . PCR conditions: 200 µM Primers , 200 µM NTP's , 1 unit of Expand long Taq polymerase ( Roche ) , 95°C for 30 s , 52°C for 30 s for annealing , 68°C for extension for 37 cycles . All PCR products were purified using Qiagen's PCR purification kit . To induce trichothecene production in liquid culture , a two stage media protocol , modified from Miller and Blackwell was employed [41] . 20 , 000 spores of wildtype , tri6Δand tri6ΔTri6 over expression strains were inoculated into 4 mL of first stage growth media and incubated in Falcon Multiwell 6-well culture trays ( Fig . S2 ) . The culture trays were affixed to an orbital shaker and the spores were grown for 24 hr at 28°C in the dark with constant shaking at 170 rpm . Following 24 hr growth , the mycelial solids were washed with water and resuspended in 4 mL of second stage media ( pH 4 . 0 ) [41] and then transferred to the 6-well culture trays . The mycelium was grown in second stage media under the same conditions as described previously . The supernatant was collected after 24 hr for trichothecene analyses . Trichothecenes were analysed on an AKTA 10 purifier ( GE Healthcare , Canada ) with direct injection of 100 µL of the culture filtrate into a 150×4 . 6 mm , 5 µm Hypersil ODS column ( Thermo-Electron Corp . ) , using a methanol: water gradient from 15∶85 to 60∶40 over 25 min at a flow rate of 1 ml/min . Under these conditions , 15-ADON elutes at a retention time ∼10 min , monitored by UV 220nm . Spores from the tri6Δand the complemented ( Tri6-HA ) strains were used to inoculate first stage media and grown for 19 hr as described before . The mycelia were washed with water and filtered ( sterile 1MM; Whatman ) . The ChIP-enriched DNA was prepared according to Saleh et al . [42] with modifications . The mycelial pellet was incubated in the cross-linking buffer for 30 min with continuous shaking . After thorough washing , the pellet was ground in liquid N2 and resuspended in the lysis buffer ( 250 mM , HEPES pH 7 . 5 , 150 mM NaCl , 1 mM EDTA , 1% Triton , 0 . 1% DeoxyCholate , 10 mM DTT and Protease inhibitor ( Roche complete Mini ) and incubated for 1 hr on ice . To obtain uniform fragments of cross-linked DNA , the suspension was sonicated 6x for 15 sec ( 60% amplitude , Misonix 4500 Sonicator ) . A small aliquot was used to confirm a dominant diffused band between 500 and 1000 bp . Approximately 750 µg of protein was incubated with 50 µL HA-magnetic beads ( Miltenyi Biotech ) and left overnight at 4°C . Immunoprecipitates were washed six times with lysis buffer and eluted with 250 µL of freshly prepared elution buffer ( 0 . 5% SDS and 0 . 1 M NaHCO3 ) with incubation at room temperature ( RT ) for 15 min with gentle agitation . The elution step was repeated once with 30 min of incubation at RT . To reverse the cross-linking , 20 µL of 5 M NaCl was added to the 500 µL elutes and incubated overnight at 65°C . The samples were further incubated for 1 . 5 hr at 45°C with 1 µL of Proteinase K ( 20 mg/mL ) , 30 mM Tris-HCl pH 6 . 5 and 10 mM EDTA to digest the proteins . DNA from these samples was precipitated according to Saleh et al . [42] . ChIP- enriched DNA was prepared for sequencing using the Illumina ChIP sample prep protocol with minor modifications . In brief , 2 µg of ChIP-enriched DNA was end repaired , and an adenosine overhang added to the 3′ ends . Standard Illumina adapters were ligated to the DNA and 240 bp fragments size selected from a 1 . 5% agarose gel . The eluted products were enriched using 18 cycles of amplification with Illumina PCR primers . Libraries were validated on the Bioanalyzer 2100 ( Agilent ) and Qubit fluorometer ( Invitrogen , Carlsbad , CA ) . Each sample was run on two lanes of the Illumina GAII sequencer at the Centre for the Analysis of Genome Evolution and Function ( CAGEF , University of Toronto ) . For each sample , 6 pmol was loaded in one lane of a standard flow cell , and 8 pmol was loaded in a second lane . The GAII was run for 38 cycles . In total , 24 , 201 , 991 out of 29 , 933 , 903 tags from Tri6-HA complemented strain and 15 , 756 , 703 out of 22 , 010 , 411 tags from tri6Δstrain were normalized and uniquely mapped to the genome by Novoalign ( http://www . novocraft . com ) [43] , [44] . The rest of the tags were either of low quality or mapped to multiple locations . Of the mapped tags , ∼50% were mapped to sense strand and another 50% were mapped to anti-sense strand . The mapping data were analyzed by the Site Identification from Short Sequence Reads ( SISSRs ) software for identification of the binding sites with tags originating from the tri6Δstrain as control [22] . The following parameters were used to run the program: 36 , 898 , 000 base pairs for the genome size , 0 . 8 for the fraction of genome mappable by reads , 1 for the E-value ( minimum number of directional tags required on each side of the inferred binding site ) , 0 . 1 for the p-value ( for fold enrichment of ChIP tags at a binding site location compared to that at the same location in the control data ) , 2 for the scanning window size , 240 base pairs for the average DNA fragment length , and 350 base pairs for the upper bound DNA fragment length . The switch -u was turned on to allow for identification of the binding sites supported only by reads mapped to one strand . Under these conditions , we were able to identify 1491 potential binding sites with at least 120 tags ( Tag# , the sum of the tags mapped to positive strand of the left half of the binding site and the tags mapped to negative strand of the right half of the binding site ) and at least 2 . 15 fold more tags in treatment vs control . We then compiled a list of 198 protein-coding genes with at least one binding site in 1 Kb upstream of the start site . The sum of the Tag# indicates the relative affinity of Tri6 to the binding sites in the promoter of the gene . The two-stage media was employed to grow F . graminearum as described before . Mycelia grown for 5 hr in the second stage ( nitrogen-limiting ) media were filtered and ground to a powder in liquid nitrogen . The RNA was isolated from 0 . 25 gm of ground mycelia with 1 mL of Trizol ( Invitrogen , USA ) according to manufacturer's instructions . The RNA was purified further with the InviTrap Spin Cell RNA mini kit ( Invitek , Germany ) according to the manufacture's instructions . cDNA for the quantitative RT-PCR Analysis ( RT-qPCR ) experiments was synthesized from 1 µg total RNA using random hexamers using the high-capacity cDNA reverse transcription kit ( Applied Biosystems , USA ) . RT-qPCR was performed using the Applied Biosystems StepOne Plus Real Time PCR system ( ABI , Foster City , USA ) . Standard curves were created for the house keeping genes ( β-tubulin; FGSG_09530 and Gapdh; FGSG_06257 ) and the genes of interest according to Relative standard curve method outlined in StepOne 2 . 1 software . Primers used in the RT-qPCR are listed in supplementary Table S2 . Using the relative standard curve , the relative quantity ( RQ ) was determined by comparing target quantity in each sample to the reference sample . P values <0 . 05 were considered to be statistically significant . Tri6 was cloned into pDEST17 vector ( Invitrogen , USA ) and expressed in BL21 pLys E . coli and the Tri6 protein was purified by the His Trap FF affinity column ( GE Health care , Sweden ) . Double stranded DNA probes ( 100 ηg/mL ) were labelled using T4 Polynucleotide Kinase ( Fermentas MBI ) and 20 µci of γP32 ( Perkin Elmer , USA ) . The labelled probes were purified using the Quick spin column ( Roche , USA ) and specific activity varied from 4–7×104 cpm/ηg . Binding reactions for the EMSA were performed in 15 µL volume with 2 µg purified Tri6-HA recombinant protein , labelled probes ( 20 , 000 cpm; 2ηg ) for 30 minutes at room temperature in a buffer containing 20 mM HEPES pH 7 . 9 , 2 mM DTT , 5% ( V/V ) Glycerol and 1 µg poly ( dIdT ) . The reaction was run on 6% polyacrylamide gels ( acrylamide/bis ratio of 19∶1 w/w ) in 50 mM Tris-HCl , pH 8 . 0 , 50 mM sodium borate and 1 mM EDTA . The competition experiments were performed by adding unlabelled oligonucleotides to the reaction at 10X molar excess ( 20 ηg ) of the labelled probe . The shift obtained by the Tri6 was scanned by the Storm 840 densitometer ( GE healthcare , USA ) and quantified by Image Quant TL 7 . 0 software ( GE healthcare , USA ) . All the DNA probes used in EMSA were synthesized by Sigma Genosys ( SigmaAldrich , Canada ) . Wildtype and the tri6Δstrains were grown in the second stage media for 5 hrs and the RNA was extracted as described before . The integrity of RNA was confirmed by an Agilent 2100 Bioanalyzer ( Agilent , Canada ) . RNA was then converted into cDNA using the Agilent Quick Amp Labeling Kit and converted back into labeled RNA using T7 RNA polymerase and cyanine 3-labeled CTP or 5-lableled CTP from the Agilent two-color RNA Spike-in kit . The cRNA was then hybridized to a custom F . graminearum 4X44K oligomer microarray ( Agilent Technologies , CA , USA ) , using an Agilent gene expression hybridization kit . Both dye combinations were performed for each biological replicate . Each array consisted of 1 , 417 spike-in and negative controls and up to three 60-mer oligos designed for each of 13 , 918 predicted F . graminearum genes ( NCBI GEO , Platform Accession #GPL11046 ) . The hybridizations were scanned using the GenePix Professional 4200A scanner , and the signals quantified using GenePix Pro 6 . The microarray data was transferred into Acuity 4 . 0 and the data was normalized using Lowess Normalization . Data points with low intensities were removed , and the dye swapped replicates were combined and expressed in log2 ratio . ANOVA was used to determine the consistency between samples for each hybridization ( P<0 . 05 ) . The data points were then averaged first between three biological replicates , then within the three average hybridizations . The data was then back transformed from the log scale as fold-expression . Separate datasets were then generated that contained genes that were positively identified in the chromatin immunoprecipitation data , as well as the genes that are up and down regulated in the entire genome by either 1 . 5-fold or greater and 2 . 0-fold or greater . Raw data can be accessed at NCBI GEO , Accession # GSE30892 .
|
Our knowledge of mechanisms involved in the activation and biosynthesis of DON comes largely from in vitro culture studies . Cumulated knowledge suggests that the physiological status of the fungus and the availability of nutrients are the main determining factors for DON production . Integration of various environmental cues to coordinate expression of secondary metabolic genes is thought to be mediated by a combination of global and pathway-specific transcription factors . While the global transcriptional factors respond to broad range of environmental cues such as the availability of carbon and nitrogen , the pathway-specific transcriptional factors regulate genes within a gene cluster . In F . graminearum , the transcriptional regulator Tri6 is encoded within the trichothecene gene cluster and regulates genes involved in the synthesis and transport of DON . In this report , we utilized ChIP-Seq to demonstrate that Tri6 can potentially bind to promoters and regulate genes not involved in the synthesis of DON and furthermore , many of these non-trichothecene genes are involved in various aspects of cellular metabolism , including transport and energy . Expression profiling revealed that many of the target genes are differentially regulated by Tri6 , thus validating our hypothesis that Tri6 is a global regulator involved in cellular metabolism .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry",
"biology",
"metabolism"
] |
2011
|
Tri6 Is a Global Transcription Regulator in the Phytopathogen Fusarium graminearum
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AmBisome therapy for VL has an excellent efficacy and safety profile and has been adopted as a first-line regimen in Bangladesh . Second-line treatment options are limited and should preferably be given in short course combinations in order to prevent the development of resistant strains . Combination regimens including AmBisome , paromomycin and miltefosine have proved to be safe and effective in the treatment of VL in India . In the present study , the safety and efficacy of these same combinations were assessed in field conditions in Bangladesh . The safety and efficacy of three combination regimens: a 5 mg/kg single dose of AmBisome + 7 subsequent days of miltefosine ( 2 . 5 mg/kg/day ) , a 5 mg/kg single dose of AmBisome + 10 subsequent days of paromomycin ( 15 mg/kg/day ) and 10 days of paromomycin ( 15 mg/kg/day ) + miltefosine ( 2 . 5 mg/kg/day ) , were compared with a standard regimen of AmBisome 15 mg/kg given in 5 mg/kg doses on days 1 , 3 and 5 . This was a phase III open label , individually randomized clinical trial . Patients from 5 to 60 years with uncomplicated primary VL were recruited from the Community Based Medical College Bangladesh ( CBMC , B ) and the Upazila Health Complexes of Trishal , Bhaluka and Fulbaria ( all located in Mymensingh district ) , and randomly assigned to one of the treatments . The objective was to assess safety and definitive cure at 6 months after treatment . 601 patients recruited between July 2010 and September 2013 received either AmBisome monotherapy ( n = 158 ) , AmBisome + paromomycin ( n = 159 ) , AmBisome + miltefosine ( n = 142 ) or paromomycin + miltefosine ( n = 142 ) . At 6 months post- treatment , final cure rates for the intention-to-treat population were 98 . 1% ( 95%CI 96 . 0–100 ) for AmBisome monotherapy , 99 . 4% ( 95%CI 98 . 2–100 ) for the AmBisome + paromomycin arm , 94 . 4% ( 95%CI 90 . 6–98 . 2 ) for the AmBisome + miltefosine arm , and 97 . 9% ( 95%CI 95 . 5–100 ) for paromomycin + miltefosine arm . There were 12 serious adverse events in the study in 11 patients that included 3 non-study drug related deaths . There were no relapses or PKDL up to 6 months follow-up . All treatments were well tolerated with no unexpected side effects . Adverse events were most frequent during treatment with miltefosine + paromomycin , three serious adverse events related to the treatment occurred in this arm , all of which resolved . None of the combinations were inferior to AmBisome in both the intention-to-treat and per-protocol populations . All the combinations demonstrated excellent overall efficacy , were well tolerated and safe , and could be deployed under field conditions in Bangladesh . The trial was conducted by the International Centre for Diarrhoeal Disease Research ( ICDDR , B ) and the Shaheed Suhrawardy Medical College ( ShSMC ) , Dhaka , in collaboration with the trial sites and sponsored by the Drugs for Neglected Diseases initiative ( DNDi ) . ClinicalTrials . gov NCT01122771
World-wide , 200 , 000–400 , 000 new cases of visceral leishmaniasis ( VL ) occur annually [1] . The majority of these cases occur in South Asia; mainly in Bihar , India and neighbouring regions of Nepal , and in the highly endemic Mymensingh province of Bangladesh . Before the introduction of single-dose AmBisome , miltefosine was included in the National Guidelines of India , Nepal and Bangladesh as a first line treatment for VL following a phase III trial in India that showed a final cure rate of 94% [2] . However , poor compliance due to its long treatment course ( 28 days ) [3] and possible teratogenic effects have limited its successful roll-out . Moreover , a decrease in susceptibility to miltefosine was found in clinical isolates of relapse patients [4] and the efficacy of miltefosine declined to 90% within the last decade of use in South Asia [3] . A phase III clinical trial in India demonstrated that paromomycin at a dose of 15 mg/kg for 21 days provided a final cure rate of 94 . 6% [5] , but this regimen was never implemented in Asia . As with miltefosine , there were indications that resistance to paromomycin might easily develop when used in monotherapy [6] . Due to the challenges in implementing clinical trials to assess treatment safety and efficacy , very few studies have been conducted in government sector at Upazila Health Complexes under real life conditions within national program settings . The present study aimed to assess the efficacy and safety of alternative combination treatments for primary visceral leishmaniasis and its implementation at different levels of the health system . To reduce pressure on the drugs and prolong their therapeutic life-span , miltefosine and paromomycin should preferably be used in combination; short course combination regimens will lead to better compliance and are more readily implemented at health facility level . Three short-course combination regimens including AmBisome , miltefosine and paromomycin have been evaluated in a phase III clinical trial conducted in India ( 2008–2010 ) . All showed an excellent safety profile and an efficacy of at least 97% in controlled conditions [7] . The present study aimed to compare the safety and efficacy of the following combination regimens with AmBisome alone for the treatment of VL in Bangladesh:
Ethical approval was obtained from the Ethical Review Committee of the International Centre for Diarrhoeal Disease Research , Bangladesh ( ICDDR , B ) and the National Research Ethics Committee ( NREC ) of the Bangladesh Medical Research Council ( BMRC ) prior to starting the study . The study was conducted in accordance with the ICH Harmonized Tripartite Guideline–Guideline for Good Clinical Practice ( GCP ) , and ethical principles enshrined in the Declaration of Helsinki . This was a randomized , controlled , open-label , parallel group phase III clinical trial conducted in Mymensingh province , Bangladesh . Initially , 120 patients were recruited and treated in a hospital setting ( the Community Based Medical College , CBMC ) primarily for the purpose of confirming the safety of the combination treatments in Bangladesh . After review of safety data up to day 45 from the 120 patients treated at CBMC , and based on good safety profile of the treatments , the Data Safety Monitoring Board ( DSMB ) recommended to initiate recruitment at Upazila Health Complexes ( UZHC ) . Additional 482 patients were recruited for the trial and treated in the Upazilas of Trishal , Gaffargoan and Bhaluka . HIV negative primary VL patients between 5 and 60 years screened with positive rK39 rapid immunochromatographic tests ( InBios , Seattle , USA ) and parasitologically confirmed via bone marrow or spleen aspirates ( only at CBMC ) were enrolled into the study after giving informed consent . Because of the potential teratogenic effects of miltefosine , women of child-bearing age who were not using an assured method of contraception for the duration of treatment and three months afterwards were excluded , unless they agreed to receive an injection of medroxyprogesterone acetate ( DepoProvera , Pfizer , NY , USA ) . One injection ( which is effective for 3 months ) was needed to ensure adequate coverage , taking into account miltefosine’s long half-life of approximately 7 days . Other exclusion criteria were: known hepatitis B , hepatitis C , or HIV infection , Hb concentrations less than 5 g/dl , platelet count of less than 40 , 000/mm3 ( at CBMC only ) , a prothrombin time of more than 5 seconds longer than the control ( at CBMC only ) , severe malnutrition [for adults ( > 18 years ) defined as BMI <14; for children ( < 18 years ) defined as BMI for age z score < -3 in children measuring > 121 . 5cm; and weight for height less than 60% in children measuring <121 . 5 cm] , known alcohol or drug abuse , use of any investigational ( unlicensed ) drug within the last 3 months , and severe concurrent illnesses ( TB , malaria ) or chronic conditions ( diabetes , hypertension ) . Pregnant and breast-feeding women , and patients with known hypersensitivity to the study drugs were also excluded . Patients were randomized to four treatment arms . In the reference treatment group , patients were given the standard regimen of 15 mg/kg AmBisome , given in doses of 5 mg/kg on days 1 , 3 and 5 , infused over 2 hours in 5% dextrose solution . Patients allocated to the AmBisome + miltefosine arm received 5 mg/kg AmBisome on day 1 , followed by 7 days of miltefosine ( Impavido , Paladin , Canada ) . Miltefosine is provided as foil-wrapped blister packs of 10 and 50 mg capsules and was given to adults ( >12 years ) at a dose of 50 mg once daily if < 25 kg bodyweight , 50 mg twice daily if > 25 kg bodyweight; or 2 . 5 mg/kg/day divided into 2 doses for children younger than 12 years . Patients assigned to the AmBisome + paromomycin arm received 5 mg/kg AmBisome on day 1 , followed by 10 days of paromomycin ( Gland Pharma , India ) at a dose of 11 mg/kg/day ( base ) equivalent to 15 mg/kg/day ( sulphate salt ) , given by deep IM injection . Patients allocated to the miltefosine + paromomycin arm received the above described doses daily for 10 days . Patients treated with miltefosine on an outpatient basis in UZHC’s were given detailed instructions on the number of capsules to be taken each day , and asked to return to the clinic in case of vomiting . Miltefosine was re-dosed within one hour of vomiting . Patients were asked to return the empty blister packs for drug accountability . The main outcome was final cure , defined as initial cure at day 45 and absence of VL signs and symptoms during the follow-up period of 6 months . The secondary outcome was initial cure , defined as clinical improvement at day 45 . In the CBMC hospital setting , initial cure was confirmed by the absence of parasites in splenic/bone marrow aspirates at day 15 . In cases of 1+ parasite at day 15 , patients were retested at day 45 . Patients who presented positive parasitology at day 45 , or cases of relapse following combination treatment , were to receive rescue treatment with AmBisome 15 mg/kg . Those who failed to respond/relapsed following the reference treatment , or where AmBisome was contra-indicated , were to be rescued with sodium stibogluconate ( SSG ) 20mg/kg/day for 30 days , or miltefosine 2 . 5mg/kg/day for 28 days as recommended by the National Treatment Guidelines of Bangladesh and the investigator’s judgement . Patients with initial cure presenting with VL symptoms during follow-up were suspected of relapse , and were referred for parasitological confirmation at the CBMC hospital . Safety outcomes were adverse events and serious adverse events recorded during treatment and up to 6 months afterwards . Assessments were done on the basis of clinical adverse events systematically at all study sites . At the CBMC hospital , laboratory investigations included liver enzymes alanine aminotransferase ( ALAT ) , aspartate aminotransferase ( ASAT ) , bilirubin , prothrombin time , platelets , RBC count , WBC count , random blood glucose ( RBS ) , urea , creatinine , serum sodium , potassium , magnesium . At the UZHC settings , laboratory parameters were limited to haemoglobin and random blood glucose ( RBS ) . All patients were assessed for dermal manifestations of leishmaniasis ( Para-KDL at baseline , and PKDL at day 15 , 45 and at 6 months ) . A computer generated randomization code was used for patient treatment allocation . Individual , opaque , sealed and sequentially numbered envelopes were provided to each study site ( one envelope per patient ) , indicating the individual patient allocation to treatment . Eligible patients who fulfilled all the inclusion criteria , met none of the exclusion criteria and from whom informed consent had been obtained were randomized to treatment regimens using the sealed envelopes . Randomization was stratified by treatment centre and was done using an equal allocation ratio for married women , men , and children firstly; and further with an equal ratio in single women of childbearing potential . Single women of childbearing age were randomized to receive either AmBisome alone or AmBisome + paromomycin . The allocation ratio was adjusted to account for this , in order to achieve approximately equal numbers of patients in each arm . Thus the allocation ratio was 1:1:1:1 for four treatments in married women , men , and children; and 1:1 ( for AmBisome alone or AmBisome + paromomycin ) in single women of childbearing potential . This was an open-label study; miltefosine is an orally administered medication and AmBisome and paromomycin are administered IV and IM respectively . The sample size was calculated assuming a treatment success of 97% in the reference arm ( AmBisome ) and a margin of non-inferiority of any tested treatment of 7% , leading to a minimally acceptable cure rate of 90% for each treatment . With a power of 90% , the sample size per group in the sample of married women , men and children would be 140 . Based on the possible teratogenic effect of miltefosine and the assumption that 20% of the patients would be single women of child bearing potential , 26 extra patients were to be recruited among these women for both non-miltefosine groups . Assuming a drop-out rate of 10% , 154 patients were needed in both miltefosine groups and 183 in both non-miltefosine groups . The total sample size was calculated to be 674 patients . The primary efficacy analysis was performed using the standard approach of non-inferiority for the comparison AmBisome vs AmBisome + miltefosine and for AmBisome vs . paromomycin + miltefosine on populations ITT1 and PP1 . For AmBisome vs AmBisome + paromomycin comparisons , a logistic model was carried out using populations ITT and PP ( Table 1 ) . The Intention to Treat 1 ( ITT1 ) population included married women , men and children randomized to the trial and who received at least one dose of the study medication; but it did not include the single women of childbearing potential who were randomized either to AmBisome or Ambisome + paromomycin arms . The Intention to Treat population ( ITT ) included all patients randomised to the treatment groups who gave informed consent and who took at least one dose of study medication . The Per Protocol 1 population ( PP1 ) included patients ( married women , men and children ) enrolled in the Intent to Treat 1 population who were randomized to the trial , who had no major protocol deviations and who completed the 6 month follow-up visit or were classified as a treatment failure and received rescue medication . The Per Protocol population ( PP ) included all patients in the ITT population with no major protocol deviations and who completed the 6 month follow-up visit or were classified as a treatment failure and received rescue medication . The ITT population was 601 and the PP population was 587 . The reasons for exclusion in the PP population were 12 cases of withdrawal due to AE/SAE , which required rescue treatment , and 2 deaths .
Of the 673 patients screened , 71 did not meet the inclusion criteria . A total of 24 screened patients did not have VL diagnosis confirmed by rK39 or microscopy . Among the patients with proven disease , the most common reasons for exclusion were chronic underlying disease ( n = 14 ) and simultaneous participation in another study ( n = 9 ) . Five patients refused consent , four had abnormal laboratory parameters , 3 were pregnant or lactating women , and 12 were excluded for other reasons . The decision to stop recruitment was made after enrolling 602 patients ( 120 in the CBMC hospital setting , 482 in UZHC’s ) . Only 2% rather than the estimated 10% of patients were lost to follow-up , so that the sample size could be reduced by 72 patients . The patient flow through the study is shown in Fig 1 . Patients were recruited from July 6 , 2010 to September 2013 and asked to return to the clinic at day 45 and at 6 months after treatment onset , or sooner if any symptoms of VL reoccurred . Follow-up of all patients was completed by the end of March 2014 . Randomisation produced groups with no significant differences in the main baseline characteristics across treatment groups ( e . g . age , sex , weight , nutritional status , spleen size , haemoglobin ) ( Tables 2–4 ) . 673 patients screened in the study , 602 randomised in the study , 71 patients did not meet inclusion criteria . 587 patients in the PP population , with: 3 deaths; 4 SAEs and 09 AEs that lead to treatment discontinuation , n = 13; 10 protocol deviations; 2 miltefosine redosing when vomiting occurred > 1h after administration; 3 patients missed a miltefosine dose; 2 received wrong Miltefosine capsule strength; 1 received additional miltefosine medication after finishing treatment; 1 mistake in randomization: randomized to PM+Milt administered AmBisome; 1 patient did not receive single dose of study medication after randomisation to AmBisome arm . In the safety population ( ITT ) of 601 patients , 374 ( 62% ) were males and 227 ( 38% ) were females . 85% of patients had haemoglobin < 10 mg/dl at the time of screening . There were 594 ( 99% ) patients who complained of weight-loss and feelings of weakness . There were 588 ( 98% ) patients who had pallor at baseline . The primary analysis was intention-to-treat; data were available for 158 patients randomized to AmBisome ( 1 withdrew consent before treatment started ) , 159 to AmBisome + paromomycin , 142 patients to AmBisome + miltefosine and 142 patients to paromomycin + miltefosine , with a total of 601 patients included in the ITT analysis . Four patients were withdrawn from the study due to serious adverse events ( SAEs ) , and another nine patients due to adverse events ( AEs ) that required treatment discontinuation , making a total of 13 early withdrawals due to adverse events . Three deaths occurred in the study: one in the AmBisome arm and two in AmBisome + miltefosine arm . There were 10 cases of protocol deviations . Protocol deviations were due to miltefosine re-dosing to patients presenting with vomiting more than 1 hour after drug administration ( 2 patients ) , missing of a miltefosine dose ( 3 patients ) or inadvertently receiving the wrong miltefosine capsule strength ( 2 patients ) . One patient took additional miltefosine after finishing her study medication , and one patient randomized to paromomycin + miltefosine treatment was administered AmBisome . Finally , one patient did not receive even a single dose of study medication after randomization to the AmBisome arm . There were no patients lost to follow-up . Cure rates at 45 days ( initial cure ) and 6 months ( final cure ) are shown in Tables 5 and 6 . In the ITT population , the initial and final cure rates were >95% in all arms , except in the AmBisome + miltefosine arm ( 94 . 4% for both initial and final cure rate ) . All arms showed a final cure rate of >95% in the PP population . In children , the initial cure rate is 100% in all groups except the paromomycin + miltefosine group with a cure rate of 96 . 7% . However , adolescents achieved 100% cure initial cure rate in the paromomycin + miltefosine group ( Table 6 ) . In the ITT population , final cure rates were > 95% in children and adolescents in all groups . The lowest final cure rate was observed in the ITT population in adults treated with AmBisome + miltefosine ( 91 . 5% ) . Treatment failures in this arm were due to two cases of death not related to treatment and AEs or SAEs that lead to treatment discontinuation where patients required rescue treatment . Although not statistically significant , AmBisome + paromomycin was the most effective treatment with initial and final cure rates of 99 . 4% in the ITT population . Out of the first 120 patients that were included and followed up in the hospital setting ( CBMC ) , parasitological cure measured on day 15 was achieved in > 90% of patients in all groups ( patients who did not have cure confirmed were due to ‘no tissue to perform the test’ or ‘test not done’ ) , and in 100% in the AmBisome + paromomycin group ( Table 7 ) . There were no relapses and no cases of PKDL up to 6 months follow-up . None of the combination treatments were inferior to AmBisome monotherapy when compared in pairs for both the intention-to-treat and the per-protocol populations ( Table 1 ) . There were 11 patients who experienced a total of 12 SAEs , which included three non-drug related deaths ( severe pneumonia , sudden cardiac death and hepatic encephalopathy ) . In the miltefosine + paromomycin group , three drug-related SAEs occurred; two of which occurred in the same patient . This patient was a 50 year old male who developed drug induced nephropathy and ototoxicity two weeks after treatment , both probably related to paromomycin; mild hearing loss was still present at 6 months after treatment . In a 40 year old male , acute hepatitis developed and worsened during treatment but resolved spontaneously after treatment was finished . In the AmBisome + miltefosine group , a 35 year old female patient presented with high grade fever , rash and swelling of arms and legs after 2 days of Miltefosine , which was possibly drug related . Treatment was interrupted and she was later diagnosed with Rickettsial fever with concomitant nutritional oedema . Rescue treatment was given with AmBisome and she made a full recovery . None of the other non-fatal reported SAEs ( encephalitis , internal bleeding due to a peptic ulcer , acute respiratory tract infection , epilepsy and viral encephalitis ) were related to treatment . 368 out of 602 patients experienced at least one AE in the study . Approximately 34% of these AEs were related to treatment; these included vomiting in one fifth of patients in miltefosine containing treatment regimens and pyrexia in AmBisome containing treatment regimens . Vomiting directly after administration of miltefosine was common; there were 28 ( 20% ) patients in the paromomycin + miltefosine arm and 16 ( 11% ) in the AmBisome + miltefosine arm that needed re-dosing within the hour . The proportion of patients that experienced any treatment-related side effects was highest in the AmBisome + miltefosine arm ( 42% ) , and lowest ( 27% ) in the AmBisome arm ( Table 8 ) . Extensive biochemical testing was only done for patients treated in the hospital setting ( 120 patients ) . The clinically significant laboratory adverse events considered related to the study drug are described in Table 9 . All of them were classified as mild . There were no statistically significant changes over the treatment period in any of the biochemical parameters . Haematological parameters ( haemoglobin , red and white blood cell counts and platelets ) were improved at day 45 as compared to baseline , without a significant difference between the individual treatment arms ( S1–S4 Tables , supporting information ) .
All combinations proved non-inferior to the standard treatment with AmBisome , with definitive cure rate differences in relation to AmBisome compared to: AmBisome + paromomycin ITT 1 . 3% ( 95%CI -1 . 73 , 4 . 27 ) ; AmBisome + miltefosine ITT1–3 . 7% ( 95%CI -9 . 20 , 1 . 85 ) and paromomycin + miltefosine ITT1–0 . 1% ( 95%CI -4 . 15 , 4 . 03 ) ( Table 1 ) . Treatments were well tolerated and no new safety signal was identified . Overall adverse events were of mild intensity . The internationally accepted parameters for efficacy of VL treatment ( ≥95% ) [8] were also met for all combinations in both the per-protocol ( PP ) and the intention-to-treat ( ITT ) populations , except for AmBisome + miltefosine , which showed an efficacy of 94 . 4% in the ITT population . These cases of failure were not due to lack of response or relapse , but related to two deaths and a higher number of treatment discontinuations in relation to adverse events , requiring rescue treatment . The trial was not powered to detect differences between the treatment arms; however , a small but significant difference was found between the efficacy of AmBisome + miltefosine and AmBisome + paromomycin in both the PP and ITT population . Post-hoc analysis of the data stratified per age group showed that this difference only remained significant in adult patients ( Table 5 ) . There was no loss to follow up at 6 months as patients were actively tracked by committed field workers , and there were no relapses or PKDL . However , there is recent evidence that most relapses occur after 6 months [9 , 10] . We therefore recommend , in line with other authors [9] , to follow VL patients for at least 12 months before determining the final treatment outcome . The combination regimens described in this paper have been studied earlier in a Phase III clinical trial conducted in India ( 2008–2010 ) [7] . The excellent safety and efficacy outcomes in the present study support those found in India . The main difference with the Indian study is that patients have been mostly treated in field conditions at Upazila level , with treatment provided by government doctors . This study provides evidence that it is feasible to scale up the implementation of combination regimens within national program settings and that these are acceptable to patients as well as doctors . However , the patient population was selected to have non-severe disease , and we recommend active pharmacovigilance at sentinel sites in Bangladesh documenting treatment outcome ( side effects , early treatment failure , relapse and PKDL ) on the full patient population after implementation of combination regimens . Recent discussions among decision-makers around the Road Map for elimination of VL in South Asia have led to the inclusion of single dose AmBisome as a first-line treatment and miltefosine + paromomycin as an alternative recommended treatment for VL in India and Bangladesh . Earlier , combination regimens had already been recommended by the WHO Expert Committee [8] and the Regional Technical Advisory Group ( RTAG ) for adoption by policy makers after demonstration of the feasibility of their implementation in field conditions [11] . The evidence generated in the present study supports the use of combination treatments as valid alternatives to single dose AmBisome therapy . The most cost effective combination appears to be 10 days of miltefosine + paromomycin , since this can be given on an outpatient basis [12] . However , ultimately the choice of treatment will depend on the circumstances . Considering the requirement for a cold chain for AmBisome and the availability of trained staff to give intravenous infusions , miltefosine and paromomycin given on outpatient basis may be a suitable treatment in most settings . But as miltefosine cannot be given to women of child bearing age who refuse contraception , AmBisome and paromomycin is a viable alternative . Given the fact that paromomycin is not currently registered in Bangladesh , AmBisome + miltefosine may be considered as an interim solution . In Bangladesh , evidence on the excellent efficacy and safety profile of a single dose ( 10 mg/kg ) of AmBisome was generated in 2010 [13] and it was soon thereafter adopted as a highly promising tool for regional elimination . Rolled out in a rural public hospital in Bangladesh , single dose AmBisome showed a final cure rate of 97% and this provided sufficient evidence for scaling up the use of AmBisome in the region as a first-line treatment in hospital settings [14] . Single dose AmBisome was adopted as a first-line treatment in Bangladesh in 2013 , when the current clinical trial was still ongoing . Data from this clinical trial support the use of combination regimens as 2nd line treatments for VL in Bangladesh . The validation and use of combination therapy to provide an alternative to AmBisome in the context of a VL elimination program , where AmBisome is used as a first-line treatment for uncomplicated VL , relapse VL , HIV/VL co-infected patients and PKDL , is crucial .
|
Treatment is one of the key strategies for visceral leishmaniasis control and elimination . Historically a number of monotherapy drugs for VL treatment were used in Bangladesh , including pentavalent antimonials , amphotericin B deoxycholate ( AmB ) , and miltefosine ( MF ) . With the limited number of drugs available , it was necessary to preserve existing drugs and also to develop shorter and safer treatment regimens . At the time the study was initiated , miltefosine monotherapy was a recommended first-line treatment in Bangladesh . The present study aimed to provide safety and efficacy data for three short-course combination regimens including AmBisome , miltefosine and paromomycin when rolled out in field conditions in Bangladesh , and to compare these to AmBisome monotherapy . All combinations proved non-inferior to AmBisome monotherapy and were safe and well tolerated . This study was implemented in field conditions at Upazila level with treatment provided by government doctors , providing further evidence for scaling up new regimens in national program contexts within the public health sector .
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2017
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Safety and efficacy of short course combination regimens with AmBisome, miltefosine and paromomycin for the treatment of visceral leishmaniasis (VL) in Bangladesh
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We introduce an Active Vertex Model ( AVM ) for cell-resolution studies of the mechanics of confluent epithelial tissues consisting of tens of thousands of cells , with a level of detail inaccessible to similar methods . The AVM combines the Vertex Model for confluent epithelial tissues with active matter dynamics . This introduces a natural description of the cell motion and accounts for motion patterns observed on multiple scales . Furthermore , cell contacts are generated dynamically from positions of cell centres . This not only enables efficient numerical implementation , but provides a natural description of the T1 transition events responsible for local tissue rearrangements . The AVM also includes cell alignment , cell-specific mechanical properties , cell growth , division and apoptosis . In addition , the AVM introduces a flexible , dynamically changing boundary of the epithelial sheet allowing for studies of phenomena such as the fingering instability or wound healing . We illustrate these capabilities with a number of case studies .
Owing to its origins in the physics of foams [62] , in the VM cells are modelled as two-dimensional convex polygons that cover the plane with no holes and overlaps , i . e . , the epithelial tissue is represented as a convex polygonal partitioning of the plane ( Fig 1 ) . The main simplification compared to models of foams is that most implementations of the VM assume that contacts between neighbouring cells are straight lines . However , we note that there have been several recent studies where this assumption has been removed and cell-cell junctions were allowed to be curved [63 , 64] . In addition , neighbouring cells are also assumed to share a single edge , which is a simplification compared to real tissues , where junctions between two neighbouring cells consist of two separate cell membranes that can be independently regulated . Typically , three junction lines meet at a vertex , although vertices with a higher number of contacts are also possible [58] . The model tissue is therefore a mesh consisting of polygons ( i . e . , cells ) , edges ( i . e . , cell junctions ) , and vertices ( i . e . , meeting points of three or more cells ) . An energy is associated to each configuration of the mesh . It can be written as E V M = ∑ i = 1 N K i 2 A i - A i 0 2 + ∑ i = 1 N Γ i 2 P i 2 + 2 ∑ μ , ν Λ μ ν l μ ν , ( 1 ) where N is the total number of cells , Ai is the area of the cell i , while A i 0 is its reference area . Ki is the area modulus , i . e . a constant with units of energy per area squared measuring how hard it is to change the cell’s area . Pi is the cell perimeter and Γi ( with units of energy per length squared ) is the perimeter modulus that determines how hard it is to change perimeter Pi . lμν is the length of the junction between vertices μ and ν and Λμν is the tension of that junction ( with units of energy per length ) . 〈μ , ν〉 in the last term denotes the sum is over all pairs of vertices that share a junction . Note that the model allows for different cells to have different area and perimeter moduli as well as reference areas , allowing for modelling of tissues containing different cell types . Finally , for convenience we introduced a prefactor 2 in the last term in Eq ( 1 ) to compensate for double counting of cell junctions when switching from a sum over junctions to a sum over cells in the force calculation discussed below . Some authors write the perimeter term as ∑ i Γ ˜ i / 2 ( P i - P i 0 ) 2 , where P i 0 is a reference perimeter , and omit the last term in Eq ( 1 ) or completely omit the P2 term [47 , 58] . Under the assumption that the values of Λμν for all junctions of the cell i are the same , i . e . , Λμ , ν ≡ Λi , the last term in Eq ( 1 ) becomes Λi ∑〈μ , ν〉 lμ , ν = ΛiPi . Therefore , if we identify Λ = - Γ ˜ P i 0 , it immediately becomes clear that the descriptions in Eq ( 1 ) and the model with the preferred perimeter are identical to each other . Note that this is true up to the constant term 1 / 2 Γ ˜ i ( P i 0 ) 2 , which is unimportant as it only shifts the overall energy and does not contribute to the force on the cell ( see below ) . The description in Eq ( 1 ) is slightly more general as it allows for the junctions to have different properties depending on the types of cells that are in contact . Retaining the P i 2 term is also advisable in order to prevent the model from becoming unstable if the area modulus is too small . It is straightforward to express cell area and cell perimeter in terms of vertex coordinates . Therefore , vertex positions together with their connectivities uniquely determine the energy of the epithelial sheet , hence the name Vertex Model . The main assumption of the VM is that the tissue will always be in a configuration which minimises the total energy in Eq ( 1 ) . Determining the minimum energy configuration is a non-trivial multidimensional optimisation problem and , with the exception of a few very simple cases , it can only be solved numerically . A basic implementation of the VM therefore needs to use advanced multidimensional numerical minimisation algorithms to determine the positions of vertices that minimise Eq ( 1 ) for a given set of parameters Ki , Γi and Λμν . Most implementations [51 , 53 , 58] , also introduce topology ( connectivity ) changing moves to model events such as cell rearrangements . There have been several attempts to introduce dynamics into the VM [47 , 51 , 56] , including a recent study that introduced stochasticity into the junction tension [53] . The idea behind such approaches it to write equations of motion for each vertex as γ d r μ d t = F μ , ( 2 ) where γ is a friction coefficient and rμ is the position vector of vertex μ . Fμ is the total force on vertex μ computed as the negative gradient of Eq ( 1 ) with respect to rμ , i . e . , Fμ = −∇rμ EVM . We note that the exact meaning of friction in confluent epithelial tissues is the subject of an ongoing debate that is beyond the scope of this study . Here , as in the case of most models to date , we assume that all effects of friction ( i . e . , between neighbouring cells as well as between cells and the substrate and the extracellular matrix ) can be modelled by a single constant . While this may appear to be a major simplification , as we will show below , the model is capable of capturing many key features of real epithelial tissues . Eq ( 2 ) is a first order equation since the mass terms have been omitted . This so-called overdamped limit is commonly applied to biological systems , since the inertial effects are typically several orders of magnitude smaller than the effects arising from the cell-cell interactions or random fluctuations produced by the environment . Note that the force on vertex μ depends on the position of its neighbouring vertices , resulting in a set of coupled non-linear ordinary differential equations . In most cases those equations can only be solved numerically . While the introduction of dynamics alleviates some of the problems related to the quasi-static nature of the VM , one still has to implement topology changing moves if the model is to be applicable to describing cell intercalation events . This can lead to unphysical back and forth flips of the same junction and has only recently been analysed in full detail [58] .
It is important to note that the VM in its original form is a quasi-static model . In other words , it assumes that at every instant in time , the tissue is in a state of mechanical equilibrium . This is a strong assumption , which is in line with many biological systems , especially in the case of embryos where cells actively grow , divide and rearrange . As a matter of fact , biological systems are among the most common examples of systems out of equilibrium . Therefore , while it is able to capture many of the mechanical properties of the tissue , the VM is unable to fully describe the effects that are inherently related to being out of equilibrium . Many such effects are believed to be behind the collective migration patterns observed in recent experiments . In addition , in many dynamical implementations of the VM the effects of both thermal and non-thermal random fluctuations originating in complex intercellular processes and interactions with the environment are either completely omitted or not very clear . While for a system out of equilibrium the fluctuation-dissipation theorem [65] does not hold , and the relation between random fluctuations and friction is not simple , it is even more important to note that fluctuations can have non-trivial effects on the collective motion patterns [53] . Here we take an alternative approach and build a description similar to the recently introduced SPV model [59] . The idea behind the SPV is that instead of treating vertices as the degrees of freedom , one tracks positions of cell centres . Forces on cell centres are , however , computed from the energy of the VM , Eq ( 1 ) . The core assumption of the model is that the tissue conformations correspond to the Voronoi tessellations of the plane with cell centres acting as Voronoi seeds . We recall that a Voronoi tessellation is a polygonal tiling of the plane based on distances to a set of points , called seeds . For each seed point there is a corresponding polygon consisting of all points closer to that seed point than to any other . This imposes some restrictions onto possible tissue conformations , i . e . , not all convex polygonal tessellations of the plane are necessarily Voronoi , but it has recently been argued that Voronoi tessellations can predict the diverse cell shape distributions of many tissues [66] . Furthermore , the exact details of the tessellation are not expected to play a significant role in the large scale behaviour of the tissue , which this model aims to describe . We , however , note that recently an interesting model based on a generalised Voronoi description has been proposed [67] . In the original implementation of Bi , et al . [59] the Voronoi tessellation is computed at every time step . The vertices of the tessellation are then used to evaluate forces at all cell centres , that are , in turn , moved in accordance to those forces and the entire process is repeated . While conceptually clear , this procedure is numerically expensive as it requires computation of the entire Voronoi diagram at each time step . This limits the accessible system size to several hundred cells . Here , we instead propose an alternative approach based on the Delaunay triangulation . The Delaunay triangulation for a set of points P in the plane is a triangular tiling , DT ( P ) , of the plane with the property that there are no points of P inside the circumcircle of any of the triangles in DT ( P ) [68] . A property of a Delaunay triangulation that is key for this work is that it is possible to construct a so-called dual Voronoi tessellation by connecting circumcenters of its triangles . This establishes a mathematical duality between Delaunay and Voronoi descriptions . This duality is exact and quantities , such as the force , expressed on the Voronoi tiling have an exact map onto quantities expressed on its dual Delaunay triangulation . Although being non-linear ( see Sec . “Force on the cell centre” ) , this map is relatively simple , and therefore fast to compute . An important property of the Voronoi-Delaunay duality is that continuous deformations of one map into continuous deformations of the other . In other words , smooth motion of a cell’s centre will correspond to a smooth change in that cell’s shape . This is crucial to ensuring that during the dynamical evolution the cell connectivity changes continuously , a feature that is essential for accurately modelling T1 transitions . The main advantage of working with the Delaunay description is that while the Voronoi tessellation has to be recomputed each time cell centres move , it is possible to retain the Delaunay character of a triangulation via local edge flip moves ( Fig 2c ) , which drastically increases the efficiency of the Delaunay based approach and enables us to simulate systems containing tens of thousands of cells . Before we introduce the Active Vertex Model ( AVM ) , we pause to make a comment about the notation . In the following , we will always use Latin letters to denote cells , i . e . positions of their centres , and Greek letters to denote vertices of the dual Voronoi tessellation , i . e . , meeting points of three or more cells . Therefore , vertices of the VM will always carry Greek indices ( Fig 2a ) .
We start by illustrating one of the key processes observed in epithelial tissues , the T1 transition . As detailed in Fig 2 , in the AVM T1 transitions are handled through an edge flip in the Delaunay triangulation . An edge flip only happens when , in the notation of Fig 2c , we have α + β = δ + γ = 180° . Then both triangles are circumscribed by the same circle passing through its combined four vertices . The location of the T1 transition coincides with the centre of this circle . Due to the continuous connection between the position of sites of the Delaunay triangulation and its dual Voronoi tessellation , we always approach this point smoothly , i . e . a junction between two cells will smoothly shrink to a point , the T1 transition will occur , and then it will expand in a new direction . This process arises naturally in the AVM model , in stark contrast with many currently available implementations [85] that require a cut-off criterion on the edge length of a cell before a T1 transition can occur . It also avoids discontinuous jumps at finite edge length , bypassing the T1 point altogether , also a feature of a number of models , notably those based on sequential energy minimisation [49 , 81 , 86] . Next to its high computational efficiency , the ability to smoothly go through a T1 transition without the need for any additional manipulations of either the Delaunay triangulation or the Voronoi tessellation is one of the key advantages of the AVM approach . In Fig 5 , we illustrate a T1 transition in the bulk , in a region of phase space where the system exhibits liquid-like behaviour , but with very slow dynamics ( see next section ) . The edge linking cells 2 and 4 ( in red ) slowly shrinks to a point , and then rapidly expands in the opposite direction . This feature points to dynamics akin to certain models of sheared materials [87] , where the active driving pulls the material over an energy barrier from one minimum to the next . It is somewhat different from the activated dynamics which has been proposed for the SPV [86] , which would predict a series of fluctuations through which the barrier between minima is ultimately crossed . We now explore different modes of collective behaviour , i . e . , phases , of the tissue based on the values of parameters of the original VM ( Ki , Γi and Λμ , ν ) , and AVM-specific parameters such as the activity fa , the orientational correlation time τr , and the boundary line tension λ . In order to keep the number of independent parameters to a minimum , it is again convenient to rewrite the energy of the VM , Eq ( 1 ) , in a scaled form [49 , 59] . We first choose Ki = 1 and set A i 0 = π as an area scale . For simplicity , we assume that all perimeter and junction tensions are the same , i . e . , we set Γi ≡ Γ and Λμ , ν ≡ Λ for all i , μ and ν . Then , as discussed below Eq ( 1 ) , we can complete the square on the second and third terms in Eq ( 1 ) and obtain the scaled VM potential E V M = ∑ i = 1 N 1 2 A i - A 0 2 + ∑ i = 1 N Γ 2 P i - P 0 2 , ( 20 ) where P0 = −Λ/Γ and A0 = π . The first term in Eq ( 20 ) penalises changes in the cell area , while the second term penalises changes of the perimeter . There is no reason for the preferred area A0 to be generically compatible with the preferred perimeter P0 . This sets up a competition between the two terms in Eq ( 20 ) , giving a natural scale that is determined by the relative ratio of Γ P 0 2 to K A 0 2 . In other words , if K A 0 2 > Γ P 0 2 , the cell will try to optimise its area at the expense of paying a penalty for not having the most optimal perimeter , and the opposite if K A 0 2 < Γ P 0 2 . Bi , et al . [59] introduced the dimensionless shape factor p 0 = P 0 A 0 , which controls the ratio of the cell’s perimeter to its area through the target area A0 and target perimeter P0 . The value of p0 then determines whether the area or the perimeter term in Eq ( 20 ) wins and effectively sets the preferred shape of each cell: cells of different shapes have different values of p0 . For example , regular hexagons , pentagons , squares and triangles correspond to p0 = 3 . 722 , p0 = 3 . 812 , p0 = 4 . 0 and p0 = 4 . 559 , respectively . Remarkably , one observes [49 , 59 , 86] a transition between a solid-like behaviour of the tissue , where cells do not exchange neighbours , and liquid-like behaviour , where neighbour exchanges do occur , at p0 = 3 . 812 , a value that corresponds to a regular pentagon . At present , the biological significance of this observation is not clear , but it appears to be a robust feature of many experimental systems [88] . In order to make the comparison between the AVM and the SPV model , we also adopt p0 as a main parameter that controls the preferred cell shape . In order to initialise the simulation , in each run we start by placing soft spheres with slightly polydisperse radii in a circular region . We then use SAMoS to minimise the energy of a soft sphere packing in the presence of a fixed boundary . This ensures that initially , cells are evenly spaced without being on a grid . We also fix the packing fraction to ϕ = 1 , ensuring that the average cell area of the initial configuration is 〈A〉 = A0 . The boundary is either fixed ( referred to as “fixed system” ) , or allowed to fluctuate freely ( “open system” ) . Fig 6 shows a representative set of the states that we observe . We run the simulation for either 100 , 000 time steps with step size δt = 0 . 01 in the unstable region ( e . g . , Fig 6e ) , or 250 , 000 time steps with δt = 0 . 025 in the solid-like region ( e . g . , Fig 6c ) . For these systems with N = 1000 cells in the interior , this takes between 10–40 minutes on a single core of a modern Intel Xeon processor depending on the number of rebuilds of the Delaunay triangulation that are necessary ( more in the liquid-like phase ) . The unit of time is set by γ/Ka2 , where a ≡ 1 is the unit of length . We note that Bi , et al . use a = A 0 as the unit of length . This is possible as long as cells are not allowed to grow , i . e . , when A0 does not change in time . The AVM allows for the cells to change their size and therefore we need to choose a different unit of length . In our case , a is the range of the of soft-core repulsion between cell centres ( see S1 Appendix , Eq . ( 35 ) ) . At low values of p0 , we find a system that prefers to be in a state with mostly hexagonal cells , unless the active driving fa is very high . Open systems will shrink at this point so that all cells are close to their target P0 , as shown in Fig 6a . Consistent with this , larger values of the perimeter modulus Γ lead to stronger shrinking . For fixed systems , this route is blocked , and instead there is a strong inward tension on the boundaries and a gradient in local density , as shown in Fig 6b . In agreement with the results of Bi , et al . [59] , we find that at low p0 < 3 . 81 and low values of driving fa , cells do not take an organised pattern and do not exchange neighbours . Recast in the language of solid state physics , the tissue is in an amorphous solid or glassy state . In Fig 6c we show such a state for a fixed boundary . In order to characterise the physical properties of this state , we measure the dynamical time scale of cell rearrangements through a standard tool of the physics of glassy systems , the self-intermediate scattering function [15] F q , t = exp i q · r ( t ) - r ( 0 ) . ( 21 ) F ( q , t ) measures the decay of the autocorrelation of cell-centre positions r ( t ) at a particular wave vector , q , taken usually to be the inverse cell size q ≡ |q| = 2π/a . The long-time decay of F ( q , t ) is characterised by the so-called alpha-relaxation time τα at which F ( q , t ) has decayed by half . When the system solidifies , i . e . when neighbour exchanges stop , r ( t ) remains constant and hence τα diverges [15] , and stays infinite within the solid phase . In Fig 7a–7c , we show the phase diagram of τα as a function of p0 and fa , for several systems with different boundary conditions . In Fig 7a we show regions of solid-like and liquid-like phases in a system with fixed boundaries , at Γ = 1 , and a low noise value of τr = 0 . 01 . We find a boundary of the solid-like phase that stretches from p0 ≈ 3 . 81 at small fa to a maximum activity fa beyond which the system is fluid at all p0 . This is qualitatively , but not quantitatively consistent with the results of Bi , et al . , who find a transition line at roughly twice our fa values . Several factors are likely implicated in this discrepancy . Our systems , at N = 1000 cells , are more than twice as large as the N = 400 systems considered by Bi , et al . , and finite system size effects seem to play an important role , as shown below . We measure τα at a value of 1/q corresponding to displacements of one cell size . However , even though displacements are large , we have evidence that this may not be sufficient to induce T1 transitions and therefore fluidise the system . Finally , fixed boundaries were used here and the periodic boundaries of Bi , et al . are likely not strictly equivalent . The influence of the type of boundary conditions is very significant . In Fig 7b , we show the phase diagram for the same Γ = 1 and τ r - 1 = 0 . 01 as in Fig 7a , except with open boundary conditions and boundary line tension λ = 0 . Separately , for Γ = 0 . 1 , we have also confirmed that the value of the boundary line tension does not significantly affect the onset of the solid-like regime . We find a significantly lower maximum fa for the transition , fa = 0 . 03 , a factor of 10 compared to the fixed case . We note that the effect also persists at τ r - 1 = 0 . 1 , but is less pronounced . While we do not have a full explanation for this result , we do note that fluctuations of the boundary allow for rearrangements that are otherwise strongly suppressed by the fixed boundary . For example , the system in Fig 6d shows significant boundary fluctuations . It is liquid-like with τα ≈ 10 , whereas the equivalent fixed system has τα ≈ 100 . In view of the significant role of the boundary , we expect a strong system-size dependence . At very high p0 and low active driving , we observe a systematic increase of τα ( especially visible in Fig 7c ) . This unexpected result is accompanied by structural changes in the cell patterns that we observe . Fig 6f shows a liquid system at p0 = 3 . 95 , near the relative minimum τα for a given fa . The distribution of cell centres appears random . In contrast , as can be seen in Fig 6g , at very high p0 = 4 . 85 , cells arrange themselves into rosette shapes , where many vertices meet in a point . Rosettes are a feature of many developmental systems [89] , so it is interesting to see that they do appear in the AVM context . Cell centres also arrange themselves in equidistant chains , hinting at a connection to one of the various pattern-formation instabilities studied in nonlinear dynamics . We note that this regime is numerically delicate , and the addition of the soft repulsive core between cell centres ( see S1 Appendix , Eq . ( 35 ) ) is necessary to make simulations stable . This simulation is performed deep inside the liquid regime where cell junctions are not necessarily accurately represented by straight lines and the applicability of the model is questionable . At present it is , therefore , not clear whether the configuration shown in Fig 6g is an artefact of the model or it indeed has biological significance . One should proceed with caution when assigning biological interpretation to any configuration with very large values of p0 , i . e . for p0 ≳ 4 . 6 . In parts of the phase diagram , we observe a fingering instability [90–93] where regions a few cells wide migrate outward from the centre , as shown in Fig 6e . When τα drops below approximately 10 , we observe that the fluctuations of the boundary already present in Fig 6d become unconstrained . This is a mechanically unstable regime: Eventually , these cells will detach , a process we are not yet able to model due to the topological change that it would imply ( see , Fig 3 ) . We have observed that fluctuations need to reach a threshold of approximately >5% of a length increase in the boundary to break through to an unconstrained growth , otherwise the system remains stable , see e . g . Fig 6d–6g . We then associate a time scale τinst with reaching this threshold and use it to measure the degree of instability: a small time scale denotes a rapid growth rate of fluctuations . Fig 7c shows τα , and Fig 7d shows τinst for the same open system with Γ = 0 . 1 , τ r - 1 = 0 . 1 and boundary line tension λ = 0 . 1 . We note that the transition line between solid-like and fluid-like states is low , at fa = 0 . 03 . At and below fa = 0 . 1 , the boundary of the system is stable , and above this threshold , the instability becomes more pronounced with increasing fa and smaller τα . The physical mechanism responsible for the instability involves a subtle interplay of fa , boundary line tension ( stronger line tension suppresses the instability ) , the noise level τ r - 1 ( lower τ r - 1 enhances the instability ) , and p0 . The instability resembles observations of finger formation in MDCK monolayers [90 , 91] . Existing models link it to either leader cells [93 , 94] , a bending instability [92] , or an active growth feedback loop [95] , while here it emerges naturally . A detailed account of this phenomenon will be published elsewhere . Division and death processes are important in any living tissue , for example , cell division and ingression processes play essential roles during development . Therefore , as noted in Sec . “Cell Growth , Division and Death” , the AVM is equipped to handle such processes . It is important to note , however , that the removal of one cell during apoptosis or ingression and the addition of two new cells during division in the AVM causes a discrete change in the Voronoi tessellation which implies a discontinuous change of the local forces derived from the VM . We have simulated the growth of a small cluster of cells to assess whether this discrete change in geometry can lead to any instabilities in the model . These test runs did not reveal any artefacts due to discontinuities in the force caused by the division events . In order to illustrate the growth process , we choose a shape factor , p0 = 3 . 10 , corresponding to Γ = 1 and Λ = −5 . 5 and no active driving , i . e . , we set fa = 0 . This puts the system into the solid-like phase where T1 events are absent . Our simulation runs for 106 time steps at δt = 0 . 005 , corresponding to 5000 time units , starting from 37 cells and stopping at about 24 , 000 cells . To balance computational efficiency with a smooth rate of division , cells are checked for division every 25 time steps . We show snapshots of different stages of the tissue growth in Fig 8a–8e . We note that the numerical stability of the simulation that involves growth is quite sensitive to the values of the parameters used in the AVM . For example , divisions of highly irregularly shaped cells , as commonly observed in the high p0 regime , can put a significant strain on the simulation and even cause a crash . Helpfully , some of these problems are alleviated by the soft repulsive potential between cell centres ( see S1 Appendix , Eq . ( 35 ) ) . This in addition to a smaller time step is used to mediate the impact of cell divisions for growing systems with high p0 . In Fig 8f we show the tissue size as a function of the simulation time . In this simulation there are no apoptosis or cell ingression events and , as expected , the tissue size grows exponentially . However , at long times , the growth slows down and deviates from exponential growth . This is easy to understand , as the centre of the tissue is prevented from expanding by the surrounding cells . The effect can be seen in Fig 8e , where cells located towards the centre have , on average , smaller areas and in Fig 8g , which shows a clear pressure buildup in the centre . This suggests that in the later stages , the simulated tissue is not in mechanical equilibrium any more . The pressure is computed as the trace of the Hardy stress tensor , defined as [96] σ ^ w H = 1 2 ∑ α , β α ≠ β ∫ s = 0 1 - f α β ω ( 1 - s ) r α + s r β - r ⊗ r α - r β d s , ( 22 ) where ω is a smoothing function and the sum is over all junctions and triangulation edges . The reason is that we can determine the shape and area of each cell using just the scalar lengths , {rαβ} , of these two sets of edges . We eliminate the integral by choosing , ω ( r ) = 1 / A D if r ∈ D 0 otherwise ( 23 ) where D is the region for which the stress is calculated and A D is the area of D . For convenience we choose D to coincide with individual cells . Finally , f α β = - ∂ E V M ∂ r α β r ^ α β , where EVM is defined in Eq ( 1 ) and r ^ α β is the unit-length vector along the junction or triangulation edge denoted by ( α , β ) . This particular choice of ω and D reduces our calculation to that of the more common virial stress [96] , but we note that the Hardy stress is a useful tool for coarse-graining . A full discussion regarding coarse-graining of stress calculations in the AVM will be published elsewhere . We also see clear heterogeneities in the local pressure shown in Fig 8g . In Fig 8h , we show the radial pressure profile in the tissue at the end of the simulation . From the figure it is also evident that the there is a substantial pressure buildup close to the centre of the tissue as well as that angular averaging substantially reduces local pressure fluctuation notable in Fig 8g . The origin of these effects warrants a detailed investigation and will be addressed in a later publication , we note however that stress inhomogeneities are a persistent feature of the epithelial cell monolayers that have been investigated by traction force microscopy [12 , 97] . A similar pressure buildup has also been investigated in a growing cell aggregate [98] and in a mathematical model of nonuniform growth in a layer of tissue [99] . Finally , in Fig 8i we show the distribution of the number of neighbours for this model system . The observed distribution is in qualitative agreement with observations on several tissues both in animals and plants ( e . g . , Drosophila wing disc , Xenopus tail epidermis , Hydra outer epidermis , Anagallis arvensis meristem , cucumber epidermis ) reported in the literature [100 , 101] . We note that while the relative values of the percentages of nearest neighbours are dependent on the parameters used in the model , we observed that the overall shape of the distribution is maintained over a several sets of parameters chosen in different regions of the parameter space . A detailed study of this distribution and its precise dependence on the model parameters is , however , beyond the scope of this study . The AVM is equipped to allow for cell-specific parameters , which enables us to investigate tissues with locally varying mechanical properties . A commonly studied example of the effects such heterogeneities is cell sorting . As an example we show simulations that display sorting of two distinct cell types . We achieve this by setting the junction tension Λ for each pair of cell-cell and cell-boundary contacts . All our simulations consist of 1000 cells with half chosen randomly to be of the “red” type and the others being of the “blue” type . In these simulations , boundaries have been kept fixed . We observe sorting behaviour akin to that found in other commonly used tissue models [35 , 102] . Using r , b and M to denote red , blue and the boundary respectively , we start by fixing K = 1 and Γ = 1 and set −6 . 8 = Λrr < Λrb < Λbb = −6 . 2 , corresponding to p0 in the range 3 . 58–3 . 93 . We , however , note that p0 is a quantity defined “per cell” and one should understand it in this context only as a rough estimate whether a given cell type is in the solid or fluid phase . All cells are subject to small random fluctuations of their position which allows for T1 transitions that can bring initially distant cells into contact . We set the active driving , fa , to zero . We have chosen different values for Λrr and Λbb to reflect the idea that the surfaces of these cells have different adhesive properties [103] . Note that the Λ parameter for a particular contact is proportional to its energy per unit length . Sorting of cells into groups of the same type occurs when the energy of two red-blue contacts is greater than the energy of one red-red contact and one blue-blue contact , corresponding to Λrb > ( Λrr + Λbb ) /2 , see Fig 9a–9c . In this regime , for cells of the same type it is energetically favourable for the new contact to elongate while local red-blue contacts are shortened . Conversely , if Λrb < ( Λrr + Λbb ) /2 , then cells maximise their red-blue contacts forming a “checkerboard” pattern ( Fig 9d ) . The final pattern is not without defects , the number and location of which depend on the initial conditions . The tissue boundary consists of contacts between cell centres and boundary particles so ΛrM and ΛbM need also to be specified to reflect the way in which the cell types interact with the extracellular matrix or surrounding medium . Initially we set ΛrM = ΛbM = −6 . 2 and observe that blue cells cover the boundary enveloping red cells because this facilitates lower energy red-blue and red-red contacts being formed . If we incentivise red-boundary contacts by setting ΛrM < Λrr + ΛbM − Λrb = −6 . 6 we make red-boundary contacts preferable [102] . This case is shown in Fig 9e for ΛrM = −6 . 8 . Finally , we note that all simulations for mechanically heterogeneous systems were performed without any active driving . While a detailed study of the effects of active driving on cell sorting is beyond the scope of this study , we note that a limited set of test runs suggest , as expected , that including activity can reduce the time over which cells sort but that very high activity leads to mixing . We now briefly turn our attention to the effects of several models of cell polarity alignment . So far , we have assumed torque τi = 0 in Eq ( 14 ) , i . e . , we are in the situation where the the polarisation vector of each cell is independent of the surrounding cells and its direction diffuses randomly over time . In biological systems , it is known that a cell’s polarity responds to the surrounding and many forms of polarity alignment have been proposed . Here , we highlight two alignment mechanisms that are compatible with the current understanding of cell mechanics . In Fig 10a–10c , we have used the alignment model defined in Eq ( 9 ) that assumes that the polarity vector ni of cell i aligns with its velocity vi . The torque term in Eq ( 14 ) is then given by τi = −Jv vi × ni , where Jv is the alignment strength . This model was first developed for collectively migrating cells ( modelled as particles ) [74] , and it exhibits global polar migration , i . e . a state in which all particles align their velocities and travel as a flock . In dense systems of active particles confined to a finite region , velocity alignment has been shown to be intimately linked to collective elastic oscillations [75] . It is remarkable that the main hallmarks of this active matter dynamics are also observed in the model tissue . In Fig 10a , we show velocity alignment dynamics for a confined system in the solid-like phase; here the collective oscillations are very apparent . They are strikingly reminiscent of the collective displacement modes observed in confined MDCK cell layers [104 , 105] . In Fig 10b , we apply the same dynamics , but now to a system that is in the liquid-like phase , with fixed boundaries . Here , the collective migration wins , but the confinement to a disk with fixed boundaries forces the cells into a vortex-shaped migration pattern . Finally , in Fig 10c , in the absence of confinement , we recover the collective polar migration of the cell patch . In Fig 10d , we show the effects of aligning the cell’s polarity to the largest principal axis of the cell shape tensor , defined in Eq ( 10 ) . This type of alignment also leads to collective motion in an unconfined system , however there are significant fluctuations as the allowed cell patterns are highly frustrated by the constraint to remain in a Voronoi tesselation . These preliminary results serve as a showcase of the non-trivial effects of cell-cell alignment on the collective behaviour of the entire tissue . A more detailed account of the effects of different alignment models will be published elsewhere . In the previous discussions , all examples assumed a patch of cells with the topology of a disk . However , the AVM is not restricted to the circular geometry and can be applied to systems of arbitrary shapes , including domains with complex connectivity . Such situations often arise when modelling experimental systems where cells surround an obstacle , or in studies of wound healing . In Fig 11 we present a gallery of non-circular shapes that can be readily studied using the AVM as it is implemented in SAMoS . The annular geometry shown in Fig 11a would be suited for modelling wound healing problems as well as situations where cells migrate in order to fill a void . A common experimental setup where cell colonies are prepared as rectangular strips [90] is shown in Fig 11b , where three separate patches grow towards each other . Finally , in Fig 11c we show an example of yet another very interesting situation [106] , where cells are grown in a confined region of space . In this paper we have introduced the Active Vertex Model . It is a hybrid model that combines ideas from the physics of active matter with the Vertex Model , a widely used description for modelling confluent epithelial tissues . Active matter physics is a rapidly growing field of research in soft condensed matter physics , and it is emerging as a natural framework for describing many biophysical processes , in particular those that occur at mesoscales , i . e . , at the scales that span multiple cells to the entire tissue . Our approach is complementary to the recently introduced Self-Propelled Voronoi model [59] , for it allows modelling of systems with fixed and open , i . e . dynamically changing boundaries as well as cell-cell alignment , cell growth , division and death . The AVM has been implemented into the SAMoS software package and is publicly available under a non-restrictive open source license . The AVM utilises a mathematical duality between Delaunay and Voronoi tessellation in order to relate forces on cell centres to the positions of the vertices of the dual lattice , i . e . meeting points of three of more cells—a natural description of a confluent epithelial tissue . This not only allows for a straightforward and efficient implementation using standard algorithms for particle-based simulations , but provides a natural framework for modelling topological changes in the tissue , such as intercalation and ingression events . In other words , in the AVM T1 transition events arise spontaneously and it is not necessary to perform any additional steps in order to ensure that cells are able to exchange neighbours . Furthermore , our implementation of the AVM is very efficient , allowing for simulations of systems containing tens of thousands of cells on a single CPU core , thus enabling one to probe collective features , such as global cell flow patterns that span length-scales of several millimetres . In addition , the AVM is also able to handle multiple cell types and type specific cell contacts , which allows simulations of mechanically heterogeneous systems . All these features make the AVM a strong candidate model to address many interesting biological and biophysical problems related to the mechanical response of epithelial tissues , especially those that occur at large length and time scales that are typically only accessible to continuum models . Unlike in the case of continuum models where relating parameters of the model to the experimental systems is often difficult and unclear , the AVM retains the cell-level resolution , making it simpler to connect it to the processes that occur at scales of single cells . The AVM is , however , not designed to replace continuum models , but to serve as the important layer that connects the complex molecular processes that occur at the cell level with the global collective behaviour observed at the level of the entire tissue . A natural question to ask is: What is the advantage of the AVM compared to other particle based models , e . g . [43 , 44] , that are computationally far less demanding ? There is clearly a tradeoff between computational costs and the required level of details necessary to address a specific biological question . It is , however , not a priori clear where the right balance between the two lies . The key advantage of the AVM compared to other cell-centre based models is that keeping track of both cell centres and cells themselves allows for straightforward extensions of the model to include effects such as active forces on vertices , active non-linear response of cell junctions , etc . that would be impossible to implement and parametrise in purely cell-centre based models . With that in mind , there are , of course , still many ways the model can be improved . For examples , it would be very interesting to augment the AVM to include the effects of biochemical signalling . This would require solving a set of differential equations for signals in each time step , and then supplying those solutions to the mechanics part of the model . Adding such functionality would substantially increase the computational cost of simulations , however at the same time it would allow for detailed studies of the coupling between chemical and mechanical signalling . These are believed to be essential for developing a full understanding of the mechanics of epithelial tissues . Given the layout of the AVM and its implementation , implementing such functionality would be straightforward . Furthermore , in the current version of the AVM activity is introduced in a very rudimentary manner , via assuming that cells self-propel in the direction of their polarity vector . This is a very strong assumption that would need a much stronger experimental support than currently available . It is also possible that a far more sophisticated model would be required to fully capture cell motility . However , one also needs to keep in mind that there is a tradeoff between being as biologically accurate as possible and retaining a sufficient level of simplicity to be able to efficiently perform simulations of large systems . With all this in mind , we argue that the our simulations clearly show that even this simplistic model of self-propulsion is capable of capturing many features of real systems , and that it can serve as a good starting point for building biologically more accurate descriptions . Another potentially very interesting feature that is currently not supported would be splitting and merging of the boundaries , that is , allowing for topological changes of the entire sheet such as those depicted in Fig 3c . This would allow us to study detachment of a part of the tissue or opening apertures as well as the opposite problem of closing holes and gaps . The latter is of great importance for studying problems related to wound healing . Unfortunately , setting up a set of general rules on how to automatically split a boundary line or merge two boundaries into a single one is not a simple task from a point of view of computational geometry . The problem is further complicated if those rules are also to be made biologically plausible , which is essential for the model to be relevant to actual experiments . We conclude by noting that recently there have been several interesting attempts at extending the Vertex Model description to three dimensions [85 , 107–112] . While in principle possible , extending the AVM to a curved surface or making it fully three-dimensional would be quite involved . Being able to study curved epithelial sheets would be of great interest to systems where curvature clearly cannot be ignored , e . g . , as is the case in modelling intestinal crypts [113–116] . While there is nothing in the description of the AVM that is unique to the planar geometry , there are several technical challenges associated with directly porting it onto a curved surface . Most notably , building a Delaunay triangulation on an arbitrary curved surface is not a simple task . In addition , quantities such as bending rigidity that are naturally defined on triangles would have to be properly mapped onto contacts lines between neighbouring cells . This is not straightforward to do . Developing a fully three-dimensional version of the AVM would be an even a greater challenge since the duality between Delaunay and Voronoi descriptions central to this model has no analogue in three dimensions . We hope that the AVM will provide a useful and complementary tool for probing the aspects of the epithelial tissue mechanics that are not available to other methods , as well as serve as an independent validation for the results obtained by other methods .
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We present a detailed analysis of the Active Vertex Model to study the mechanics of confluent epithelial tissues and cell monolayers . The model combines the commonly used Vertex Model for describing epithelial tissue mechanics with the active matter dynamics extensively studied in soft matter physics . We utlise an exact mathematical mapping that enables a very efficient numerical implementation using standard methods for simulating particle-based models . System sizes accessible to this model allow us to probe the dynamical motion patterns that occur in tissues over a range of length- and time-scales previously inaccessible to available simulation tools . Our model also includes a number of essential features required to properly describe actual biological systems such as cell growth , cell division and aptotsis , as well as the dynamic boundary of the epithelial sheet . This allows us to study phenomena such as the finger-like protrusions in cell monolayers and processes related to wound healing . The model is implemented into the SAMoS simulation software package and is publically available under a non-restrictive open source licence .
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"discussion"
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2017
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Active Vertex Model for cell-resolution description of epithelial tissue mechanics
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Neural systems are inherently noisy , and this noise can affect our perception from moment to moment . This is particularly apparent in binocular rivalry , where perception of competing stimuli shown to the left and right eyes alternates over time . We modulated rivalling stimuli using dynamic sequences of external noise of various rates and amplitudes . We repeated each external noise sequence twice , and assessed the consistency of percepts across repetitions . External noise modulations of sufficiently high contrast increased consistency scores above baseline , and were most effective at 1/8Hz . A computational model of rivalry in which internal noise has a 1/f ( pink ) temporal amplitude spectrum , and a standard deviation of 16% contrast , provided the best account of our data . Our novel technique provides detailed estimates of the dynamic properties of internal noise during binocular rivalry , and by extension the stochastic processes that drive our perception and other types of spontaneous brain activity .
Despite appearing constant , our sensory perception fluctuates from moment to moment because of the non-deterministic nature of biological neurons . This ‘internal noise’ operates at multiple timescales , and affects our decisions about sensory information . Internal noise is particularly apparent in bistable phenomena such as binocular rivalry , in which our perception of conflicting images shown to the two eyes fluctuates over time in a stochastic fashion . Because phenomena like rivalry make otherwise invisible processes available to conscious perception , they provide a useful tool for probing the properties of internal noise . In a typical rivalry experiment , participants view sine wave grating patterns with orthogonal orientations in the left and right eyes ( see Fig 1A ) . They are asked to report which stimulus they perceive at each moment in time by continuously pressing a response button that corresponds to the perceived orientation . Histograms of the durations for which each image remains dominant typically have positive skew , approximating a gamma distribution ( or a normal distribution on logarithmic axes ) . Computational models of rivalry ( e . g . [1–4] ) have successfully explained the statistical pattern of percepts reported by assuming the presence of three key processes: inhibition between neurons representing the two stimuli , adaptation to the dominant stimulus , and noise . Inhibitory processes have been investigated using dichoptic masking paradigms [5–7] and by varying the properties of rivalling stimuli [8–11] , and there is direct evidence of adaptation during a period of dominance [12] . However , comparatively little is known about the precise properties of the noise , as there have been few attempts to investigate it directly , despite recognition of its importance [13–16] . One exception is a study that randomly manipulated the coherence of rivalling dot motion stimuli throughout a trial in order to influence alternations [17] . By reverse-correlating coherence with the observers’ percepts , a biphasic profile was apparent , in which coherence was stronger in the suppressed eye and weaker in the dominant eye during the ~1s preceding a flip . This pattern was reversed at longer pre-flip durations , and overall the results were predicted by a simple rivalry model featuring adaptation and mutual inhibition . Although the results demonstrate that external noise can influence rivalry alternations , the parameters of the external noise were not manipulated , and so the results can reveal little about the characteristics of internal noise . Other work has aimed to influence rivalry alternations by periodically changing the contrast of the rivalling stimuli . In a study by O’Shea and Crassini [18] , the contrasts of rivalling gratings were periodically reduced to 0 , either in phase or in antiphase across the eyes . At modulation frequencies above 20Hz ( and sometimes as low as 3Hz ) , rivalry alternations still occurred as normal regardless of phase , suggesting a persistance in the underlying mechanism ( see also [19 , 20] ) . In a related study , Kim , Grabowecky and Suzuki [1] used a square wave temporal modulation to alter the contrast of rivalling stimuli in antiphase ( i . e . one stimulus increased in contrast and the other decreased at the same time ) at a range of temporal frequencies from 0 . 28Hz to 2 . 48Hz . This manipulation caused a peak in the histogram of dominance durations at the half period of the modulation frequency . The increase was greatest when the half period was 600ms , a duration corresponding to the peak of the histogram for unmodulated rivalry using the same stimuli . Furthermore , there were additional peaks at odd integer harmonics of the modulation frequency . The authors consider this to be evidence of a stochastic resonance effect , and support this with a computational model of rivalry alternations . Here we extend these approaches by modulating the contrast of rivalling stimuli using two independent dynamic noise sequences instead of square wave modulations ( see Fig 1B and 1C ) . As well as measuring the effect on dominance durations , this design allows us to cross-correlate the participant’s reported percept with the timecourse of the external noise . In addition , we can use the same noise sequences multiple times , and measure the consistency of the participants’ percepts in a dynamic version of the ‘double pass’ paradigm [21 , 22] . If the external noise sequences were entirely determining perception , responses should be identical across the two repetitions . On the other hand , if the external noise sequences have no influence on perception then the similarity of responses will be determined by internal noise , and response consistency will be that expected by chance . The empirically measured consistency scores will therefore give an index of the relative influences of internal and external noise on perception . By manipulating the variance and temporal frequency content of the noise sequences , we can investigate properties of the internal noise that influence rivalry alternations . We interpret the results with reference to an established computational model of rivalry proposed by Wilson [3 , 4] ( see Fig 2 ) , to which we add different types of internal noise .
In the absence of any noise modulations , binocular rivalry produced a typical histogram of dominance durations with a positive skew ( see grey curve in Fig 3Ai ) , and a mean of 2 . 7 seconds . A 5x5 repeated measures ANOVA indicated that the mean dominance duration depended on both temporal frequency ( F ( 4 , 16 ) = 34 . 43 , p<0 . 001 , ηp2 = 0 . 90 ) and modulation contrast ( F ( 4 , 16 ) = 8 . 15 , p<0 . 01 , ηp2 = 0 . 67 ) , and also showed that the two variables interacted ( F ( 16 , 64 ) = 18 . 01 , p<0 . 001 , ηp2 = 0 . 82 ) . The histograms in Fig 3A show that at lower temporal frequencies ( panels on the left ) , strong contrast modulation resulted in slightly more long-duration percepts ( an increase in positive skew ) , whereas at higher temporal frequencies ( panels on the right ) the peak of the histogram shifted leftwards ( compare lower vs upper traces in Fig 3Av ) . These patterns were reflected in both the change in means ( Fig 3B ) and also the shift in the autocorrelation functions ( Fig 3C ) , such that high temporal frequencies ( e . g . the purple curve ) had a shorter lag than long ones ( e . g . the red curve ) . The functions in Fig 3B begin to diverge at a standard deviation of around 4% contrast , and data from individual participants showed a similar pattern ( see S1 Fig ) . We also cross-correlated the noise time course ( difference between left and right eye contrasts for the 16% contrast modulation conditions pooled across all temporal frequencies ) with the participants’ continuous percept reports . In the traces shown in Fig 3D , a lag of 0s ( given by the vertical dashed line ) would indicate that participants responded to a stimulus-driven alternation immediately . However , the peak response lag was 583ms , somewhat faster than estimates from previous studies [8] . The mean cross-correlation coefficient at the peak was 0 . 35 , indicating that a substantial proportion of the variance in participant percepts was predictable from the changes in stimulus contrast . Functions for individual participants are shown by the thin traces in Fig 3D , and are similar to the mean . The fact that the cross-correlation function remains slightly above zero at positive lag times might appear to indicate ( somewhat counterintutively ) that percepts were driven by the future state of the stimulus . However this is simply a consequence of the bandpass filtering of the external noise sequences , which means that stimulus contrasts at one instant are predictive of contrasts shortly afterwards . Note that the auto- and cross-correlation functions shown here differ from the switch-triggered-average reverse correlation measure reported by Lankheet [17] , and the serial correlation measures used by Lehky [14] , van Ee [23] and others ( where ‘lag’ on the x-axis refers to dominance epoch rather than time ) . These measures assess different aspects of rivalry data that are not the focus of the current work . Next , we calculated the consistency of responses across pairs of presentations of identical noise streams . In the absence of any noise modulation , the mean consistency was slightly above the expected baseline of 0 . 5 , having a value of 0 . 53 ( horizontal grey lines in Fig 4 ) . One possible explanation for this is that slight eye dominances or biases towards one or other stimulus will increase the consistency across repetitions , however the effect was very small and was not statistically significant ( t = 1 . 2 , df = 4 , p = 0 . 1 ) . For conditions where the stimulus contrast was modulated , a 5x5 repeated measures ANOVA indicated that the response consistency depended on both temporal frequency ( F ( 4 , 16 ) = 9 . 90 , p<0 . 001 , ηp2 = 0 . 71 ) and modulation contrast ( F ( 4 , 16 ) = 28 . 81 , p<0 . 001 , ηp2 = 0 . 88 ) , as well as the interaction between the two variables ( F ( 16 , 64 ) = 3 . 55 , p<0 . 001 , ηp2 = 0 . 47 ) . These effects are shown in Fig 4 , which plots the same data twice as a function of either modulation contrast ( Fig 4A ) or temporal frequency ( Fig 4B ) . The general trends are that consistency increases with contrast , and at each contrast is strongest for the 1/8Hz temporal frequency ( shown in green ) . The maximum consistency was 0 . 72 , for the 1/8Hz , 16% contrast condition , which is particularly noteworthy given that this temporal frequency had the weakest influence on dominance durations ( see green points in Fig 3B ) . This suggests that frequencies closest to the natural period of rivalry oscillations are able to entrain perception most strongly ( see Kim et al . , 2006 ) . Consistency exceeded baseline for the 1/8Hz condition at around 4% modulation contrast ( green diamonds in Fig 4 ) . These main findings were also clear in the data of individual participants , shown in S1 Fig . We first investigated how the amplitude of internal noise , and its spectral slope ( ɑ ) , affected model behaviour . We selected a single stimulus condition ( stimulus noise frequency of 1/8Hz and standard deviation of 16% contrast ) and ran the model with a range of internal noise variances ( SD = 1–64% contrast ) at five different spectral slopes ( ɑ = 0–2 ) . The results of our simulations on dominance duration and response consistency are shown in Fig 5A ( i-v ) , with the equivalent human data plotted in green for comparison . For all spectral slopes , as internal noise contrast increased it more strongly affected rivalry alternations . This is shown by the change in dominance duration ( Fig 5B; increases for steep slopes and decreases for shallow slopes ) , and response consistency ( Fig 5C ) , which decreased as responses became increasingly dominated by internal noise . We can use the joint dominance durations and consistency scores to rule out several types of internal noise . White internal noise ( ɑ = 0 ) is not viable because there is no internal noise level for which both durations and consistency are close to human levels . Internal noise with steep amplitude slopes ( ɑ > 1 ) produces sensible consistency scores , but dominance durations become too long . This leaves slopes of ɑ = 0 . 5 and ɑ = 1 , for which an internal noise contrast of around 16% gives a good approximation to the human data . We performed full simulations for all noise spectral slopes with this contrast . A slope of ɑ = 1 was the best predictor of the human data , so these simulations are discussed in the main text , with simulations of other spectral slopes presented in S2 Fig and S3 Fig . The histograms of dominance durations , mean dominance duration and response consistency of the model simulations for all 26 stimulus conditions are shown in Fig 6 . The model replicated the pattern of human data shown in Figs 3 & 4 remarkably well . The histograms of dominance durations of the model ( Fig 6A i-v ) show similar trends to those of human observers ( Fig 3A ) . Slow modulation frequencies ( 1/16Hz and 1/8Hz ) increased positive skew at high modulation contrasts ( Fig 6A i-ii ) , while higher modulation frequencies shifted the peak of the dominance duration histograms leftwards as modulation contrast increased . The shifts in the histograms are reflected in the mean dominance durations of the model ( Fig 6B ) , just as with human observers . Similarly , response consistency ( Fig 6C and 6D ) increased when stimulus noise contrast reached and SD of 4% and was highest for each contrast at a temporal frequency of 1/8Hz . Whereas human response consistency was quite bandpass ( peaking at 1/8Hz and dropping quickly for faster frequencies ) , the model exhibited slightly broader tuning at high stimulus noise contrast . This may be due to the other parameters of the model that were fixed prior to our simulations , or it could imply additional physiological constraints such as bandpass temporal filters on the input , or variable response lag . We next explored whether the model could predict performance in novel conditions . Inspired by Kim et al . [1] , we designed a further condition in which the noise modulations were in antiphase across the eyes ( i . e . a contrast increase in one eye matched with an equal contrast decrease in the other ) . We chose a temporal frequency of 1/8Hz , and tested four of our original participants . With no additional parameters , the model described above made a clear quantitative prediction about performance in this condition ( see Fig 7A ) , namely that response consistency should be reliably increased for the antiphase noise ( brown squares in Fig 7A ) , compared to the equivalent condition from the main experiment with two independent streams of external noise ( green circles in Fig 7A ) . This prediction was borne out empirically , as shown in Fig 7B . We note that dominance duration histograms from our human participants ( and therefore mean dominance durations ) remained relatively unaffected by this manipulation ( see Fig 7C ) , consistent with performance with independent noise streams ( Fig 3Aii ) . We also tested a condition in which we presented both stimuli to both eyes as a plaid , and modulated the contrast of the components . Just as in the main experiment , we asked participants to report which component appeared higher in contrast at each moment in time , though there was no binocular rivalry . This ‘monocular rivalry’ condition also produced greater consistency scores than the equivalent condition from the main experiment ( see Fig 7E ) , and demonstrates that the technique can be used to dynamically monitor perception even in the absence of interocular competition . The distributions of dominance durations were rather broader than for binocular rivalry ( see grey curve ) at low contrast modulations , but narrowed at higher contrasts ( see Fig 7F ) . One explanation of monocular rivalry alternations is that they are largely driven by the interaction between afterimages and eye movements , and could occur in the absence of any neural suppressive alternation process ( e . g . [24] ) . We reasoned that one way to test this account might be to remove the rivalry mechanism from the model , leaving only the combination of internal and external noise to determine dominance at each moment . The predictions for this arrangement are shown by the cyan symbols in Fig 7D , and involve markedly lower consistency scores than both the model and empirical binocular rivalry conditions ( green circles in Fig 7D and 7E ) , and also the monocular rivalry data itself ( cyan diamonds in Fig 7E ) . Clearly then , monocular rivalry still involves some sort of alternation process ( e . g . [25] ) , but the increased empirical consistency scores in this condition suggest that the alternating mechanism is more strongly driven by the external noise modulations than during binocular rivalry . In principle , this could imply that internal noise is more highly correlated ( and therefore effectively weaker ) between monocular units representing the same eye , compared with monocular units representing different eyes .
In the course of developing the model , we also considered several variants using same architecture that were either less successful or less plausible . One variant was a model in which a single source of internal noise was added to both channels . In this arrangement , the internal noise was less effective , because it increased or decreased the response in both channels by the same amount , and so did not materially influence the competition between channels . Another variant placed the internal noise sources outside of the gain control equation ( i . e . added after Eq 1 rather than appearing on the numerator and denominator ) . Although moving internal noise later is consistent with the assumptions of a family of popular computational models of early binocular vision ( [27 , 28] see next section ) , this was less successful than our main model because internal noise levels sufficient to influence consistency had too large an effect on dominance durations . This rendered the dynamic properties of the model moot , with rivalry percepts being largely determined by the internal noise streams . We also tested alternative values of the main parameters in the rivalry model . These altered model behaviour in the unmodulated baseline condition much as described in previous work [4] , but had relatively minimal effects on dominance durations and consistency scores with strongly noise-modulated stimuli , where rivalry alternations depend more on the interplay of internal and external noise than on adaptation and inhibition . We anticipate that other rivalry models with architectures related to that of Wilson [3 , 4] could be modified in a similar way as described here to achieve comparable effects , but have not tested this assumption . As mentioned above , Kim et al . [1] modulated the contrast of rivalling stimuli periodically in antiphase at a range of temporal frequencies ( building on earlier work by O’Shea and Crassini [18] in which rivalling stimuli were entirely removed at different frequencies and phases ) . They implement three computational models to account for their results , each of which has random walk ( i . e . brown ) noise with a spectral slope of 1/f2 , but report obtaining similar results with white noise for their experimental conditions . Furthermore , one of the models they implement is a version of the Wilson [3] model considered here , but they report the best performance when the internal noise is added to the adaptation differential equation ( see Methods ) , rather than the rivalling units ( see also [23] ) . In additional simulations , we found similar effects on the dominance duration distributions for internal noise placed either in the main equation or adaptation equation . However , placing internal noise in the adaptation differential equation resulted in response consistency that was not tuned to modulation frequency ( i . e . , flat ) . We suspect that Kim et al . ’s paradigm did not afford sufficient constraints to distinguish between the two very different internal noise types or the locus of internal noise . Other models that have incorporated a stochastic component include the model of Lehky [2] which also used random walk ( brown ) noise , Kalarickal and Marshall [29] who used additive uniformly distributed ( effectively white ) noise , and Stollenwerk and Bode [30] who used temporally white noise that was correlated across space . A further model developed by Rubin and colleagues [15 , 16] uses exponentially filtered white noise which progressively attenuates higher frequencies . However none of these studies report testing other types of internal noise , nor were their experimental conditions sufficient to offer meaningful constraints on the internal noise properties . As far as we are aware , this is the first study that has modelled internal noise of different amplitudes and spectral properties and compared the predictions to empirical results . Baker & Graf [8] explored binocular rivalry using broadband pink noise stimuli that also varied dynamically in time . By testing factorial combinations of temporal amplitude spectra across the two eyes , they showed that stimuli with 1/f temporal amplitude spectra tended to dominate over stimuli with different spectral slopes ( the same was also true of static stimuli with a 1/f spatial amplitude spectrum ) . Whilst these results do not directly imply anything about the properties of internal noise , they are consistent with the idea that the visual system is optimised for stimuli encountered in the natural world , which are typically 1/f in both space and time ( e . g . [31–35] ) . Our findings here imply that as well as having a preference for external stimuli with naturalistic properties , the internal structure of the visual system might itself have evolved to emulate these temporal constraints [32 , 36–38] . Early models of binocular signal combination attributed the √2 improvement in contrast sensitivity for fusible stimuli viewed binocularly vs monocularly to the pooling of independent monocular noise sources [39] . However this model assumes that during monocular presentation , the noise in the unstimulated eye can be ignored , which is unlikely in the absence of experimental confounds [27] . Contemporary binocular models of contrast detection and discrimination assume noise that is late and additive , occurring at a point beyond binocular signal combination [28] . It is generally assumed that this late source of noise is the combination of multiple noise generators at successive stages of processing , though relatively little is known about their precise characteristics . However a small number of studies have investigated this issue , as we now summarise . Pardhan & Rose [40] added binocular external noise during a monocular or binocular detection task and found that binocular summation decreased at high levels of external noise , and that equivalent input noise ( the minimum external noise level required to influence thresholds ) was higher for monocular than binocular targets . One interpretation of these results is that the effective internal noise is greater for monocularly presented stimuli ( see also [41] ) . However , the type of external noise that they used was broadband white pixel noise , which can also cause substantial gain control suppression ( see [26] ) , potentially confounding the effects of increased variance . These results are therefore relatively inconclusive regarding sources of internal noise in binocular vision . Recently , Ding & Levi [42] have demonstrated that the inclusion of early ( monocular ) multiplicative noise in gain control models can account for some subtle features of binocular contrast discrimination performance . It has also been suggested that monocular noise might be increased in the affected eye of individuals with amblyopia [43] . Finally , we have recently shown [44] using a contrast discrimination paradigm that EEG and MEG data are consistent with both an early ( ~100ms post stimulus onset ) noise source in low level visual areas , and a later noise source in more frontal and parietal brain areas , both of which affect perceptual decisions . All of these results are therefore consistent with an early monocular source of internal noise , as included in our model , but do not preclude the addition of later sources of noise which we do not consider here . Regarding noise more generally , surprisingly few studies have addressed the spectral and distribution properties of internal noise using psychophysical methods . The default assumption is typically that internal noise is Gaussian ( owing to Central Limit Theorem ) and white . However , Neri [45] concluded that internal noise had a Laplacian distribution , and other psychophysical work has assumed Poisson processes for internal noise [46] , based on single cell recordings [47] . Noise with a pink amplitude spectrum typically retains a Gaussian distribution , though in principle non-Gaussian distributions ( such as Laplacian or Poisson distributions ) could also be altered to have a pink spectrum . Although we are unaware of any other psychophysical studies attempting to estimate the spectral characteristics of internal noise , we note that measurements of spontaneous neural activity using ECoG and fMRI also have fractal properties , and a slope of approximately 1/f in visual areas [48] . We anticipate that extending the dynamic double pass approach to tasks and paradigms beyond rivalry has the potential to reveal the generality of our findings . Using a novel dynamic double pass paradigm with binocular rivalry , we measured how alternation rates and response consistency were affected by different types and amounts of external noise . The results were consistent with a computational model of rivalry in which internal noise was independent in each monocular channel . We conclude that internal noise relevant to rivalry has an amplitude spectrum of 1/f , and a standard deviation equivalent to a stimulus contrast around 16% . We anticipate that future studies might use temporally sensitive neuroimaging techniques such as EEG and MEG to further investigate these sources of internal noise .
Procedures were approved by the Ethics Committee of the Department of Psychology at the University of York ( approval number 113 ) . The main experiment was completed by five psychophysically experienced observers ( 2 male ) , who provided written informed consent . Two of the participants were the authors , the remainder were unaware of the aims or design of the study . A control experiment was completed by four of the same observers . All observers had no known abnormalities of binocular vision , and wore their standard optical correction if required . Stimuli were sinusoidal grating patches with a spatial frequency of 1c/deg , subtending two degrees of visual angle , and ramped in contrast by a cosine function over a further ¼ degree . The gratings shown to the left and right eyes had orthogonal orientations ( ±45 degrees ) which were assigned randomly on each trial ( see Fig 1A for examples ) . The mean Michelson contrast ( defined as 100* ( Lmax-Lmin ) / ( Lmax+Lmin ) ) of the gratings was 50% , but this was modulated by dynamic noise streams of various centre frequencies ( 1/16 Hz to 1Hz ) and standard deviations ( 1% to 16% Michelson contrast ) . The noise streams were constructed by bandpass filtering white noise at the required frequency using a one octave bandpass filter ( see Fig 1B ) . In the main experiment , the noise streams used to modulate the contrast of each eye were independent . Stimuli were displayed on a ViewPixx 3D display ( VPixx Ltd . , Canada ) , driven by an Apple Macintosh computer . The monitor operated with 16 bits of greyscale luminance resolution ( M16 mode ) and was gamma corrected using a Minolta LS110 photometer . Independent stimulation of the left and right eyes was achieved using stereo shutter glasses ( NVidia 3D Vision ) , synchronised with the monitor refresh rate of 120Hz via an infra-red signal . To promote good vergence and binocular alignment , each stimulus was surrounded by a static high contrast greyscale Voronoi texture ( squares of 14 x 14 degrees , with a 7 degree diameter disc in the centre set to mean luminance ) that was identical in both eyes ( see Fig 1A ) . A different texture was presented on each trial , selected at random from a set of 99 pre-generated textures . Participants sat in a darkened room and viewed the display from a distance of 57cm . Stimuli were presented for 60 seconds per trial , with condition order determined at random . Participants were instructed to indicate using a two-button mouse which of the two grating stimuli they perceived at each moment in time by holding down one or other button . If both stimuli were perceived , they were instructed to choose the stimulus that was most visible ( i . e . that took up the largest part of the image ) , or to hold down both buttons if they were equally salient ( these mixed percepts accounted for an average of 3 . 2% of all percepts , so we did not analyse them further ) . At the end of each trial , there was a minimum blank interval of three seconds , with the following trial initiated by the participant . Each of the 26 conditions ( 5 contrasts * 5 temporal frequencies + 1 baseline ) was repeated 5 times by each observer using unique noise sequences in each repetition , and then a further 5 times using the same noise sequences as in the first pass . This resulted in 260 trials ( 4 . 3 hours of rivalry data ) per participant , which were completed across multiple sessions ( each typically lasting 20–30 minutes ) over several days . Raw data are available online at: http://dx . doi . org/10 . 6084/m9 . figshare . 7262201 There are multiple models that have been successful at capturing the oscillatory behaviour of dominant percepts in binocular rivalry [1–4 , 49] . While they vary in complexity , all include two key characteristics: inhibition between units responding to the left and right monocular stimuli , and self-adaptation . These guarantee that only one unit will be active at a given moment , and that over time , the active unit will decrease its firing rate sufficiently to allow the suppressed unit to be released from inhibition . Apart from a few exceptions [1 , 2 , 13 , 15 , 16 , 29 , 30 , 49] , most computational investigations of binocular rivalry have focused on deterministic implementations of their models to investigate how suppression and self-adaptation contribute to oscillations in perceptual dominance . It is , however , fairly straightforward to adapt these models of rivalry to include an internal noise term and directly probe the properties ( i . e . , amplitude and spectral qualities ) of internal noise . Here , we investigate the properties of internal noise with the minimum rivalry model of Wilson [3 , 4] . The minimum rivalry model defines the response of a single unit by two differential equations ( Eq 1 and Eq 2 ) , which incorporate stimulus excitation ( L/R ) , self-excitation ( ε = 0 . 2 ) , competitive inhibition ( ω = 3 . 5 ) , self-adaptation ( H ) , and here , an additive internal noise term ( N ) . For the unit responding to stimuli presented to the left eye ( EL ) , the response term is: τdELdt=−EL+M[L−ωER+ϵEL+gHL+NL]+1+[L−ωER+ϵEL+gHL+NL]+0 . 8 ( 1 ) and self-adaptation is: τdHLdt=−HL+EL ( 2 ) which is identical for activity in the right eye ( ER ) , but with the subscripts switched . The model output is then half wave rectified , such that negative values are set to 0 . The constants M and g serve to scale the response gain and adaptation strength and were set to values of 1 . 0 and 3 . 0 , respectively , based on values from Wilson ( 2007 ) . The excitatory ( τ ) and hyperpolarizing ( τh ) time constants of Eq 1 and Eq 2 were set to 15ms and 4000ms respectively , with the former value taken from Wilson ( 2007 ) , and the latter value being set to reproduce the average dominance duration of our observers . All model parameters were fixed in our simulations . Internal noise was additive and independently generated for each eye . Because the internal noise ( NL ) and external drive ( EL ) sum linearly on the numerator of Eq 1 , the units of internal noise are % Michelson contrast . As previous studies have already investigated the locus of internal noise with this particular model [1] , we chose here to only conduct model simulations with noise added to the unit response equation ( Eq 1 ) . Note that as the stimulus input to the model is identical to that of the psychophysical experiment ( see Fig 2A ) , we use a contrast gain control variant of the Minimum rivalry model [4] to account for any differences in contrast between eyes . This also means that the noise term is added to both the numerator and denominator of Eq 1 . We probed the spectral characteristics of internal noise by injecting the model with broadband noise patterns ( 1/fɑ ) generated at one of five different spectral slopes1 , where ɑ = [0 , 0 . 5 , 1 . 0 , 1 . 5 , 2 . 0] ( see Fig 2B ) . Noise patterns were generated in the Fourier domain by first creating a flat ( ɑ = 0 ) amplitude spectrum and then multiplying the amplitude coefficient at each frequency by f-ɑ . The phase of each frequency component was assigned a random value between -π and π . Two different phase spectra were generated in order to create two independent noise streams ( NL and NR ) with the same amplitude spectrum . These were rendered in the temporal domain by taking the inverse Fourier transform and adding them to the left and right units separately . Although the noise stream added to some versions of the model was white ( i . e . , had a flat amplitude spectrum ) , the output of the model is not a white noise process because it was integrated in the same manner as all other noise sources . This means that the variance of model responses increases with time when the internal noise has a white spectrum . This does not occur for steeper noise spectra ( α > 0 ) . To estimate the amplitude of internal noise , we selected a single stimulus condition ( 1/8Hz , SD = 16% external noise contrast ) and ran the model with a range of internal noise levels . Internal noise was set to 1% , 2% , 4% , 8% , 16% , 32% and 64% ( %SD ) . The results of this analysis demonstrated that internal noise set to 16% was best at matching the human data and was the value used to simulate the full range of stimulus conditions . We also conducted simulations with bandpass filtered internal noise streams with the same frequencies as that of the stimulus sequences , in addition to the broadband internal noise simulations . Response consistency was high for all stimulus conditions , which suggests that this type of internal noise is incapable of modulating model responses beyond that of the external noise sequences . As these results do not offer any additional insight to the characteristics of internal noise , we do not show them here . Perceptual switches were implemented as a winner-take-all rule: the dominance of a percept was defined by the magnitude of EL/R at any given moment in time ( if EL > ER , EL is dominant; see Fig 2C ) Finally , all model simulations were conducted in MATLAB ( version R2017a ) using ODE45 to solve the 4 differential equations that define the response of each unit and their self-adaptation over 60 seconds ( i . e . the duration of a trial in the psychophysical experiment ) . We simulated binocular rivalry twice–with different internal noise samples but the same external noise sequences–for each stimulus noise condition in order to calculate the response consistency of the model . This was repeated 1000 times , and the model outputs ( dominance duration and response consistency ) were averaged across repetitions .
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Although our perception of the world appears constant , sensory representations are variable because of the ‘noisy’ nature of biological neurons . Here we used a binocular rivalry paradigm , in which conflicting images are shown to the two eyes , to probe the properties of this internal variability . Using a novel paradigm in which the contrasts of rivalling stimuli are modulated by two independent external noise streams , we infer the amplitude and character of this internal noise . The temporal amplitude spectrum of the noise has a 1/f spectrum , similar to that of natural visual input , and consistent with the idea that the visual system evolved to match its environment .
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2019
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Dynamic properties of internal noise probed by modulating binocular rivalry
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Streptococcus equi subsp . zooepidemicus ( SEZ ) is a zoonotic pathogen capable of causing meningitis in humans . The mechanisms that enable pathogens to traverse the blood-brain barrier ( BBB ) are incompletely understood . Here , we investigated the role of a newly identified Fic domain-containing protein , BifA , in SEZ virulence . BifA was required for SEZ to cross the BBB and to cause meningitis in mice . BifA also enhanced SEZ translocation across human Brain Microvascular Endothelial Cell ( hBMEC ) monolayers . Purified BifA or its Fic domain-containing C-terminus alone were able to enter into hBMECs , leading to disruption of monolayer barrier integrity . A SILAC-based proteomic screen revealed that BifA binds moesin . BifA’s Fic domain was required for its binding to this regulator of host cell cytoskeletal processes . BifA treatment of hBMECs led to moesin phosphorylation and downstream RhoA activation . Inhibition of moesin activation or moesin depletion in hBMEC monolayers abrogated BifA-mediated increases in barrier permeability and SEZ’s capacity to translocate across monolayers . Thus , BifA activation of moesin appears to constitute a key mechanism by which SEZ disrupts endothelial monolayer integrity to penetrate the BBB .
Streptococcus equi subsp . zooepidemicus ( SEZ ) is a Lancefield Group C opportunistic pathogen capable of infecting a broad range of animal species , including humans [1] . The most significant burden of disease caused by SEZ is in farmed animals , including horses , cows and pigs [2] . However , human SEZ infections have been reported globally and are often linked to consumption of unpasteurized milk or contact with infected animals . Meningitis is the most common clinical manifestation of human infection with SEZ and can be fatal [3 , 4] . SEZ , like most streptococci , is an extracellular pathogen [2] and to cause meningitis , these organisms must penetrate the blood-brain barrier ( BBB ) , a functional barrier established in part by the endothelial cells lining the brain microvasculature . This highly selective barrier between the brain and the circulatory system acts as an important protective mechanism , excluding blood-borne pathogens and toxins from the central nervous system [5] . While relatively high pathogen concentrations in blood are thought to be a prerequisite for organisms to traverse the BBB , different pathogens appear to rely on varied mechanisms to penetrate this barrier [5] . Diverse factors facilitating pathogen adhesion to brain capillary endothelial cells have been identified and both transcellular and paracellular routes for pathogens to cross the BBB have been reported [6 , 7] . Although SEZ virulence factors that facilitate pathogen adhesion to host tissue and immune evasion have been identified [8–10] , there is little knowledge of the factors and mechanisms that enable SEZ to penetrate the BBB . In previous research , we sequenced and compared the genome sequence of a virulent SEZ strain ( ATCC35246 , isolated from a dead pig ) to those of non-virulent SEZ strains , to identify potential virulence-linked genes [11] . Several loci in the ATCC35246 isolate appeared to have been acquired through horizontal gene transfer . One such region ( pathogenicity island II ) contained a gene ( SeseC_01334 ) that is predicted to encode a protein carrying an N-terminal RhuM domain and a C-terminal Fic domain . These two domains are linked to virulence in other pathogens . Fic ( filamentation induced by cyclic AMP ) domain-containing proteins are present in many animal and plant pathogens [12] . Often these proteins are delivered via type III or type IV secretion systems ( T3SS , T4SS ) directly into the cytosol of host cells , where they manipulate host signaling pathways via covalent modification of target proteins . Though Fic proteins induce varied modifications in their targets ( e . g . , AMPylation , UMPylation , phosphorylation and phosphocholination have been described ) , they all share a consensus 9 amino acid core , HxFx ( D/E ) ( A/G ) N ( K/G ) R , with the histidine residue exhibiting the greatest conservation [12] . Since Fic domain proteins are linked to pathogenicity , we investigated whether SeseC_01334 ( here re-named BifA , for brain invasion factor ) contributes to SEZ virulence . We show that BifA is critical for SEZ to disrupt the BBB and to infect the mouse brain . Furthermore , this Fic-domain protein is required for SEZ to penetrate a tissue culture model of the BBB . BifA’s Fic domain enables the protein to enter into and to disrupt the barrier function of brain endothelial monolayers . BifA targets moesin and leads to its phosphorylation . Inhibition of moesin phosphorylation or knockdown of moesin expression prevented BifA-mediated increases in monolayer permeability and SEZ’s capacity to penetrate a monolayer barrier . Collectively , our findings reveal that SEZ meningitis depends on BifA , a Fic-domain protein that disrupts BBB function by manipulating moesin-dependent signaling .
We previously found that SEZ ATCC35246 contains 2 purC homologues , SeseC_00028 and SeseC_01334 . The later locus was presumably acquired by horizontal transfer because its G+C content ( 34 . 86% ) differs from the chromosomal G+C content ( 41 . 65% ) . Notably , although SeseC_01334 bears some similarity to SeseC_00028 , it also features an additional C-terminal Fic domain ( S1 Fig ) , which in several other bacteria has been linked to pathogenicity [12] , and an N-terminal RhuM domain that SeseC_00028 lacks . To investigate if SeseC_01334 ( here renamed bifA , for brain invasion factor A ) is required for SEZ ATCC35246 virulence , we generated a bifA deletion mutant strain ( ΔBif ) as well as a complemented strain ( CBif ) , in which BifA was expressed from a plasmid in the ΔBif background . Using an established murine model of SEZ infection [13] , mice were inoculated via intraperitoneal ( i . p . ) injection with WT or ΔBif strains . There was ~100× more WT colony forming units ( CFU ) than ΔBif CFU recovered from the brains of infected mice ( Fig 1A ) . In contrast , there were less marked differences in numbers of WT and ΔBif CFU recovered from the lung and kidney and in the liver and spleen , the number of ΔBif CFU recovered tended to exceed those of the WT ( Fig 1A ) . Thus , BifA may be particularly important for SEZ colonization of the brain . Furthermore , all WT-challenged mice died by 2 days post-infection ( dpi ) , whereas mice challenged with ΔBif survived until 5 dpi ( Fig 1B ) . Complementation of BifA in the ΔBif mutant restored its lethality to WT levels ( CBif , Fig 1B ) as well its capacity to colonize the brain ( Fig 1C ) . Despite the differences in the virulence of the WT and ΔBif strains , they had very similar in vitro growth curves ( S2A Fig ) , suggesting that an intrinsic growth defect is not the explanation for the in vivo attenuation of the mutant . Together , these observations show that BifA promotes SEZ’s lethality and its capacity to enter into and/or proliferate in the brain . For SEZ to colonize the brain it must traverse the BBB . We used an Evans Blue ( EB ) dye permeability assay [13] to assess the integrity of the BBB in mice inoculated with SEZ . EB was administered to mice 18 hours post infection ( hpi ) with WT , ΔBif or CBif and then the brains were dissected 2 hours later ( Fig 1D ) . The brains of mice infected with WT SEZ had significantly greater amounts of detectable EB than the brains of mice infected with ΔBif ( Fig 1D ) ; bifA complementation partially restored the capacity of ΔBif to disrupt the BBB ( Fig 1D ) . Thus , the marked defect of the ΔBif strain to colonize the brain may , at least in part , be explained by the reduced capacity of this strain to penetrate the BBB . Consistent with this hypothesis , we found that there was a much lower ratio of CFU recovered from the CSF vs the blood 12 hour after infection with ΔBif vs the WT strain ( Fig 1E ) , even though there were very similar numbers of WT and ΔBif organisms recovered from blood at this point ( S2B Fig ) . The absence of bifA appears to account for the reduced capacity of ΔBif to access the CSF , since this defect was not observed in the complemented strain ( Fig 1E ) . Furthermore , the WT and ΔBif strains had indistinguishable capacities to proliferate in blood ( S2B Fig ) . One consequence of BifA’s apparent capacity to promote SEZ disruption of the BBB may be the severe cerebral hemorrhage that was observed in the brains of animals infected with WT and CBif , but not in those infected with ΔBif ( S3 Fig ) . Moreover , using a transwell assay , we found that WT and CBif had a greater capacity to traverse human brain microvascular endothelial cell ( hBMEC ) monolayers than ΔBif ( Fig 1F ) . Together , these observations suggest that BifA promotes SEZ virulence and brain pathology by enabling the pathogen to transit the BBB . Prediction of protein structure using the THHMM server suggested that BifA lacks transmembrane helical domains and is likely a hydrophilic protein . We found that BifA could be detected in SEZ culture supernatants ( Fig 2A ) , raising the possibility that it might directly interact with host cells to modulate BBB integrity . Consistent with this idea , we found that BifA could be detected as cytoplasmic foci inside cultured hBMEC cells after exposure to supernatant derived from WT but not ΔBif SEZ ( Fig 2B ) . The full-length and N- and C-terminal portions of BifA ( ΔFic and ΔRhuM , respectively ) were purified along with a BifA mutant containing an H247A substitution in the Fic domain ( Fig 2C ) . This mutation was shown to ablate the catalytic activity of other Fic domain containing proteins [14] . Purified full length BifA was taken up into cultured hBMEC cells where it was detected as cytoplasmic foci by immunofluorescence microscopy ( Fig 2D ) . Notably , the concentration of BifA found in the culture supernatants ( ~18ug/ml , S4 Fig ) used above , were similar to the final concentration of purified BifA used to detect BifA entry into hBMEC cells in Fig 2D and to modulate monolayer permeability in experiments described below . Neither ΔFic nor BifA H247A were detected inside the hBMEC cells , whereas the intracellular amount and distribution of the ΔRhuM BifA variant was similar to full length BifA . Thus , the activity of BifA’s Fic domain appears required for the protein to enter host cells , but its RhuM domain is dispensable for this function . We also tested whether BifA was sufficient to enable latex beads coated with the protein to enter hBMEC cells . Transmission electron microscopy revealed that beads coated with full length BifA or the ΔRhuM truncated variant enabled latex bead internalization ( Fig 2E ) . Beads coated with ΔFic or H247A BifA were not internalized into cells any more than uncoated beads . Together , these observations indicate that BifA can mediate its own entry into hBMEC cells , and that entry appears dependent on a functional Fic domain . To test whether a functional Fic domain was important for SEZ virulence in vivo , we inoculated mice with the ΔBif strain complemented with BifA lacking the Fic domain ( CBif ( ΔFic ) ) or the H247A allele ( CBif ( H247A ) ) . These strains were similarly attenuated as ΔBif in lethality ( Fig 1B ) and brain colonization ( Fig 1C ) . These observations strongly suggest that BifA’s Fic domain is required for robust SEZ virulence . Since BifA appears to promote SEZ’s capacity to transit the BBB , we tested whether BifA treatment altered the barrier integrity of hBMEC monolayers . Using penetration of EB as a gauge of barrier disruption [15] , addition of either full-length BifA or the ΔRhuM truncation variant to hBMEC monolayers resulted in time-dependent increases in barrier permeability , which became apparent as early as 15 minutes after addition of BifA or ΔRhuM ( Fig 3A ) . In contrast , addition of the H247A BifA mutant or the ΔFic truncation variant to the transwells did not alter the monolayers’ barrier function . Live microscopy of monolayers was carried out to monitor the effects of BifA and BifA H247A treatment on monolayer integrity ( Fig 3B and S1–S6 Movies ) . In some parts of the BifA-treated monolayers , the hBMEC membranes between adjacent cells appeared to retract by ~15–30 min after addition of the protein and frank gaps in the monolayer , which widened through time , became evident by ~120 min after treatment ( Fig 3B from S1 Movie and Fig 3C from S2 Movie ) . In contrast , addition of H247A BifA to monolayers did not result in detectable morphologic changes in the hBMEC cells compared to the untreated monolayer ( mock ) over a 3 hours period of observation ( Fig 3B , S3–S6 Movies ) . Additional studies to elucidate the molecular mechanism ( s ) by which BifA disrupts the integrity of hBMEC monolayers are required . However , interruption of tight junctions could contribute to the permeabilization of the monolayers , since we found that cellular levels of the tight junction protein , zona occludens-1 ( ZO-1 ) , decreased after addition of BifA ( Fig 3D , S5 Fig ) . We used a SILAC-based comparative ‘pull-down’ approach to identify BifA binding partners . For these studies , BifA-GFP was expressed in HEK293T cells and the proteins that precipitated along with BifA were identified by mass spectrometry ( Fig 4A ) . One of the top hits among the 19 candidate BifA-interacting protein identified ( S1 Table ) was an ERM family protein , which was enriched ~1 . 8-fold in the BifA-GFP vs the GFP pull-down . ERM family proteins include Ezrin , Radixin , and Moesin , which function in endothelial cells as well in other cell types as critical regulators of the actin cytoskeleton [16] . These proteins are capable of binding to integral membrane proteins through their N-terminal FERM domains and filamentous actin through their C-terminal Ezrin Radixin Moesin association domain ( ERMAD ) . By virtue of these dual binding capacities , ERM proteins regulate actin polymerization at the cell cortex , where they provide a critical link between the cell membrane and cytoskeletal components [17] . Since the dominant ERM family protein in hBMEC is moesin [16] , we focused subsequent studies on BifA’s potential interaction with moesin . To confirm that BifA interacts with moesin in hBMEC cells , co-immunoprecipitation ( co-IP ) experiments were performed with lysates from hBMEC expressing HA-tagged moesin and several BifA variants . The epitope-tagged moesin co-IPed with full-length BifA and the ΔRhuM truncation variant , but not with the H247A BifA or ΔFic variants ( Fig 4B ) . Thus , BifA’s interaction with moesin in hBMEC cells appears to depend on its Fic domain . Similar co-IP experiments were carried out using cells transfected with tagged variants of moesin ( Fig 4C ) , to determine which of the moesin domains is required for BifA interaction . BifA co-IPed with a moesin variant lacking the FERM domain but not with a variant lacking the ERMAD domain ( Fig 4D ) , suggesting that the FERM domain is dispensable for the BifA-moesin interaction . In addition , we found that purified BifA could interact with moesin in hBMEC lysates , while BifA H247A could not ( S6 Fig ) . Moesin’s ERMAD domain includes a highly conserved threonine residue ( T558 ) that is phosphorylated during activation [17] . Substitution mutants in the moesin T558 residue that are predicted to be phosphoablative ( T558A ) or phosphomimetic ( T558D ) were generated to begin to address whether T558 phosphorylation modulates BifA-moesin interaction . Interestingly , BifA precipated less moesin T558A than WT moesin or moesin T558D , which precipitated with BifA at least as well as WT moesin ( Fig 4D ) , suggesting that BifA’s interaction with moesin is enhanced by phosphorylation of moesin T558 . Surface plasmon resonance analyses with purified BifA and moesin proteins were performed to further characterize BifA’s interaction with moesin . These studies demonstrated that BifA could bind moesin in isolation from other proteins , and thereby indicate the interaction is direct ( Fig 4E ) . Consistent with previous results , minimal binding of the H247A or ΔFic BifA variants to moesin was detected with this assay ( S7A Fig ) . Additionally , the binding affinity of BifA for the moesin T558A mutant was less ( T558A , KD = 7 . 366×10−7 M ) than that of T558D ( KD = 1 . 078×10−8 M ) , which had an even higher affinity than the wild-type protein ( Fig 4E and S7B Fig ) . Collectively , these observations demonstrate a direct interaction between BifA and moesin that is dependent on their respective Fic and ERMAD domains and that is likely enhanced by activation ( T558 phosphorylation ) of moesin . Since several Fic domain-containing bacterial toxins are reported to lead to the phosphorylation of their respective target proteins [18] , we tested whether BifA promotes moesin phosphoryation . We monitored moesin T588 phosphorylation following addition of different BifA variants to hBMEC cells by immunoblotting with an antibody that recognizes phosphorylated moesin T588 ( p-Moesin ) . Addition of either full length BifA or the BifA ΔRhuM variant to cells led to moesin T588 phosphorylation in a time-dependent fashion but did not alter total cellular moesin levels ( Fig 5A and 5C ) . In contrast , no changes in moesin phosphorylation or levels were detected when the H247A BifA or ΔFic variants were added to cells ( Fig 5B and 5D ) . Similar results were obtained from immunoblots of lysates electrophoresed with Phos Binding Reagent Acrylamide , which alters the electrophoretic mobility of phosphorylated proteins ( S8 Fig ) . These observations indicate that treatment of hBMECs with internalizable and moesin-binding variants of BifA promotes moesin phosphorylation . ERM family proteins are phosphorylated by protein kinase C ( PKC ) [19] . We used NSC305787 , a small molecule inhibitor of PKC phosphorylation of ERM family proteins [20] , to investigate whether BifA-induced phosphorylation of moesin was dependent on PKC . When hBMEC cells were pre-treated with NSC305787 for 30 minutes before addition BifA , there was no induction of moesin phosphorylation ( Fig 5E ) , consistent with the idea that BifA induction of moesin phosphorylation depends on PKC . Moesin phosphorylation leads to activation of small G proteins , such as RhoA and Rac1 [21] , that regulate actin cytoskeletal and membrane protrusion dynamics [22] , phenotypes that could be pertinent to BifA-induced changes in brain endothelial cells and BBB permeability . RhoA and Rac1 activation are controlled by their conversion from GDP- to GTP-bound states [23] , and we used immunoblots to monitor GTP-RhoA and GTP-Rac1 levels in BifA-treated cells . There was a time-dependent increase in GTP-RhoA that was associated with moesin phosphorylation in BifA-treated cells ( Fig 5F ) . GTP-Rac1 levels were also increased during BifA treatment ( S9 Fig ) . When BifA-induced moesin phosphorylation was blocked with NSC305787 , GTP-RhoA formation was abrogated ( Fig 5F ) , consistent with the idea that RhoA activation by BifA is dependent on moesin phosphorylation . We next tested whether moesin phosphorylation was required for BifA-mediated barrier disruption . Monolayers pre-treated with NSC305787 did not exhibit increased permeability after addition of BifA ( Fig 6A ) . Similarly , NSC305787 pre-treatment led to marked reduction in SEZ translocation across hBMEC monolayers ( Fig 6B ) . Furthermore , we used siRNA to knockdown ( KD ) moesin in hBMECs ( S10 Fig ) to further investigate the requirement of moesin for BifA action . By itself , moesin KD did not alter the barrier function of the hBMEC monolayer , as these cells remained impermeant to Evans Blue dye ( Fig 6A ) . However , the moesin KD cells exhibited significantly less permeabilization after BifA treatment , in marked contrast to control hBMEC monolayers treated with BifA ( Fig 6A ) . Moreover , there was a marked reduction in the ability of SEZ to translocate across the moesin KD monolayer vs the WT monolayer , phenocopying the effects of NSC305787 ( Fig 6B ) . Since NSC305787 inhibits all ERM family protein phosphorylation , the similarity of the phenotypes observed in the NSC305787 treated and moesin KD cells supports that idea that moesin is the dominant ERM protein in hBMECs . Thus , both blockade of moesin phosphorylation and moesin depletion are sufficient to protect cells from BifA-dependent bacterial translocation across the hBMEC monolayer . Collectively , these observations suggest that BifA disruption of hBMEC monolayer barrier integrity relies on moesin-dependent signaling pathways .
We found that the virulence of SEZ ATCC35246 depends on BifA , a Fic domain-containing protein encoded in a pathogenicity island . Deletion of bifA reduced its lethality in mice as well its capacity to disrupt the BBB , to colonize the brain and to traverse hBMEC monolayers in tissue culture . BifA bound to moesin , a host protein that regulates cytoskeletal processes . Inactivation of BifA’s Fic domain eliminated its capacity to enter hBMEC monolayers , increase monolayer permeability , and to bind to moesin . BifA activation of moesin appears to be critical for BifA’s modification of monolayer permeability , since either moesin knock down or pharmacologic inhibition of moesin activation abolished BifA-mediated increases in hBMEC permeability and SEZ penetration of a hBMEC monolayer . Collectively , our findings suggest that by usurping moesin-dependent signaling , BifA enables SEZ to efficiently penetrate the BBB . Our observation that addition of BifA to hBMEC monolayers induced formation of gaps and increased monolayer permeability is consistent with the idea that BifA enables SEZ penetration of the BBB by disrupting the integrity of the brain endothelial monolayer , a critical constituent of the BBB . Concordant with this model , BifA’s action appears dependent on the associated phosphorylation of the ERM protein moesin , which is known to have diverse consequences that include activation of signaling pathways involved in cell adhesion , migration and invasion [21 , 24–26] . In particular , we found that moesin phosphorylation following BifA treatment was linked to formation of RhoA-GTP , the active form of this small G protein known to regulate multiple cytoskeletal processes [27 , 28] . Formation of RhoA-GTP is likely a consequence of moesin phosphorylation , since blockade of moesin phosphorylation with NSC305787 inhibited the generation of RhoA-GTP ( Fig 5F ) . Notably , activation of RhoA has been shown to promote the dissolution of tight junctions , which serve to limit paracellular permeability between endothelial cells [29] . Loosening of tight junctions and additional factors ( e . g . adherens junctions ) that increase the adherence of adjacent cells in the brain endothelium could open a paracellular route for SEZ movement across the BBB ( S11 Fig ) . Additional pathogens manipulate RhoA signaling to reduce the integrity of the BBB . For example , E . coli K1’s CNF toxin’s modulation of RhoA activity is thought to be important for this common agent of neonatal meningitis to cross the BBB [5]; however , in this case , RhoA activation is thought to enable this pathogen to traverse the BBB via a transcellular route . RhoA activation by the brain-invasive fungal pathogen Cryptococcus neoformans also facilitates its traversal of the BBB [30] . Additional Fic domain-containing proteins are known to catalyze post-translational modification of Rho family proteins ( e . g . AMPylation of Rho proteins by Vibrio parahaemolyticus VopS [12] ) , but to our knowledge , other Fic toxins have not been reported to modify BBB function . Both the mechanisms of BifA release from SEZ and uptake into eukaryotic cells require elucidation . In contrast to several Fic domain-containing virulence factors described in other pathogens ( e . g . VopS ) , BifA delivery into the eukaryotic cytosol does not rely on a bacterial type III or type IV secretion system . In this regard , BifA functions as a traditional bacterial toxin , mediating its own uptake into host cells . Similar to BifA , IbpA , a Fic-domain containing protein from the cattle pathogen Histophilus somni doesn’t require additional bacterial factors for uptake into bovine cells , where it AMPylates Rho family proteins [12] . It will be particularly interesting to determine whether the receptor ( s ) and pathways that mediate BifA uptake into host cells modulate its downstream function ( s ) . The characterized Fic domain-containing proteins produced by other pathogens catalyze post-translational modifications of target proteins upon entry into the eukaryotic cell cytosol [12] . Fic domain-containing proteins can directly phosphorylate their targets; e . g . , Doc phosphorylates its target EF-Tu [31] . However , although we found that BifA directly binds to moesin ( Fig 4 ) and that BifA treatment of endothelial cells resulted in elevated levels of phosphorylated moesin ( Fig 5 ) , we did not directly demonstrate that BifA phosphorylates moesin . The observation that the PKC kinase inhibitor NSC305787 blocked the induction of moesin phosphorylation in cells treated with purified BifA suggests that BifA may not directly phosphorylate moesin , but could instead promote its phosphorylation indirectly . For example , BifA could enhance the activity of a host kinase , akin to the action of the Pseudomonas syringae Fic-like T3SS effector AvrB , which leads to the phosphorylation of the plant immune regulator RIN4 by promoting the activity of the endogenous kinase MPK4 [32] . Alternatively , our observation that BifA binds to the phosphorylated form of moesin with greater affinity than to the non-phosphorylated form ( Fig 5 ) , raises the possibility that BifA stabilizes phospho-moesin , leading to its accumulation . Interestingly , despite a high degree of overall conservation among sequenced SEZ isolates , bifA homologues are not found in other SEZ genomes . BifA is encoded in a SEZ ATCC35246 pathogenicity island , suggesting that this critical SEZ Fic-domain containing virulence factor was likely acquired via horizontal gene transfer , and thus that lateral gene exchange was a key step in the evolution of SEZ ATCC35246 as a pathogen . Acquisition of bifA alone may be sufficient to enhance BBB penetration by related organisms . BifA homologues are not present in other well-characterized meningeal pathogens , e . g . Group B streptococci , consistent with the idea that different CNS pathogens rely on distinct factors to traverse the BBB [5] . However , BifA homologues with intact Fic domains are present in a variety of other Gram-positive as well as Gram-negative organisms , many of which are usually thought of GI tract commensals , suggesting that BifA-like proteins may carry out functions beyond diminishing the integrity of the BBB . Finally , BifA’s capacity to increase BBB permeability may have medical applications in delivery of drugs and other agents to the brain .
Streptococcus equi subsp . zooepidemicus ATCC35246 ( SEZ ) was isolated from a dead pig in Sichuan Province , China . SAICAR gene SeseC_01334 ( Genbank ) was re-named bifA . A bifA deletion mutant and complemented strain were constructed using pSET4s , a Streptococcus-E . coli temperature sensitive suicide shuttle vector and expression plasmid pSET2 respectively ( SI Appendix ) [33] . SEZ was cultured in Todd Hewitt Broth ( THB ) ( Becton , Franklin Lakes , NJ , USA ) at 37°C . Human brain microvascular endothelial cells ( hBMECs ) were purchased from ScienCell Research Laboratories ( Catalog #1000 ) . HEK293T cells were purchased from American Type Culture Collection ( ATCC number CRL-3216 ) . Cells were cultured in DMEM ( Gibco , Grand Island , NY , USA ) with 10% fetal bovine serum ( FBS ) ( Gibco , Grand Island , NY , USA ) in a 37°C incubator containing 5% CO2 . The vectors pAcGFP-C and pCMV-C-HA were used for the respective expression of BifA and moesin in eukaryotic cells respectively . E . coli BL21 ( DE3 ) plysS was used to express recombinant BifA and its variants with the pCold-SUMO vector; E . coli Rosetta ( DE3 ) was used to express moesin and its variant proteins with pGEX-6p-1 . The bifA gene was PCR amplified from SEZ genomic DNA and subcloned into the pAcGFP-C vector . The moesin cDNA was PCR amplified from human cDNA and subcloned into the pCMV-C-HA vector . For expression of His- or GST-tagged proteins , bifA was subcloned into pCold-SUMO vectors and moesin was subcloned into pGEX-6p-1 . The mutations in bifA and moesin were constructed by PCR mutagenesis using the ClonExpress II One Step Cloning Kit ( Vazyme Biotech Co . , China ) . The plasmid constructs were verified by Sanger sequencing . E . coli DH5α was used for propagation of plasmids . All plasmid information and primers are listed in S2 Table . An allele exchange vector for deletion of bifA was created by PCR amplification of fragments upstream and downstream of the bifA gene with primers of bifA-up-fwd/bifA-up-rev and bifA-dwn-fwd/bifA-dwn-rev , using SEZ ATCC35246 genome as template . The upstream and downstream PCR products were mixed 1:1 , and primer pair bifA-up-fwd/bifA-dwn-rev were subjected to fusion PCR amplification . The fusion fragment was purified , digested with appropriate endonucleases , and then cloned into the same sites of the temperature-sensitive S . suis-E . coli shuttle vector pSET4s [33] . Plasmids were electroporated into SEZ ( Bio-Rad , Gene Pulser Xcell , Voltage: 2300V , Capacitance: 25μF , Resistance: 200Ω , Cuvette: 1mm ) and mutant isolation was carried out as described [34] . The bifA gene was amplified using the primer pair bifA-pSET2-fwd and bifA-pSET2-rev using SEZ genomic DNA as the template , and then inserted into the pSET-2 plasmid . This plasmid was used to complement the bifA deletion in the ΔBif strain . Templates containing mutant versions of bifA were amplified from the expression vectors used above and subcloned into pSET-2 . The inserts in all plasmids were confirmed by Sanger sequencing . All animal experiments were performed with protocols approved by the College of Veterinary Medicine of Nanjing Agricultural University for Research Protection Standing Committee on Animals in accordance with Science and Technology Agency of Jiangsu Province guidelines ( SYXK2017-007 ) . All efforts were made to minimize animal suffering . Four-week-old female BALB/c mice , purchased from the Comparative Medicine Center of Yangzhou University , were used for all animal work . In bacterial load determination of different organs in Fig 1A , mice ( 10/group ) were i . p . challenged with 1×105 CFU of WT or mutant SEZ . In the mortality experiments shown in Fig 1B , mice ( 20/group ) were i . p . challenged with 5×105 CFU of WT or mutant SEZ . For bacterial load determinations in Fig 1C , mice ( 10/group ) were i . p . challenged with 5×105 CFU of WT or mutant SEZ and CFU counts from the brain were determined 2 days later . For pathology ( S3 Fig ) , brains were harvested and embedded in paraffin and sectioned for hematoxylin and eosin staining , 48 hours after intravenous injection of 1×106 CFU of WT and mutant SEZ . Evans Blue ( EB ) leakage was used to assess BBB permeability as described [13] . In these experiments , mice were challenged i . v . with 5×106 CFU of WT or mutant SEZ , and 18 hour later , 100μl of 2% EB was administered i . v . Two hours later , brains were dissected , photographed and then dried at 56°C in aluminum foil for two days . Formamide was used to extract the EB out of the tissue and EB amounts were determined as absorbance at OD620 . To purify His-tagged BifA and its variants , cultures of BL21 ( pCold-SUMO-bifA ) was grown to OD600 = 1 . 0 in Luria-Bertani ( LB ) broth at 37°C , 180 rpm then induced with IPTG at a final concentration of 1 mM at 16°C , 180 rpm for 24 hours . Bacterial cells were collected by centrifugation . Cells were lysed in the lysis buffer ( 10mM Tris-HCl , pH 8 , containing 100 mM NaCl and 20mM imidazole ) by sonication . The cell lysate was centrifuged and the supernatant was used for purification . SUMO tag was digested with SUMO protease ( Thermo , Waltham , MA , USA ) . Primary purification was performed using the Histrap HP column ( GE Healthcare , Piscataway , NJ , USA ) , followed by Superdex 200 10/300 GL gel filtration ( GE Healthcare , Piscataway , NJ , USA ) using an AKTA Protein Purifier ( GE Healthcare , Piscataway , NJ , USA ) . To purify non-tagged moesin for SPR , cultures of BL21 ( pGEX-6p-1-msn ) were grown until OD600 = 0 . 8 in LB at 37°C , 180 rpm then with IPTG at a final concentration of 1 mM at 30°C , 180 rpm for 5 hours . Cells were lysed in the lysis buffer ( PBS , 140 mM NaCl , 2 . 7 mM KCl , 10 mM Na2HPO4 , 1 . 8 mM KH2PO4 , pH 7 . 3 ) by sonication . The lysates were used for purification with GSTrap HP 5 ml column ( GE Healthcare , Piscataway , NJ , USA ) followed by tag digestion with Precission Protease and GSTrap FF 1 ml column ( GE Healthcare , Piscataway , NJ , USA ) , Sephadex 10/300 ( GE Healthcare , Piscataway , NJ , USA ) was used to final purification in AKTA Protein Purifier ( GE Healthcare , Piscataway , NJ , USA ) . WT hBMEC or moesin knock-down hBMEC were seeded on the apical side of collagen-coated polytetrafluoroethylene ( PTFE ) 3 μM pore-size membranes ( Corning Incorporated , Corning , NY , USA ) for the bacterial penetration assay and 0 . 4 μM pore-size membranes ( Corning Incorporated , Corning , NY , USA ) for the barrier integrity assay . Cells were grown for 7 to 10 days to form intact monolayers . Barrier integrity was assessed with 0 . 4% Evans Blue solution [35] . Bacterial cells ( 1×106 CFU ) were added to the upper chamber of transwells containing hBMEC and incubated at 37°C in 5% CO2 for 2 hours . The 100 μl medium from both sides of the transwells was collected and spread on THB agar plates for CFU determination [36] . To examine the effect of BifA on barrier integrity , 10 μg/ml BifA was added to the upper chamber of transwells . Transwell inserts were then transferred to a fresh plate containing Hanks Balanced Salt Solution ( HBSS ) in the bottom chamber and 50 μl of 0 . 4% Evans Blue solution in PBS was added to the upper chamber . Transwell inserts were incubated at 37°C in 5% CO2 for 40 min , and the permeability was assessed by colorimetric quantification at OD600 nm of the bottom chamber as described [37] . SEZ was grown to an OD600 = 0 . 6 in THB media at 37°C with vigorous shaking ( 180 rpm ) . Bacteria were diluted 1:100 in DMEM media and grown for 12 h at 37°C with vigorous shaking ( 180 rpm ) and then culture supernatants were isolated by centrifugation . Proteins were precipitated from supernatants with TCA-acetone as described [38 , 39] . Approximately 106 sulfate-modified fluorescent red polystyrene latex beads ( 0 . 1 μm mean particle size , Sigma-Aldrich , St . Louis , MO , USA ) were suspended in 200 μL of 25 mM 2- ( N-morpholino ) ethanesulfonic acid ( MES ) buffer , pH 8 . 0 . Purified BifA or BifA variants were dissolved in 10 μL 25mM phosphate buffer ( pH 7 . 2 ) and incubated with the suspended beads at 4°C overnight with gentle mixing . We sequentially added 25mM MES buffer ( 150 μL ) every 15 min until the original volume was diluted 200-fold . The coated beads were collected by centrifugation at 3000 × g for 20 min , washed twice in MES buffer and resuspended in DMEM without FBS and then sonicated for dispersal . Dot blot assays were used to confirm protein coating of the beads [40] . For transmission electron microscopy , coated beads were incubated with hBMEC ( 100:1 ) for 4h at 37°C . Extracellular beads were removed by washing with PBS and then samples were fixed in 2 . 5% paraformaldehyde and 0 . 1% glutaraldehyde in 0 . 05 M cacodylate buffer , pH 7 . 3 . Then , 0 . 03% CaCl2 was added to the mixture . After fixation , the cells were washed with 0 . 1 M cacodylate buffer , and pelleted by centrifugation . Low melting point agar was pre-embedded and stained with 1% uranyl acetate in 0 . 1 M maleate buffer , then dehydrated in ethanol . Ultrathin sections were cut , stained with lead citrate and examined using a JEM 1400-PLUS electron microscope ( JEOL , Tokyo , Japan ) [41] . The hBMEC were seeded onto 15 mm Glass Bottom Cell Culture Dishes ( Corning , NY , USA ) and treated with 10 μg/ml BifA or BifA variants for 2 hours . Cells were then fixed with 4% paraformaldehyde followed by 0 . 1% Triton X-100 permeabilization buffer and blocked with 5% BSA in PBS-Tween . Mouse polyclonal anti-BifA antibody , Alexa 488-conjugated goat anti-mouse antibody ( Jackson Immunoresearch , West Grove , PA , USA ) , rabbit anti-Moesin antibody ( Abcam , Cambridge , MA , USA ) and Alexa 594-conjugated goat anti-rabbit antibody ( Jackson Immunoresearch , West Grove , PA , USA ) were used at 1:2000 in PBS containing 1% BSA . Primary antibodies were incubated for 2 hours and secondary antibody for 1 . 5 hours at room temperature . 4 , 6- Diamidino-2-phenylindole ( DAPI ) was used to detect cell nuclei . Plates were washed three times with Phosphate buffered saline with Tween-20 ( PBST ) with shaking to wash out unbound antibodies . Images were obtained on a laser scanning confocal microscope ( LSCM ) ( ZEISS , Japan ) . The hBMEC cells were cultured on 6-well Glass Bottom Plates ( ∅35mm , Cellvis , CA , USA ) for 7–9 days until monolayers were confluent . Cells were replenished with DMEM medium , and BifA or BifA variants , at a final concentration of 10 μg/ml , was added to the wells . The plates were cultured in a controlled environmental chamber at 37°C in 5% CO2 . Time-lapse images were acquired at an interval of 30 s for 300 min through an EC Plan-Neofluar 20×/0 . 50 M27 lens on an Axiom Observer . Z1/7 microscope , using the Applied Precision motorized stage ( Carl Zeiss , Japan ) . ZEN software was used for image processing . Stable isotope labelling of amino acids in cell culture ( SILAC ) was used to identify BifA interacting host proteins in HEK293T cells . Cells were labeled with heavy isotopes ( Arg13C6 , Lys13C6 ) or light isotopes ( Arg12C6 , Lys12C6 ) in Dulbecco’s modified Eagle medium ( DMEM ) with 10% FBS ( Pierce , Rockford , IL , USA ) at 37°C in 5% CO2 as previously described [42] . The cells were passaged for 6 generations to ensure adequate labeling of proteins . The heavy and light labeled cells were seeded in 10 cm cell culture dishes and transfected with 24 μg of pAcGFP-BifA or pAcGFP using Lipofectamine 2000 ( Thermo , Waltham , MA , USA ) respectively . Transfected cells were lysed in 500 μl cold Mammalian Protein Extraction Reagent ( Thermo , Waltham , MA , USA ) , containing a protease inhibitor cocktail ( Thermo , Waltham , MA , USA ) and centrifuged at 14000 g for 10 min at 4°C . Protein concentrations were measured using the BCA Protein Assay Kit ( Pierce , Rockford , IL , USA ) according to the manufacturer’s directions . We mixed equal quantities of heavy and light lysates and pre-cleared them on Protein G agarose ( Santa Cruz , Santa Cruz , CA , USA ) with 100 μg mouse IgG ( CMCTAG , Milwaukee , WI , USA ) for 1h at 4°C with gentle agitation . Pre-cleared lysates were centrifuged and the supernatants transferred to new tubes . Mouse anti-GFP antibody ( CMCTAG , Milwaukee , WI , USA ) was added to the cold lysates and incubated at 4°C for 1 h , then 40 μl protein G agarose was added and incubated at 4°C on a rotating device overnight . Beads were washed five times with 1 ml of cold PBS . After the final wash , the bound proteins were eluted with 50 μl of elution buffer ( 50mM Tris-HCl , 1% SDS ) and samples were boiled for 5 min . The eluted proteins were digested as previously described [35] . The peptides were separated by reverse-phase liquid chromatography using a nano-LC system ( DIONEX Thermo Scientific ) and analyzed by tandem mass spectrometry using an LTQ-Orbitrap mass spectrometer ( Thermo Scientific ) with a nanoelectrospray ion source . HEK293T cells were seeded in 10 cm cell culture dishes , which were each transfected with 24 μg of pAcGFP-BifA and pCMV-HA-Moesin , or pAcGFP and pCMV-HA plasmids . In addition , truncated fragments of moesin were obtained by PCR and cloned into pCMV-HA plasmids . The resulting plasmids , pCMV-HA-Moesin FERM domain ( 1-470aa ) and pCMV-HA-Moesin C-ERMAD domain ( 470-577aa ) were co-transfected with pAcGFP-BifA plasmid respectively . Lysates were harvested 48 h later with lysis buffer and cleared by centrifugation as described above . Twenty microliters of lysate was saved for analysis of the expression efficiency and the remainder was immunoprecipitated with Protein G agarose bound to either anti-HA or anti-GFP specific antibody ( CMCGAT , Milwaukee , WI , USA ) . Immunoprecipitated beads were resuspended and boiled for 5 min in 1× Laemmli sample buffer and then used for Western blot analysis . Boiled cell lysates were subjected to SDS-PAGE , followed by transfer to a PVDF membrane ( Roch , Basel , Switzerland ) using a semi-dry transfer apparatus ( GE Healthcare ) . Membranes were blocked in 5% non-fat milk powder in TBS containing 0 . 01% Tween 20 ( TBST ) . Primary antibodies were used and diluted as follows: 1:500 anti-BifA rabbit polyclonal antibody; 1:1000 anti-Moesin ( Abcam , Cambridge , MA , USA ) ; 1:1000 anti- phospho T558-Moesin ( Abcam , Cambridge , MA , USA ) ; 1:2000 anti-HA ( CMCGAT , Milwaukee , WI , USA ) ; 1:2000 anti-GFP ( CMCGAT , Milwaukee , WI , USA ) ; 1:2000 Anti-ZO-1 tight junction protein antibody ( Abcam , Cambridge , MA , USA ) and 1:2000 anti-GAPDH ( CMCGAT , Milwaukee , WI , USA ) . Membranes were incubated with primary antibody diluted in TBST containing 1% BSA overnight at 4°C and then washed for 30 min in TBST . This was followed by incubation with 1:5000 HRP goat anti-rabbit or goat anti-mouse IgG antibody ( ABGENT , San Diego , CA , USA ) . Membranes were washed for 3 × 15 min in TBST before adding ECL reagent ( Thermo , Waltham , MA , USA ) . Chemiluminescence was detected on a ChemiDoc system ( Bio-Rad , Hercules , CA , USA ) . The direct binding potential of BifA and moesin was analyzed using the Biacore X100 instrument ( GE Healthcare ) . Recombinant His-BifA protein and its variants were separately immobilized onto Biacore NTA sensorchips ( GE Healthcare ) . The recombinant moesin protein , moesin T558A or moesin T558D were injected individually and the binding interactions were recorded . Results were analyzed using the Biacore X100 Evaluation Software ( GE Healthcare ) . The hBMEC were seeded into 6-well plates ( Corning Incorporated , Corning , NY , USA ) . For serum starvation , once cells reached 70% confluency , the medium was replaced by low serum medium ( 1% FBS ) for 24h , and then replaced with DMEM without FBS and incubated for 16–20 h . After serum starvation , BifA or BifA variants at a concentration of 10 μg/ml in DMEM were added to cells . At different time points ( 0–120 min ) , cells were harvested for protein extraction . Cells were lysed with M-PER Mammalian Protein Extraction Reagent ( Thermo , Waltham , MA , USA ) on ice in the presence of Halt Protease and Phosphatase Inhibitor Cocktail , EDTA-free ( 100× ) . In some cases , cells were pretreated with 10 μM of a PKC inhibitor of ERM protein phosphorylation , NSC305787 [20] ( MedChemExpress , Monmouth Junction , NJ , USA ) for 30 min prior to addition of BifA . Phosphorylation levels of extracted proteins were detected by Western blot with anti-phospho T558-Moesin antibody ( Abcam , Cambridge , MA , USA ) . Phos Binding Reagent Acrylamide ( PBR-A ) ( APExBIO , TX , USA ) was also used to detect moesin phosphorylation . Briefly , extracted proteins were electrophoresed in a 6% acrylamide gel containing 50 mM PBR-A and 10 mM Mn2+ . After electrophoresis , the gel was soaked in a general transfer buffer containing 10 mmol/L EDTA for a minimum of 10 minutes with gentle agitation , followed by gentle agitation in buffer without EDTA for 10 minutes . The gel was then transferred to PVDF membranes for Western-blotting with a rabbit anti-Moesin antibody ( Abcam , Cambridge , MA , USA ) The amounts of GTP-RhoA or GTP-Rac1 in cell lysates were measured by a pull-down method based on specific binding to Rhotekin- RBD coated beads for 1h at 4°C under gentle rotation , followed by western blot with an antibody specific for the GTP-bound form of RhoA or Rac1 ( RhoA/Rac1/Cdc42 Activation Assay Combo Biochem Kit , Cytoskeleton , Inc . , USA ) . Total RhoA or Rac1 in cell lysates were detected by anti-RhoA and anti-Rac1 antibodies respectively . An shRNA targeting the moesin gene was ligated into the pLVX-shRNA1 vector ( Clontech , Mountain View , CA , USA ) . The lentivirus was packaged using commercial reagents ( Applied Biological Materials , Nanjing , JS , China ) . Lentiviral particles ( MOI = 1 ) were added to the hBMEC and seeded in 6-well plates , with media change after 24 h of incubation . After transduction , cellular protein was extracted for Western blot detection , while the RNA was extracted at different time points for Quantitative Real-Time PCR detection . Moesin transcripts levels were determined using the ABI Prism 7300 and Sequence Detection System software ( Applied Biosystems , Foster City , California , USA ) . The results were obtained using the mathematical model Ratio = 2-ΔΔct [43] . 72 h post transduction , puromycin was used for selecting positive colonies at final concentration 2 μg/ml . The sequences of the oligos used are found in S2 Table .
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Streptococcus equi subsp . zooepidemicus ( SEZ ) is an important animal pathogen and can cause meningitis in humans . Little is known about how this Group C streptococcal species penetrates the blood-brain barrier ( BBB ) . We identified bifA , a gene that is critical for SEZ to cause meningitis in mice and to penetrate a human brain endothelial monolayer in a tissue culture model . BifA’s Fic domain enables the protein to enter into endothelial monolayers and to bind to moesin , a cytoskeletal regulatory protein , leading to its activation . Preventing moesin activation abolished BifA-induced barrier leakiness and SEZ’s capacity to penetrate a monolayer barrier . Together , our findings suggest that SEZ meningitis depends on BifA , a Fic-domain protein that manipulates moesin-dependent signaling to modulate BBB permeability .
|
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2019
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A streptococcal Fic domain-containing protein disrupts blood-brain barrier integrity by activating moesin in endothelial cells
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DNA methylation is a key epigenetic regulator in all domains of life , yet the effects of most bacterial DNA methyltransferases on cellular processes are largely undefined . Here , we used diverse techniques , including bisulfite sequencing , transcriptomics , and transposon insertion site sequencing to extensively characterize a 5-methylcytosine ( 5mC ) methyltransferase , VchM , in the cholera pathogen , Vibrio cholerae . We have comprehensively defined VchM’s DNA targets , its genetic interactions and the gene networks that it regulates . Although VchM is a relatively new component of the V . cholerae genome , it is required for optimal V . cholerae growth in vitro and during infection . Unexpectedly , the usually essential σE cell envelope stress pathway is dispensable in ∆vchM V . cholerae , likely due to its lower activation in this mutant and the capacity for VchM methylation to limit expression of some cell envelope modifying genes . Our work illuminates how an acquired DNA methyltransferase can become integrated within complex cell circuits to control critical housekeeping processes .
DNA methylation—the covalent attachment of methyl moieties to specific nucleotides in the genome by DNA methyltransferases ( MTases ) —is a fundamental mechanism for epigenetic regulation in all domains of life ( reviewed in [1 , 2] ) . Bacterial DNA MTases principally generate three modified DNA bases [3 , 4]: 6-methyladenine ( 6mA ) , 4-methylcytosine ( 4mC ) and 5-methylcytosine ( 5mC ) . Most bacterial MTases are components of restriction-modification ( R-M ) systems; these MTases modify target DNA sequences in order to protect them from digestion by a cognate restriction enzyme , which is typically co-transcribed . R-M systems enable digestion of horizontally acquired DNA sequences that lack appropriate methylation marks , and thus protect bacteria from selfish elements and phage predation [5] . However , a subset of MTase genes are not accompanied by a cognate restriction enzyme , and a few of these so-called ‘orphan’ MTases are known to regulate diverse host cell processes ( reviewed in [2 , 6 , 7] ) . For example , the 6mA MTase Dam , which is found in E . coli and many other gamma proteobacteria , regulates DNA replication [8] , mismatch repair [9] , transposition [10] and pilus biogenesis [11] , while the adenine MTase CcrM is a critical regulator of the Caulobacter crescentus cell cycle [12] . Recently , Dcm , an E . coli orphan MTase that produces 5mC , was found to modulate antibiotic resistance [13] , translation [14] , and stationary phase gene expression [15] . Additionally , MTases of Type III R-M systems have also been found to mediate phase variation [16 , 17] . Nonetheless , roles for the majority of bacterial MTases—which are predicted in over 90% of genomes [18]—have not been defined . Here , we investigated the importance of DNA methylation in the cholera pathogen , Vibrio cholerae . The canonical El Tor O1 V . cholerae strain N16961 [19] is predicted to encode 4 MTases [18] with distinct catalytic activities . The V . cholerae Dam homologue has been shown to be critical for replication of one of the organism’s two chromosomes , and is consequently essential for survival [20 , 21] . In contrast , vc1769 ( hsdM ) , vca0198 ( vchM ) and vca0447 have been found to be not essential , either through targeted mutagenesis [22] or in transposon insertion sequencing screens [23–25] . VC1769 is a homologue of the E . coli 6mA-generating HsdM , which is part of a type I R-M system [26] , and vca0447 , a putative orphan adenine MTase , remains uncharacterized to date . VchM is present with almost 100% identity in 91% ( 10/11 ) of complete V . cholerae genome sequences at NCBI , but is absent from more than 90% ( 20/22 ) of non-cholerae Vibrios ( S1 Fig ) , and thus appears to have been acquired by horizontal gene transfer . VchM was previously characterized as an orphan 5mC MTase that targets the consensus sequence RCCGGY [22 , 27] , but the importance of this enzyme to host gene expression has not been defined . Here , we demonstrate that VchM is required for optimal V . cholerae growth , both in vitro and during infection . Bisulfite sequencing defined the V . cholerae 5-methylcytosine methylome , and RNA sequencing analyses revealed that VchM regulates expression of genes important in a variety of cellular processes , potentially through direct intragenic methylation . Unexpectedly , transposon insertion sequencing-based analyses of vchM genetic interactions revealed that deletion of vchM suppresses the essentiality of the σE envelope stress response pathway . Additional transposon mutagenesis studies identified host genes that are required for envelope stability , in whose absence σE is induced . Many of these genes , especially those involved in the modification of the lipopolysaccharide inner core , contain VchM recognition sites . Mutational analyses suggest that VchM cytosine methylation directly downregulates the expression of some of these LPS modification genes . Thus , our findings show that V . cholerae has co-opted the horizontally acquired VchM DNA methyltransferase to regulate a diverse array of critical cellular processes .
We created in-frame deletion mutants of V . cholerae’s non-essential MTases—vc1769 ( hsdM ) , vca0198 ( vchM ) , and vca0447—and compared the growth of each mutant to an isogenic wild type ( wt ) El Tor biotype strain during infection of suckling mice , using competition assays . The ∆vchM mutant displayed significantly attenuated ( ~10 fold ) growth in vivo , while the recovery of the ∆hsdM and ∆vca0447 mutants was equivalent to that of WT cells ( Fig 1A ) . When vchM was deleted in the prototypical classical biotype V . cholerae strain , O395 , ten-fold attenuation in vivo was also observed ( Fig 1A ) . Similarly , infant mice inoculated solely with ∆vchM V . cholerae accumulated 30-fold fewer intestinal bacteria than did animals infected with WT V . cholerae ( Fig 1B ) . The ∆vchM mutant was also outcompeted by wt cells when grown in vitro ( Fig 1C ) and displayed a reduced doubling rate when grown in monoculture ( Fig 1D ) . Together , these data indicate that ∆vchM cells , unlike other mutants lacking an orphan 5mC MTase [15] , have an intrinsic growth defect that manifests both during in vitro and in vivo growth . To confirm that the growth defect of the ∆vchM mutant is due to the absence of 5mC methylation , rather than to a second site mutation or a non-enzymatic role of VchM , we re-introduced a wildtype or catalytically inactive vchM ( C109A ) allele into the ∆vchM mutant at the endogenous locus . Restriction digests confirmed that gDNA from the strain into which the wt sequence was reintroduced—like that of wt V . cholerae—was resistant to cleavage by BsrFI , which cannot cleave methylated RCCGGY motifs . In contrast , gDNA from ∆vchM and C109A V . cholerae was sensitive as expected ( Fig 1E ) . The WT replacement , but not the C109A replacement , also fully complemented the in vitro growth defect of the ∆vchM parent ( Fig 1A and 1C ) . Thus , the catalytic activity of VchM is required for optimal bacterial growth , suggesting 5mC DNA methylation controls processes necessary for optimal V . cholerae growth . Previous work revealed that VchM recognizes and methylates a consensus sequence of RCCGGY ( methylated residue underlined ) [22] . Interestingly , the distribution of RCCGGY motifs is not uniform across the genome ( S2 Fig ) . A previous study evaluated the methylation status of these sites and found that three VchM sites in V . cholerae are undermethylated in late exponential phase , compared to the rest of the genome [27] . However , it remained unknown whether V . cholerae’s pattern of 5mC methylation could vary between different growth states , as was observed for the E . coli orphan 5mC DNA MTase , dcm [15] . Thus , we used bisulfite sequencing , in which non-methylated cytosines are converted into uracils and detected as C to T transitions , to assess the methylation status of all cytosines in the genomes of bacteria in exponential and stationary growth phases , as well as V . cholerae that had been isolated from infected rabbit intestines . This approach was highly specific and sensitive , revealing a clear distinction between methylated cytosines within VchM’s RCCGGY target sites and non-methylated cytosines in other sequence contexts ( Fig 2A , S3A Fig ) . The bisulfite sequencing results ( GEO Accession number GSE73975 ) revealed that virtually all VchM motifs in the genome are methylated with high frequency in exponential phase , i . e . , RCCGGY sites on >90% of the DNA molecules were fully methylated ( Fig 2A ) . Of the ~2100 VchM motifs in the genome , only 3 were persistently non-methylated ( methylated <20% of the time on both strands ) . These sites , which were previously described , are all located within intergenic regions between two divergently oriented genes , and are thought to be non-methylated in exponential phase due to binding by transcription factors [27] . Most VchM sites were also methylated with high frequency in stationary and in vivo grown cells ( Fig 2A , S3B Fig ) . The non-methylated sites #2 and #3 were similarly non-methylated during infection , but site #1 ( Fig 2A ) , which is located in between VC1558 and VC1559 , showed increased methylation in vivo ( ~51% of cells ) compared to in vitro exponential grown cells ( ~20% of cells ) . While the functional consequence of this difference remains to be defined , our data show that the methylation of VchM sites is highly saturated across the genome ( i . e . , virtually all RCCGGY motifs are fully methylated ) and is not drastically altered during V . cholerae growth in the intestine . To investigate the impact of cytosine methylation on V . cholerae gene expression , we compared the transcriptomes of WT and ∆vchM cells in the C6706 strain background ( GEO Accession number GSE73974 ) . We identified 134 genes with significantly ( p-value <0 . 05 ) elevated transcript abundance in the ∆vchM mutant , and 63 genes with reduced transcript abundance ( S1 Table ) . While there was no significant enrichment of VchM motifs within the genes with reduced transcript levels , seventy-five of the genes with elevated transcript levels contained a RCCGGY motif , which is significantly more than would be predicted by chance alone ( Fig 2B ) . The correlation between the presence of VchM target sites and increased transcript abundance in the ∆vchM mutant was also observed when analysis was not restricted to genes with significantly altered transcript levels . Genome wide , relative transcript levels were significantly higher in ∆vchM cells versus wt for genes that contained 1 or more VchM targets within 200 bp of their transcriptional start sites [28] ( S4A Fig ) . We also observed a significant association between the number of RCCGGY target sites within a gene’s coding region and its expression change in ∆vchM cells , especially for genes containing more than 4 target sites ( Fig 2C ) . This result suggests that VchM methylation reduces gene expression of some genes . This significant association was independent of the genes’ GC contents ( S4B Fig ) and was not observed for several other similar motifs ( S4C Fig ) . Additionally , no strong association between the precise location of RCCGGY sites within genes and differential expression was observed; the motifs are similarly distributed throughout the coding region of all genes as well as those that are differentially expressed ( S4D Fig ) . To identify pathways that are consistently regulated ( directly or indirectly ) by VchM , we compared transcriptomic analyses for C6706 and O395 ∆vchM mutants and the corresponding wt strains . We identified 79 genes that were significantly and differentially ( p-value < 0 . 01 ) expressed in the absence of VchM in both biotypes ( Fig 2D , S2 Table ) . Approximately 25% of these are hypothetical genes , while the remainders are predicted to participate in a variety of critical processes , including energy production ( 22% ) , amino acid metabolism ( 10% ) and iron utilization ( 10% ) . Expression of the iron utilization genes was reduced in ∆vchM cells compared to wt cells , and thus is unlikely to be directly controlled by VchM-dependent methylation . Likewise , while the genes involved in the TCA cycle and respiratory chain are upregulated in ∆vchM cells , most do not contain RCCGGY motifs , suggesting that their elevated expression may also be an indirect response to the loss of methylation . To gain more insight into the physiology of the vchM mutant , in particular the processes that it utilizes for growth , we used a transposon-insertion sequencing ( TIS ) approach to screen for loci that are differentially required for survival in ∆vchM or wt V . cholerae . High-density transposon libraries were created in WT and ∆vchM cells grown in rich media , and all the transposon insertion sites in each library were sequenced . No genes specifically required by the ∆vchM mutant ( i . e . , genes lacking insertions only in the ∆vchM background ) were identified in this screen other than the positive control , vchM itself . However , we unexpectedly identified 5 genes ( Table 1 , Fig 3A ) in which there was a significantly higher frequency of transposon insertion in ∆vchM cells compared to the wt strain ( Fig 3B , S5 Fig ) , suggesting such genes are potentially more important to the survival or optimal in vitro growth of the wt strain than that of the ∆vchM mutant . Remarkably , four of the five genes—rseP , degS , rpoE and rep—are known to participate in the σE envelope stress response pathway ( reviewed in [29] ) . In the σE stress response pathway , which has been best described in E . coli but has also been characterized in V . cholerae ( Fig 3C ) , σE is sequestered at the membrane by an integral membrane anti-sigma factor , RseA [30–32] . Upon envelope stress , specific outer membrane proteins become unfolded and expose a terminal YXF motif , which interacts with and activates the intramembrane protease DegS [33 , 34] . Envelope stress may also dysregulate outer membrane biosynthesis , leading to increased periplasmic LPS , which binds and inactivates an additional DegS inhibitory factor , RseB [35 , 36\ . The presence of LPS and OMP stimuli permits DegS to cleave within the periplasmic domain of RseA [34 , 37 , 38] , allowing a second intramembrane protease , RseP , to cleave the cytosolic domain of RseA [38–40] . These proteolytic cleavages lead to the release of σE into the cytosol , where it can engage RNA polymerase to direct transcription of the σE regulon , which reduces de novo expression of outer membrane proteins while facilitating the refolding of existing ones [41–44] . An ATP-dependent helicase , rep , was also recently found to be required for induction of some σE regulon genes [45] , though the exact mechanism by which this occurs is unknown . Both in E . coli and V . cholerae , rpoE and related factors have been found to be essential [46–49] , although suppressor mutations that permit survival of rpoE-deficient cells have also been identified [47 , 50–52] . In V . cholerae , the outer membrane protein OmpU is the predominant determinant of rpoE activation , both under normal growth conditions and in response to envelope stress [53] , and ompU mutations are the most frequently identified suppressors of rpoE essentiality [47] . Suppressors directly associated with LPS synthesis or processing have not been identified in V . cholerae . Our TIS analysis revealed that rseP , degS , rpoE and rep , which are all required for activation of the rpoE pathway , appeared dispensable in ∆vchM cells , suggesting that disruption of vchM may be a previously unrecognized suppressor of rpoE essentiality in V . cholerae . To validate this hypothesis , we attempted to delete rpoE in both WT and ∆vchM cells , using a targeting construct designed to replace rpoE with a kanamycin-resistance cassette . As in previous analyses [47] , a very high percentage ( here , 100% ) of the putative ∆rpoE::aphR mutants generated in the wt background were false positives that retained an additional antibiotic resistance marker , reflecting retention of the targeting vector and failure to disrupt rpoE ( Fig 4A ) . In contrast , 99% of ∆vchM ∆rpoE candidates did not retain the allelic exchange vector , suggesting that deletion of rpoE in the ∆vchM strain can be readily achieved . Furthermore , a putative ∆vchM ∆rpoE colony was randomly selected and the absence of σE was confirmed by western blot analysis ( Fig 4B ) . Thus , V . cholerae does not require the presence of rpoE in the absence of vchM . Interestingly , our western blots also revealed that basal levels of σE were only ~30% of WT levels in the ∆vchM mutant ( Fig 4B ) . Since σE expression and activity is elevated in response to envelope stress , the lower basal level σE in ∆vchM cells suggests that 5mC methylation by VchM may contribute to envelope stress , and thereby modulate production of σE . Reduced activation of σE in cells lacking VchM could allow rpoE to be dispensable in these cells , at least under the conditions at which the mutants were selected . In addition to confirming the viability of V . cholerae lacking vchM and rpoE under relatively favorable growth conditions ( rich media ) , we assessed whether these mutations altered bacterial growth in a variety of more challenging environments . We found that growth of the ∆vchM ∆rpoE mutant was equivalent to that of the ∆vchM parent strain in LB monocultures ( Fig 4C ) , and that it exhibited an equivalent ~10-fold growth impairment as ∆vchM cells in competition assays with WT cells in aerobic LB culture ( Fig 4D ) . However , in the presence of the outer membrane targeting antimicrobial peptide , polymyxin B , which is known to induce σE above baseline levels in V . cholerae [53] , growth of the ∆vchM ∆rpoE mutant was reduced far more than that of the ∆vchM strain ( Fig 4C ) . Thus , the strain that has no capacity to activate the σE stress response pathway ( e . g . , ∆rpoE ) is at a marked growth disadvantage in envelope stress-inducing environments , and the ∆vchM mutation does not suppress V . cholerae’s need for rpoE under these conditions . Similarly , deletion of vchM did not suppress V . cholerae’s need for σE during growth in the infant mouse intestine . In in vivo competition experiments , the ∆vchM ∆rpoE mutant was recovered at more than a 1000-fold reduced frequency ( CI ~0 . 0007 ) than the wt strain from the infant mouse intestine ( Fig 4E ) , and with 100-fold reduced frequency when competed against the ∆vchM parent strain ( CI ~0 . 01 ) . These results suggest that deletion of rpoE exacerbates the ~10-fold in vivo proliferation deficiency of the ∆vchM mutant , which has a CI vs the wt strain of ~0 . 1 , by a factor of 100 . A similar ~100-fold effect of rpoE disruption on V . cholerae growth in vivo was observed using an rpoE-deficient strain containing an ompU promoter mutation ( pOmpU mut ) that reduces porin expression . Since previous studies showed that deletion of ompU does not impair V . cholerae intestinal colonization [54] , the in vivo attenuation of this double mutant can be fully explained by the absence of rpoE . Finally , since the RNA-seq results revealed that ∆vchM cells had elevated expression of TCA cycle and respiration genes , we assessed the growth of the ∆vchM and ∆vchM ∆rpoE strains in anaerobic conditions , which would also be encountered during host infection . Relative to the WT strain , the ∆vchM mutant exhibited a similar growth defect in both aerobic and anaerobic conditions ( Fig 4D ) . In contrast , the ∆vchM ∆rpoE mutant was significantly more attenuated than the ∆vchM parent during anaerobic growth , raising the possibility that the in vivo attenuation of ∆rpoE strains is in part explainable by the anaerobic conditions in the intestine ( Fig 4D ) . Interestingly , the deleterious effect of the anaerobic environment on the ∆vchM ∆rpoE mutant was eliminated by the addition of fumarate , which acts as a terminal electron acceptor for V . cholerae respiration during anaerobic growth [55] . Thus , non-respiratory growth ( e . g . , fermentation ) is specifically deleterious for V . cholerae lacking rpoE . It is possible that a fermentative byproduct is selectively toxic to ∆rpoE cells , or that physiological changes linked to fermentative growth lead to increased cell envelope stress . We used transposon-insertion sequencing to begin to explain why the presence of VchM correlates with higher basal σE levels . We hypothesized that VchM regulates genes whose products are necessary for optimal envelope stability and conducted a screen to identify genes whose absence leads to increased envelope stress . In cells with a functional envelope stress pathway , disruption of genes that are required for envelope stability should induce envelope stress that can be ameliorated by the σE pathway . However , in cells lacking rpoE , such mutations ( and the resulting stress ) may be lethal . Using TIS , we identified 13 candidate genes that could tolerate transposon insertion in the ∆vchM background but not in ∆vchM ∆rpoE cells ( Fig 3A , Table 2 ) . Many of these genes are known to be involved in envelope biogenesis ( Table 2 ) , including several genes required for modifying the inner core component of LPS ( orange shaded genes ) . Consistent with our hypothesis , disruption of many of these LPS synthesis genes ( including waaC and rfaF ) is known to cause induction of the σE stress response in E . coli [36 , 56] . We also identified non-LPS outer membrane-related genes , such as smpA , a known σE-regulating gene that is required for assembly of outer membrane beta-barrel proteins ( OMPs ) and for correct outer membrane biogenesis , and lnt , which acylates lipoproteins transported by the Lol complex [57 , 58 , 59] . It is known that overexpression of the major outer membrane protein , Lpp , in E . coli , induces the σE stress response , potentially by dysregulating outer membrane lipoprotein insertion through the LolA/B complex [44] . Additionally , the screen yielded genes that are not clearly tied to the rpoE pathway or outer membrane biogenesis , including cysB , a transcriptional activator that regulates sulfur transport [60] , and vca0200 and vca0201 , two hypothetical genes that are specific to V . cholerae and lie downstream of vchM . Using mutants from an ordered V . cholerae transposon library [24] , we validated our hypothesis that these mutants contain more σE than wt cells ( Fig 5A ) , suggesting envelope stress is increased in the absence of these genes . We speculated that expression of some of these loci might be directly regulated by VchM-dependent methylation , which could then allow them to modulate cellular levels of σE . Interestingly , the LPS-related candidate genes are enriched for RCCGGY motifs compared to candidate genes of the other classes ( p-value < 0 . 05 by Fisher’s exact test ) , so we focused on this subset . We used site directed mutagenesis to replace the RCCGGY motifs in vc0225 , vc0236 , vc0240 and vc2437 with non-consensus sites that do not alter the protein sequence . While there were no significant differences in mRNA expression of vc0225 , 0236 and 0240 after RCCGGY ablation , replacing all three RCCGGY motifs in vc2437 caused an approximately 5-fold increase in transcript abundance compared to WT levels ( Fig 5B ) , suggesting that methylation of vc2437 by VchM reduces its expression . Consistent with the idea that regulation is methylation-dependent , there was a less than two-fold difference between expression of the wt and mutated locus in the vchM background . Furthermore , a mutant harboring a disruption of vc2437 ( vc2437::pGP ) had significantly elevated basal σE levels ( Fig 5C ) , suggesting that downregulation of this gene’s expression can induce V . cholerae envelope stress .
We carried out methylomic , transcriptomic , and genetic analyses of the role of the orphan cytosine MTase , VchM , and uncovered an unexpected connection between cytosine modification and outer membrane stress in V . cholerae . To our knowledge , VchM is only the second orphan 5mC-catalyzing bacterial MTase to be characterized in depth and genetic interactions comprehensively identified . Strains lacking VchM exhibit impaired growth in vivo and during both aerobic and anaerobic growth in vitro , and transcriptomic analysis indicates that many important metabolic pathways are altered in ∆vchM cells . Comparative transposon insertion sequencing analyses of wt and ∆vchM V . cholerae revealed that deletion of vchM , suppresses V . cholerae’s requirement for the σE envelope stress response pathway , which likely reflects reduced basal activity of this pathway in the ∆vchM strain . Notably , deletion of vchM does not mitigate V . cholerae’s need for rpoE under challenging growth conditions , and by studying the ∆vchM ∆rpoE mutant we were able to quantify the contribution of σE during host infection and during anaerobic growth as well as screen for genes that cannot be disrupted in the absence of the σE stress pathway . These genes , which are likely required for optimal envelope stability , include loci that catalyze the heptose modification of LPS and are enriched for VchM recognition motifs . Our data indicate that methylation directly regulates expression of at least some of these genes , and thus reveals one of the mechanisms by which vchM influences V . cholerae physiology . Unexpectedly , we found that VchM is required for optimal V . cholerae growth in standard laboratory media ( LB ) . As deletion of rpoE does not further impair growth of the ∆vchM mutant under this condition , it is unlikely that the mutant’s dysregulation of the σE envelope stress response pathway alone accounts for its slower proliferation . Instead , additional processes , such as those shown by transcriptomic analyses to be altered by the absence of VchM , ( e . g . , the amino acid and carbohydrate metabolism pathways and those mediating aerobic respiration ) , may account for the growth phenotype . However , it remains unclear whether the growth deficiency is due to altered expression of a single pathway or to the cumulative effect of simultaneously dysregulating numerous genetic loci . Nonetheless , our data suggests that the horizontally acquired VchM has become an integral component of V . cholerae’s regulatory networks . In wt V . cholerae , rpoE is an essential gene [47]; thus , it is noteworthy that rpoE can be deleted in the ∆vchM strain , as relatively few suppressors of rpoE essentiality have been identified . Additionally , as noted above , our analyses indicate that growth of the ∆vchM and ∆vchM ∆rpoE strains can be equivalent . Deletion of vchM appears to reduce basal expression/activation of σE , likely reflecting a reduced need for this factor under conditions that apparently do not produce significant envelope stress . A similar reduction has been observed in strains in which OmpU levels are reduced and rpoE is not essential [47] . However , we do not observe reduced expression of OmpU in the ∆vchM cells ( S6 Fig ) , suggesting ∆vchM suppresses σE essentiality through a novel mechanism . Furthermore , deletion of vchM does not render rpoE dispensable under all growth conditions . We observed marked differences ( e . g . , 10–100 fold ) between the growth of ∆vchM and ∆vchM ∆rpoE strains in the presence of an antimicrobial compound that activates the σE pathway , in an animal model of infection , and during anaerobic growth . These data suggest that the vchM mutant retains the ability to activate the σE regulon in response to envelope ( or potentially other ) stress , despite its lower basal level of σE . We performed a TIS screen to identify mutations that are detrimental specifically in the absence of rpoE , as such mutations are likely to activate σE , and thus might also be regulated through VchM methylation . This screen identified a variety of loci whose products are associated with the cell envelope , including several factors required for heptose modification of the LPS inner core . As anticipated , mutations in these loci were associated with increased σE abundance , suggesting these mutants have defects in cell envelope integrity . The deletion of genes involved in LPS modification , especially those catalyzing inner core and Lipid A synthesis , have been previously linked to abnormal LPS structure and σE activation in E . coli [36 , 56 , 61] . Intriguingly , many genes encoding the LPS modifying enzymes identified by our TIS screen contained RCCGGY motifs , raising the possibility that some of these genes might be directly regulated by VchM methylation . Indeed , synonymous disruption of three VchM targets sites in one locus , vc2437 , led to enhanced expression of this gene , suggesting that VchM-dependent methylation may limit its expression . Since disruption of vc2437 leads to increased accumulation of σE , we hypothesize that increased levels of Vc2473 in the vchM mutant will reduce stimuli activating the σE stress response , as outlined in our model ( Fig 5D ) . In E . coli , two signals are required for RseA cleavage and thus σE induction: activation of DegS through interaction with unfolded outer membrane proteins [33 , 34] and displacement of RseB from RseA through titration by periplasmic LPS [36] . Lowered expression of vc2437 could induce and sustain both of these signals . Reduced heptose modification may produce aberrant periplasmic LPS molecules that bind and compete RseB away from RseA , lowering the threshold for DegS activation [35] , while simultaneously , aberrant LPS may alter outer membrane structure , facilitating the misincorporation and unfolding of outer membrane proteins . Additional VchM targets may also exhibit methylation-regulated expression , since transcriptomic and genomic analyses showed that there is a significant correlation between the presence of intragenic RCCGGY motifs and increased expression of these genes in ∆vchM cells . However , it is likely that cytosine methylation does not universally modulate gene expression in V . cholerae , since mutation of the single RCCGGY motif in each of three LPS modification genes did not detectably alter gene expression . Genes containing 5 or more motifs showed the greatest elevation in expression in the vchM mutant , raising the possibilities that the effects of methylation may be additive within a single gene and/or that a threshold level of methylation must be present for regulation to occur . It is likely that additional regulatory factors also constrain the influence of methylated bases on gene expression . VchM is the second bacterial orphan 5mC-catalyzing MTase to be characterized extensively at the genomic and transcriptomic levels , and the first for which genetic interactions have been comprehensively defined . Interestingly , our findings reveal striking differences between the functional consequences of methylation by VchM and the previously characterized E . coli 5mC-catalyzing orphan MTase , Dcm [15] . While Dcm regulates stationary phase expression of ribosomal proteins and mediates resistance to antibiotics in E . coli [13–15] , VchM is required for optimal bacterial growth and modulates cell envelope stress responses in V . cholerae . At the genomic level , the E . coli genome is enriched in Dcm targets ( CCWGG ) [15] , while the VchM target , RCCGGY , is not overrepresented in the V . cholerae genome . Furthermore , Dcm sites are undermethylated during exponential phase and rise during entry into stationary phase , while VchM target sites are nearly fully methylated under all growth states tested , including during infection , suggesting that the two enzymes differ in their expression and/or activity . While increases in gene expression were observed in both ∆dcm and ∆vchM cells , differentially expressed genes in ∆dcm strains are not enriched for intragenic CCWGG motifs and are instead thought to be controlled indirectly through rpoS-dependent regulation [14 , 15] . In contrast , there is a significant association between the presence of intragenic VchM targets and elevated gene expression in ∆vchM cells , and mutational analyses suggest that the methylation of these motifs can dampen gene expression . Thus , despite sharing similar catalytic activities , different orphan 5mC MTases can regulate diverse processes through different mechanisms . The mechanism ( s ) by which methylation alters gene expression have not been characterized , but many possibilities can be envisioned . For example , methylation within transcribed sequences may influence transcriptional attenuation or transcript half life , perhaps due to effects upon transcript or template structure . Methylation might also influence transcription initiation , e . g . by influencing binding of regulatory factors that control gene expression . It should also be noted that many genes whose expression differs between wt and vchM V . cholerae are likely indirectly controlled by methylation , e . g . , are governed by factors influenced by methylation , but are not themselves methylated . Furthermore , methylation may globally alter chromatin structure in ways that modulate gene expression . Investigation of the precise means by which cytosine methylation in V . cholerae influences gene expression will be the focus of future studies . Banerjee et al . [22] found that the closest VchM homologues lie in non-Vibrio species , suggesting VchM was horizontally acquired . The introduction of a MTase such as VchM , which modifies thousands of sites and potentially alters gene expression at numerous loci , would exert selective pressure on MTase recognition sites . Consistent with this theory , we found that RCCGGY motifs in V . cholerae are not randomly distributed; instead , the genome includes regions that are enriched or depleted for VchM recognition sites ( S2B Fig ) . Interestingly , many of the σE-related genes that become dispensable in V . cholerae lacking vchM ( as well as vchM itself ) are located in regions containing a disproportionately low number of RCCGGY motifs ( binomial test p-value <4 . 8e-6; S2B and S2C Fig ) . It is possible that target sites in these loci have been selected against , as methylation might interfere with beneficial regulatory processes that promote σE expression . In conclusion , we found that VchM , a 5mC-catalyzing DNA methyltransferase , serves critical roles in V . cholerae growth and envelope stress signaling . The processes and mechanisms through which VchM exerts control are strikingly different from E . coli Dcm , the other well-characterized bacterial 5mC DNA MTase . Thus , future investigations of the regulatory roles of additional bacterial DNA MTases will likely reveal new regulatory schemes for the control of diverse bacterial processes .
All animal infections were performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health . All animal protocols were reviewed and approved by the Harvard Medical Area Standing Committee on Animals ( protocol 04316 ) . Isofluorane was used for anesthesia . All strains were grown on LB Miller ( 1% NaCl ) unless otherwise noted . Antibiotic concentrations used were 200 μg/mL streptomycin ( Sm ) , 50 μg/mL kanamycin ( Km ) , 100 μg/mL ampicillin ( Amp ) , and 50 μg/mL polymyxin B . Wildtype V . cholerae C6706 , V . cholerae O395 and E . coli SM10 ( lambda pir ) carrying the Himar1 suicide transposon vector pSC189 [62] were grown at 37°C in LB + Sm and LB + Amp , respectively . Individual transposon mutants from the ordered V . cholerae transposon library [63] ( which contain intact vchM ) were grown overnight in LB + Sm + Km , or plated as lawns on LB + Sm + Km at 37°C . All primers used for mutant generation can be found in S6 Table . Deletion plasmids for hsdM ( vc1769 ) , vchM ( vca0198 ) and vca0447 were derived from the allelic exchange vector pCVD442 [64] using isothermal assembly [65] . Each deletion construct encodes the first five and last four amino acids of the gene of interest , with intervening sequences removed . Suicide plasmids were conjugated into V . cholerae and sucrose-based counter-selection performed as previously described [66] to create in-frame deletions . Allelic exchange of rpoE for a kanamycin resistance gene was carried out using a previously generated suicide vector [47] and a similar protocol as above . However , cells were plated on both 10% sucrose and kanamycin to select for the ∆rpoE mutant . For the introduction of a vchM C109A mutation into its endogenous locus , an allelic exchange vector containing the entire vchM gene with a C109A mutation flanked by 500 bp of upstream and downstream sequence was created , conjugated into ∆vchM cells , and counter-selected on sucrose plates . Subsequently , a second exchange vector was constructed containing wildtype vchM sequence that included 200 bp flanking sequence on each side of the C109 codon , which was used to revert the vchM C109A allele back to wildtype . Similar constructs and methodology were used to replace the single RCCGGY motifs of vc0225 , vc0236 , vc0240 with ACAGGT , ACAGGC , and GCAGGT , respectively . For vc2437 , a 850 bp fragment encompassing mutations in the three RCCGGY motifs ( converted to GCCTGC , GCAGGT and GCAGGC ) were synthesized ( Integrated DNA Technologies ) and used to carry out allelic exchange . For vc2437 disruption , an internal 850 bp fragment of vc2437 ( derived from the PCR product using primers vc2437-mut1F and vc2437-mut3R ) was blunt ligated into the suicide vector pGP704 [67] and conjugated into V . cholerae . All deletions , reversions and mutations were confirmed by Sanger sequencing ( Genewiz ) . 1 ug of purified genomic DNA from the indicated strains was subjected to digestion with SalI in the presence or absence of BsrFI at 37°C for 30 minutes . The reactions were separated by gel electrophoresis , stained with ethidium bromide and imaged on a FujiFilm FLA-5100 fluorescent imager . For growth curves , overnight V . cholerae cultures were diluted 1:1000 in LB + Sm and any additional chemicals as indicated . These cultures were grown at 37°C in a Bioscreen C optical density reader ( Growth Curves USA ) with OD600 measurements taken at 15 minute intervals for 12 hours . For competitive growth experiments , overnight stationary cultures of wildtype and mutant V . cholerae , one of which was lacZ- , were independently diluted 1:1000 in LB + Sm and then mixed in a 1:1 ratio . 20 μl of the diluted mixture was inoculated into 2 mL of LB + Sm and grown at 30°C for 24 hours . At the start and end of the experiment , cells were diluted and plated onto LB + 60 μg/mL X-gal to enumerate the ratio between wildtype and mutant cells . For anaerobic experiments , overnight cultures of V . cholerae were diluted into pre-warmed LB + Sm that was pre-depleted for oxygen by sitting overnight anaerobically at 37°C . Diluted cells were mixed and inoculated into 2 mL of oxygen-depleted LB + Sm ( + 50 μg/mL fumarate when indicated ) and after 24 hours of growth at 37°C , cultures were removed from anaerobic conditions and the competitive index determined on X-gal as above . For in vivo competitions , overnight stationary cultures of LacZ- wildtype or mutant V . cholerae were diluted and mixed 1:1 as above . 50 uL of the diluted culture was orally inoculated into 5-day-old suckling mice ( Charles River ) . After 24 hrs , the mice were sacrificed , the small intestine homogenized using a mini-beadbeater-16 and two 3 . 2mm stainless steel beads ( BioSpec Products Inc . , Bartlesville , OK , USA ) for 2 minutes , and dilutions of the homogenate were plated on LB + Sm + 60 ug/mL X-gal plates to enumerate the ratio of wildtype and mutant bacteria . Genomic DNA was extracted from two biological replicates of exponential phase , overnight stationary phase and frozen rabbit cecal fluid V . cholerae using the Wizard Genomic DNA purification kit ( Promega ) . Bisulfite conversion of the DNA was carried using the EZ DNA Methylation Kit ( Zymo ) twice to ensure high conversion efficiency . The converted DNA was then amplified by PCR using the Kapa HiFi Uracil+ polymerase for 12–15 cycles ( Kapa biosystems ) and sequenced on the MiSeq platform ( Illumina ) . Bismark [68] was used to call 5mC sites from the bisulfite sequencing data . Each cytosine site was assigned with two counts , representing the numbers of reads that had a C->T conversion ( non-methylated ) and those that did not have a C->T conversion ( methylated ) . The fraction of methylation was then calculated for each cytosine site and a minimum total coverage of 10x was used to filter out cytosine sites with too few read counts for estimating the methylation frequency . Purified mRNA was extracted from two biological replicates of exponential phase V . cholerae and converted to cDNA as previously described [69] . RNA sequencing was performed on a HiSeq 2500 with 100bp single-end reads . To call differentially expressed genes from RNAseq data , we first mapped raw RNA reads for each sample to the Genbank V . cholerae El Tor N16961 reference ( Accession number: NC_002505 for chromosome I and NC_002506 for chromosome II ) , which is highly similar ( >99 . 6% of VchM target sites are conserved ) . Reads that mapping to rRNA and tRNAs were excluded . A gene was included for differential expression analysis if it had more than one count per million reads ( CPM = 1 ) in at least two samples . Differentially expressed genes ( >2-fold differences , p-value <0 . 01 , false discovery rates <0 . 2 ) were identified by the software program edgeR [70] . Expression differences for all genes in ∆vchM C6706 and O395 cells are located in S7 Table and S8 Table . For motif counts within gene coding regions , we first use linear regression ( regress fold change on gene length ) to get residuals after removing gene length effects ( Fig 2B ) . Furthermore , to confirm that the correlation between RCCGGY count in gene body and gene expression fold change is not due to GC bias , or more generally less-specific motifs of RCCGGY , we use a linear regression to remove the effects of all less-specific motifs . For example , for RCCGGY , the less-specific motifs are RCCGG , CCGGY , RCCG , CCGG , CGGY , RCC , CCG , CGG , GGY , RC , CC , CG , GG , GY , R , C , G , Y . We observed partial correlation between motif count and gene expression fold change after removing effects of all less-specific motifs , as well as length of the gene . As shown in S4C Fig , only the RCCGGY motif has significant correlation with fold change . The RCCGGY motif distribution within genes was determined using a custom Python script . Briefly , RCCGGY motifs in every gene were localized to windows corresponding to 5% of the coding length of the gene and the sites in each window enumerated . Transposon libraries were created in wildtype , ∆vchM , or ∆vchM∆rpoE V . cholerae , and genomic DNA was purified and sequenced as previously described [23] , with the exception that 10 ug of purified genomic DNA was sheared to ~350 bp fragments through acoustic disruption ( Covaris , Woburn , MA , USA ) for each DNA library . After sequencing and mapping , the read counts for every TA site were tallied and assigned to annotated genes or intergenic regions using custom scripts [23] . The raw read count data for all libraries can be found in S1 Table . Reads in the WT and mutant TIS libraries were normalized for differences in library saturation and read depth through simulation-based resampling and then subjected to Mann-Whitney U statistical tests as previously described in the ARTIST pipeline [66] . Candidates with significant p-values ( <0 . 001 ) and > 5 fold differences in normalized read counts were considered as candidates for follow-up . In total , the WT , ∆vchM and ∆vchM ∆rpoE libraries contained ~650000 colonies with 118683 , 103029 , and 115845 unique transposon insertions detected from 3125378 , 656980 , 2709183 total mapped reads , representing insertions at 62% , 53% and 60% of all TA dinucleotides , respectively . The full ARTIST analyses for the ∆vchM and ∆vchM ∆rpoE experiments as well as the raw read counts data are found in S3 , S4 and S5 Tables , respectively . Strains of interest were harvested at mid-exponential phase ( OD 0 . 5 ) , lysed directly in 1X NuPAGE LDS buffer ( Novex ) containing 6uM DTT , separated by NuPAGE Bis-Tris gel electrophoresis and transferred onto nitrocellulose using the iBlot system ( Life Technologies ) . Blots were incubated with rabbit polyclonal antisera against σE or monoclonal antibody against RpoB ( sc56766 , Santa Cruz Biotechnology ) in 5% milk in TBST . Horseradish-peroxidase conjugated secondary antibodies ( Pierce ) and Supersignal West Pico chemilumeniscent substrate ( Pierce ) were used to detect primary antibody signal . Blots were visualized on X-ray film , which was subsequently digitized on a FujiFilm FLA-5100 imager , and bands quantitated using MultiGuage V3 . 1 image analysis software . Overnight stationary cells were inoculated into 3 ml LB + Sm medium , grown at 37°C until mid-late exponential phase ( OD 600 0 . 5–0 . 8 ) , harvested and total RNA extracted with TRIzol reagent ( Life Technologies ) . RNA was treated with Turbo DNase I for 30 min ( Life Technologies ) and subjected to qRT-PCR as previously described [71] . Briefly , 1 μg total RNA was used for the reverse transcription reaction with Superscript III first strand synthesis system with random hexamers ( Life Technologies ) . The synthesized cDNA was subjected to real time-PCR amplification using the Fast SYBR Green Master Mix kit ( Life Technologies ) on the StepOnePlus platform ( Life Technologies ) using primers shown in S6 Table . The amplification data was analyzed by ΔΔCT method utilizing rpoC mRNA as internal control .
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Methylation of DNA is used by numerous organisms to regulate a wide variety of cellular processes , but specific roles for most DNA methyltransferases have not been defined . We studied one such enzyme in Vibrio cholerae , the cholera pathogen , using genome-wide approaches to compare DNA methylation , gene expression , and the sets of genes required or dispensable for growth in bacterial strains that produced or lacked this enzyme . These studies allowed us to identify numerous cellular processes regulated , either directly or indirectly , by this cytosine methyltransferase . In particular , we found that an absence of enzyme activity was associated with reduced levels of a bacterial stress response; consequently , a stress response pathway that is essential in wild type bacteria is not needed for survival of the mutant lacking the methyltransferase . Similar genome-wide analyses can likely to be used to define the cellular roles of many additional uncharacterized DNA methyltransferases .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
A Cytosine Methytransferase Modulates the Cell Envelope Stress Response in the Cholera Pathogen
|
Marine viruses play a critical role not only in the global geochemical cycles but also in the biology and evolution of their hosts . Despite their importance , viral diversity remains underexplored mostly due to sampling and cultivation challenges . Direct sequencing approaches such as viromics has provided new insights into the marine viral world . As a complementary approach , we analysed 24 microbial metagenomes ( >0 . 2 μm size range ) obtained from six sites in the Mediterranean Sea that vary by depth , season and filter used to retrieve the fraction . Filter-size comparison showed a significant number of viral sequences that were retained on the larger-pore filters and were different from those found in the viral fraction from the same sample , indicating that some important viral information is missing using only assembly from viromes . Besides , we were able to describe 1 , 323 viral genomic fragments that were more than 10Kb in length , of which 36 represented complete viral genomes including some of them retrieved from a cross-assembly from different metagenomes . Host prediction based on sequence methods revealed new phage groups belonging to marine prokaryotes like SAR11 , Cyanobacteria or SAR116 . We also identified the first complete virophage from deep seawater and a new endemic clade of the recently discovered Marine group II Euryarchaeota virus . Furthermore , analysis of viral distribution using metagenomes and viromes indicated that most of the new phages were found exclusively in the Mediterranean Sea and some of them , mostly the ones recovered from deep metagenomes , do not recruit in any database probably indicating higher variability and endemicity in Mediterranean bathypelagic waters . Together these data provide the first detailed picture of genomic diversity , spatial and depth variations of viral communities within the Mediterranean Sea using metagenome assembly .
Bacteriophages ( viruses that infect bacteria ) , often referred to as phages , are considered the most abundant and diverse biological entities in aquatic systems [1] with an estimated population density of 107 per ml of seawater [2] . They are not only abundant but also important players in the energy and nutrient cycles [1 , 3–6] through the lysis of host microbial cells , phenomenon designated as ‘‘viral shunt” [7] . Phages also play a critical role in the evolution of bacteria , facilitating horizontal gene transfer and helping to increase genetic diversity in the microbial community [8 , 9] . Despite their importance , phage genetic diversity , evolution and distribution remains poorly characterized because phages do not share a universal marker gene analogous to the 16S rRNA gene in bacteria and archaea and most of marine microbes are still unculturable under laboratory conditions and therefore also their viruses [10] . Advances in next-generation sequencing have allowed developing culture-free approaches , such as metagenomics , providing a powerful tool that has revolutionized the analysis of microbial communities in several natural environments [11–14] . Large-scale metagenomic studies of marine viruses from both surface [15] and deep ocean [16 , 17] have advanced in the structure of viral communities , which appears to be more diverse than previously appreciated . Despite those major advances , since the amount of viral DNA recovered is small , viral metagenomes ( or viromes ) normally need a previous step for DNA amplification , using mostly multiple displacement amplification ( MDA ) , that is likely to produce highly biased samples [18] . Alternative library preparation techniques have been recently developed [10 , 19] . Although these techniques require ultra-low DNA quantities and introduce only minimal biases , they also have other drawbacks [19 , 20] . An alternative to all these methodologies is using the viral DNA present in metagenomes in relatively large amounts . It has been previously reported a high presence of viral DNA ( around 10% to 15% ) in marine metagenomes [21 , 22] likely belonging to cells that are undergoing lytic cycle [23] . Metagenomes ( the fraction > 0 . 2 μm ) will also include ( i ) viruses using the lysogenic cycle ( either integrated or as a plasmid ) , ( ii ) viruses attached/adsorbed to particles , and ( iii ) viruses larger than 0 . 2 μm . However , the vast majority is probably the replication intermediate generated during the lytic cycle . This natural amplification method increases the amount of viral DNA available that can be cloned into fosmids or assembled . Using this strategy , 206 complete marine phage genomes were recovered from a metagenomic sample from the Mediterranean deep chlorophyll maximum [24] and twenty-eight from two deep ( 1 , 000-m and 3 , 000-m ) Mediterranean Sea metagenomic libraries [25] . More recently , a complete set of genomes of a novel group of viruses , designed as magrovirus , that seem to infect the uncultured marine group II Euryarchaeota were retrieved from a cross-assembly of microbial , viral , and transcriptomic datasets [26] . It seems likely that metagenomes contain some important viral information , which is missing in viromes . In addition , another valuable tool that has emerged in the last decade is single cell genomics . Although still expensive and unreliable , due to the amplification steps , provides the sequences of individual microbes and , if they happen to be infected at the time of sorting , phages as well . This allows linking the phage to the host [27] . For example , a total of 69 SUP05-associated viruses representing five new genera within Caudovirales and Microviridae families were identified using single-cell amplified genomes [28] . Furthermore , a new technique , “viral tagging” , for sorting cells infected by all the phages in a sample has been described improving the analyses of virus-host interactions [29] . This method has been applied for a single strain of Synechococcus sp . WH7803 against Pacific Ocean cyanophages , showing an unprecedented viral diversity with at least 26 dsDNA viral populations capable of infecting Cyanobacteria [29] . There is also other recent technological advances for understanding dynamics of phage–host interactions such as phageFISH or microfluidic digital PCR ( reviewed in [10] ) . Other quantitative methods are now available to evaluate viral numbers in a sample e . g . estimate ssDNA virus abundance [30] . The Mediterranean Sea is seasonally oligotrophic and characterized by deep convective winter mixing and summer stratification of the water column . It is also relatively warm and deep , maintaining a relatively high temperature ( >13°C ) throughout the water column [31] . We previously analysed the deep chlorophyll maximum ( DCM ) in a single sample taken during fall ( October ) 2007 [21] by high throughput metagenomics . From the same station in the Mediterranean Sea at different depths of the water column including the DCM we have performed different sampling campaigns ( winter and summer ) during four consecutive years ( from 2012–2015 ) . Several new groups of microbes have been later described using assembly of Illumina high coverage metagenomes and metagenomic fosmid clones [32–35] . Recently , we took and sequenced samples from a depth profile every 15 meters , including also two additional samples from 1 , 000 and 2 , 000 meters at a single site in the off-shore Western Mediterranean . By high-throughput metagenomics , we were able to study the structure of the community , evaluate the presence of some ecologically relevant genes and reconstruct the genomes of representative microbes [36] . Although the purpose of these studies was only the description of the bacterial populations , we have found a considerable proportion of assembled contigs related to viruses in all the metagenomes . Thus , in this study we have described more than 1 , 300 viral genomic fragments larger than 10Kb , of which 36 represented complete viral genomes . Besides , we also included in the analysis five more samples from both , DCM and deep ( aphotic zone ) waters , collected along the Eastern Mediterranean Sea . These data provided a glimpse of the genetic diversity and variability of these putative phage sequences without any previous amplification step . This large-scale study using direct assembly from metagenomes i . e . from the cellular fraction , clearly shows that metagenomes are an important tool to study environmental viral communities containing complementary information which is missing in viromes that should be taken into consideration when studying viral genetic diversity in order to better understand the ecological roles played by viruses in the environment .
Frequently , in marine samples , seawater is sequentially filtered using different pore-sizes to separate different size fractions . For example , planktonic macroorganims ( >20 . 0 μm ) , eukaryotic cells and particle-associated microbes ( 5 . 0–20 . 0 μm ) , free-living prokaryotic communities ( 0 . 22–5 . 0 μm ) and finally the viral pool is concentrated by ultrafiltration . The comparison of the size-fractionated microbial communities in marine metagenomes showed that viral DNA was overrepresented in the particle-associated fraction [22 , 38] . This phenomenon has been attributed to the presence of more eukaryotic DNA and can be interpreted as a reflection of higher infection rate in this cellular fraction [38–41] . Using only metagenomic reads considered of viral origin obtained from the three different filter fractions ( 5 . 0–20 . 0 μm , 0 . 22–5 . 0 μm and <0 . 22 μm ) from the same seawater sample collected in September 2013 from the DCM in the western Mediterranean Sea , we could analyse the viral diversity across size fractions ( S1A and S1B Fig ) . The dendrogram ( Fig 1C ) and the principal coordinate composition ( PcoA ) ( Fig 1D , inset ) showed a clear separation between the three filter sizes at the level of the percentage identity of individual reads among metagenomes obtained from the same place and year ( Samples 13 , 22 and 23 ) . Although the predominant group of viruses in all the samples were attributed to members of the Caudovirales ( dsDNA viruses ) , the two metagenomic samples with larger pore size ( MedDCM-SEP2013-LF ( Sample 13 ) and MedDCM-SEP2013 ( Sample22 ) ) showed an increase in the percentage of the Myoviridae and a relative decrease in the number of Podoviridae in comparison with the virome ( MedDCM-SEP2013-Vir ( Sample 23 ) ) . As a reference , we have included other virome ( MedDCM-Vir-MDA ( Sample 24 ) ) , obtained from the same place in 2011 . However , unlike the other , this sample was amplified by MDA and clearly was enriched in ssDNA viruses ( mainly Microviridae ) , not surprising since MDA samples are known to be highly biased towards the amplification of this kind of viruses [20 , 42] . Same results were obtained from a second group of samples ( 16 and 18 ) collected from the same place at 20m in January ( 2015 ) , during the mixing of the water column [38] . Although this sample does not have a virome , particle-associated ( Sample 16 ) and free-living ( Sample 13 ) viral community were different between them and also with the summer samples ( Fig 1C and 1D , inset ) . These results show that metagenomes contain some important viral information , which is missing in the viromes and should be taken into consideration if we want to study the complete viral genetic diversity . As previously described and shown by recruitment [26] cellular metagenomes are an excellent source of viral DNA information . It should be noted that these classifications based on reads have some limitations for example the relatively few validated viral sequences deposited in public databases , and provide only a rough estimation of the community . However , these data suggest that different filter sizes contain different viral sequences . Metagenomes were assembled individually resulting in 45 , 698 contigs larger than 10Kb ( S1A Fig ) . Only 6 . 7% ( 3 , 009 ) were assigned as putative viral contigs based on similarity to viral sequences deposited in the NCBI nr database . However , in order to avoid chimeric assembly and support the viral origin , we selected only the contigs that ( i ) contained several hallmark viral genes ( i . e terminases , portal protein , tail protein and major capsid proteins ) or ( ii ) syntenic contigs with cultured viral genomes or metagenomic fosmids obtained previously from the Mediterranean Sea [24 , 25] . Finally , we manually selected 1 , 323 metagenomic viral contigs for further analysis , ranging from 10 to 196Kb ( average contig size 23Kb; GC% range 18–55 ) . It is remarkable that we have found several contigs with high similarity ( id > 99% ) to uvMED and uvDEEP genomes [24 , 25] in spite of the time elapsed between sample retrieval ( S2 Fig ) . A total of 39 , 949 open reading frames were identified and clustered based on sequence similarity into 20 , 951 protein clusters , 48% ( 9 , 968 ) of which showed significant homology to sequences present in the pVOGs ( Prokaryotic Virus Orthologous Groups ) database [16] , clearly being virus-related ( S1 Table ) . The highest percentage was classified within the Myoviridae family ( order Caudovirales ) including structural proteins ( tail tube protein , baseplate tail tube cap , baseplate wedge subunit ) DNA metabolism ( DNA endonuclease , helicase ) as well as genes involved in nitrogen metabolism during infection in cyanophages ( phytanoyl-CoA-dioxygenase and 2OG-Fe ( II ) oxygenase ) [43] . However , the comparison against several other datasets of uncultivated viral genomes [24 , 25 , 44 , 45] , including the viral RefSeq , showed that ca . 30% of the protein clusters ( 6 , 198 of 20 , 951 ) were exclusive in our dataset and most of them derived from easternmost and deep metagenomes suggesting a great diversity that remains to be discovered in bathypelagic regions . We constructed a phylogenetic tree using the large-subunit terminase extracted from the contigs ( 280 ) in order to evaluate their diversity ( S3 Fig ) , since it has been reported that this gene can be used as a marker to reconstruct phylogeny in tailed bacteriophages [46] . Besides , we included 1 , 220 sequences belonging to the previous metagenomic fosmid libraries from the Mediterranean Sea [24 , 25] and some other references ( S3 Fig ) . Most of the terminases contained a Pfam Terminase 6 domain ( PF03237 ) and the closest relatives of the ca . 60% of the sequences were terminases from cyanophages . Using a combination of different approaches ( see Methods ) we were able to assign putative hosts to 438 contigs ( ca . 33% of the total ) ( S2 Table and Fig 2 ) . The most frequent host prediction ( ca . 53% ) were Cyanobacteria , followed by Alphaproteobacteria , mainly SAR11 . While cyanophages were recovered mostly from the photic zone , we have obtained some pelagiphages also from bathypelagic waters . Twelve sequences could be assigned to SAR116 and three sequences clustered together with HMO-2011 , one of the most abundant phages in the ocean [47] . This is not surprising since most of the metagenomes come from the UP and DCM . However , we detected some new and uncharacterized contigs ( mostly from deep metagenomic sequences ) , probably belonging to new lineages . Bathypelagic regions are one of the least understood ecosystems on Earth . They are extreme environments highly oligotrophic and is already known that viral abundance decreases in the deeper water column [1 , 48] . It is important to emphasize here the peculiar nature of Mediterranean bathypelagic waters due to their relatively warm temperature [31] . The Pacific Ocean virome ( POV ) dataset that includes samples from the deep Pacific ( 1 , 000 to 4 , 300 m in depth ) [16] and more recently a larger dataset including many globally distributed deep-sea viral metagenomes from the Malaspina expedition [45] have provided new insights into viruses from the bathypelagic regions . However , none of the deep samples comes from the Mediterranean Sea . In addition , we found 50 contigs related to eukaryotic viruses with the lowest GC content ( S2 Table and Fig 2 ) . These contigs were mainly related to viruses of the Phycodnaviridae family such as Aureococcus anophagefferens , Phaeocystis globosa and Micromonas pusilla virus . Probably these metagenomic viral contigs come from sporadic blooms of marine phytoplankton since they have only been found in a specific metagenome . For example , Phaeocystis globosa contigs were only found in the Med-OCT2015-15m metagenome . We also found a new virophage and a virus that putatively infects marine group II archaea ( see below ) . Due to the fact that we have used several metagenomes to extract the contigs , we first grouped all the sequences into clusters in order to avoid genome redundancy . An all-versus-all comparison was performed using different percentages of identity and we decided to use a criterion of >20% coverage but with a nucleotide sequence identity >90% since the percentage of contigs clustering was similar at 90 and 95% ( current cut-off use for a viral population ) . However , this percentage decreased below 90% . Sequence similarity of the 1 , 323 contigs resulted in 927 different viral clusters ( VCs ) ; 177 with two or more representatives and 751 singletons ( S2 Table ) . We used two different methods to identify complete genomes from VCs ( i ) contigs with identical repeated sequences ( >30 nt ) at the 5′ and 3′ terminal regions that we called complete genome representatives ( CGRs following previous nomenclature [24] ) and ( ii ) contigs presenting relative gene order and content similar to database phage genomes that indicate completeness ( designated genomic fragments GFs [24] ) ( Table 1 ) . Moreover , after close manual inspection , we were able to extend the length of some genomes since the identity among contigs was higher than 99% , although they came from different years and depths . Some of these were classified as complete viral genomes by the presence of overlapping terminal regions . Since these complete genomes were retrieved from a cross-assembly of viral contigs belonging to different metagenomes , we called them Metagenome-Assembled Viral Genomes ( MAVGs ) . Five MAVGs coming from clusters 2 , 3 , 4 , 5 and 18 were obtained ( Table 1 ) . Fig 3 shows the reconstruction of MAVG-2 using sequences belonging to Cluster-2 coming from different metagenomic samples . This MAVG has been putatively classified as a new pelagiphage similar to HTVC008M ( see below ) . These MAVGs showed large overlaps of nearly identical contigs ( >99% ) from different samples suggesting that some phage populations can survive during several years showing a remarkable genetic stability . A recent study by [49] using only cyanophage isolates collected from the same locations over a decade revealed similar results showing cyanophage genomic clusters that remained genetically invariant . However , we have shown here that this hypothesis can be extrapolated to other groups such as pelagiphages . In the same way but with contigs from one single sample , we were able to reconstruct a complete genome , MAVG-1 , based on the similarity to Synechococcus metaG-MbCM1 , an already described cultured phage [29] ( S4 Fig ) . In previous studies where fosmid libraries were used , the length of the insert size ( normally 30–40Kb ) limited the maximum size of the complete genomes obtained [24 , 25] . However , using metagenome assembly we have recovered 36 complete genomes with a length ranging from 30 to 196Kb ( Table 1 ) ( GC content ranging from 27 . 7 to 48 . 8% ) . In order to analyse the relationships among the complete genomes retrieved here with several phage reference genomes available ( 400 ) , including those from the Mediterranean uvMED and uvDEEP , we performed an all-versus-all sequence similarity comparison using a previously described methodology [24][25] ( S5 Fig ) . Most of them appear to be related to previously described viruses preying on the major components of the prokaryotic Mediterranean community such as Cyanobacteria , SAR11 , SAR116 or Actinobacteria [21 , 36] . However , we found novel phages for which the assignment of the host was not feasible ( Table 1 ) . This large collection of metagenomes and viral contigs provide a different method to obtain complete phage genomes from a natural habitat complementary to viromes in order to advance in the knowledge of the structure and diversity of the viral communities as have been previously described in [17] . In a similar way as we did for the individual reads , we compared the abundance of the VCs between the different filter fractions and sample locations . We took into consideration only those VCs recruiting more than 10 RPKG ( Reads per Kilobase of genome per Gigabase of metagenome ) of coverage with a similarity >99% in the metagenomic samples to produce the PcoA of S6 Fig . The results showed an even more marked separation than using only individual reads . Both samples belonging to the viral fraction ( <0 . 22 μm ) were grouped together but separated from the rest ( S6 Fig ) . The same happened for the particulate fraction samples ( 5 . 0–20 . 0 μm ) . However , we found four groups for the free-living prokaryotic communities ( 0 . 22–5 . 0 μm ) ( i ) samples belonging to the UP , ( ii ) LP and DEEP , ( iii ) DCM samples form the Eastern Mediterranean Sea and ( iv ) winter MIX samples ( S6 Fig ) . It should be mentioned that the number of contigs obtained is not the same in all the samples ( S1A Fig ) and in some cases , as in the deep samples , contigs do not reach the minimum value required ( 10 RPKG ) and , as a consequence , they cluster together . However , the same pattern of Fig 1 is repeated and we can see a clear differentiation depending on the filter size fractions . Analysis of the relative abundance of the complete phage genomes in both , cellular ( 0 . 22 μm ) and viral fractions ( <0 . 2 μm ) from the Tara Oceans samples , revealed that half of them did not recruit in any station independently of the filter fraction ( S7 Fig ) . Most of them came from deep metagenomes ( Med-Ae2-600mDeep , Med-Io17-3500mDeep and Med-OCT2015-2000m ) and probably are specific from bathypelagic waters . For this reason , we analysed the abundance also in deep-sea viral metagenomes ( POV and Malaspina ) but the results did not show any difference , suggesting not only that they are specific of bathypelagic waters but also endemic of the Mediterranean Sea . Another possibility would be that the genomic diversity in bathypelagic waters is higher than in photic regions . Furthermore , recruitment showed the dominance of cyanophages in metagenomic samples ( cellular fraction ) , consistent with previously observations [26] . However , it is important to point out that phages , mainly cyanophages , often carry auxiliary metabolic genes ( AMGs ) in order to modify host metabolism during infection . We have noted that the presence of several versions of the same gene coming from bacteria and phages ( i . e photosystem II core reaction centre protein D1; PsbA ) sometimes breaks the assembly and also overestimate the value of the recruitment but only at values below 90% identity ( we have used only 95 and 99% to assess recruitment ) . With the large collection of marine metagenomes and viromes available , it is possible to evaluate not only the most abundant and widespread VCs but also their distribution in the water column . Furthermore , datasets obtained from different years from the same location can be used to detect patterns of temporal variation and evolution . We have used recruitment of metagenomic reads to elucidate possible patterns of distribution of these phages in nature . The majority of the global marine viral metagenomic studies [15] are focused on surface samples considering the photic zone as a homogeneous compartment and taking into account only the differences between the photic and aphotic zone . To investigate the vertical distribution of the VCs throughout the water column , we used recruitment of metagenomic reads from a fine-scale metagenomics profile ( every 15m ) in a stratified and mature ( early autumn ) Western Mediterranean water column [36] . Based on the vertical distribution , phages can be categorized into two types: eurybathic ( broad depth distribution ) and stenobathic ( restricted to narrow depth range ) . We took into consideration only those VCs recruiting more than 10 RPKG of coverage with a similarity >95% in the metagenomic profile . We found 227 out of 927 VCs abundant in at least one of the metagenomes , although none of them were detected in deeper waters ( 1 , 000 and 2 , 000m ) . It is remarkable that a large number of the VCs ( ca . 89% ) appear to be found exclusively in one single specific depth or two contiguous depth metagenomes ( S11 Fig ) . Moreover , this distribution was more marked in the UP and DCM where typically genomes appeared at one or the other while ca . 50% of the VCs found beyond the DCM were present in both depths ( 75 and 90m ) ( S11 Fig ) . This stenobathic character is consistent with the narrow depth distributions found in the analysis of the prokaryotic fraction in these metagenomes [36] and suggest that most of the phages have a specialized host range ( not generalist ) . Only two singletons ( MedDCM-SEP2013-LF-C8 and Med-OCT2015-30m-C1728 ) that appear related to the pelagiphage HTVC008M recruited in all the photic metagenomes and could be considered eurybathic phages . Regarding the remaining 11% of the VCs that recruit in more than one of the metagenomes they did not show any decrease with depth , indicating that there is no vertical viral transport in sinking particles as was previously hypothesized [57] . To assess the abundance and distribution of the novel VCs we performed fragment recruitment analysis by comparing each VC to that of numerous metagenomes from Tara Oceans datasets ( cellular and viral fraction ) . We considered only those VCs recruiting more than 10 RPKG and present in at least two stations . Besides , we have used two very restrictive nucleotide identity thresholds , 95 and 99% . At 99% of identity , VCs were found mainly at their habitat of origin ( Mediterranean Sea ) in both fractions , reasserting the endemicity at this level of similarity of these genomes ( Fig 5 and S12 Fig ) . We found some exceptions , a peak in the metagenomic sample from the station TARA_004 a North Atlantic Ocean station , but from the region next to the Gibraltar Strait ( the connection between Mediterranean Sea and Atlantic Ocean ) and also two samples TARA_132 and 133 located in the North Pacific Ocean . The prevalence of these VCs might reflect similar conditions since these stations were located at similar latitudes than the Mediterranean Sea . However , we did not find the same abundance in similar regions in the Atlantic Ocean , probably due to the stratification of the water column that is permanent in these two Pacific samples ( like in the Mediterranean during the time of sampling ) while the Atlantic samples were collected during the mixed period . On the other hand , when identity was shifted to 95% , results indicated that these viruses are globally widespread with the exceptions of polar latitudes and mesopelagic samples ( from 280 to 800m ) in both fractions ( Fig 5 and S12 Fig ) . We found that 514 of the 927 VCs ( 55 . 4% ) recruited in more than two metagenomic or viromic datasets . In total , 208 were abundant in both fractions , 190 were reported only in the cellular fraction and 116 in the viral fraction . While pelagiphages were the most widely distributed group in the viral fraction , cyanophages were dominant in the cellular fraction ( as found before [26] ) . The VC MedWinter-DEC2013-20m-C2965 classified as a pelagiphage was the one found in the largest numbers of Tara stations ( widespread ) while the highest absolute recruitment value found for a contig was that of the CGR MedWinter-DEC2013-20m-C17 , described as a new cyanophage , which recruited more than 480 RPKG in TARA_007 station near its isolation place . On the other hand , contigs recovered from deep metagenomes did not recruit in any Tara metagenome or virome ( most of the datasets were collected in the photic zone ) . Using the same parameters , we have analysed the abundance and distribution of these novel VCs also in the deep-sea viral metagenomes . While at 99% of identity only a couple of VCs recruited in all the Malaspina and POV stations when we moved to the population cut-off ( 95% ) , the numbers did not change excessively as in the previous case with the Tara dataset . Twelve VCs were found in Malaspina and only four in POV , most of them recovered from the Med-Io17-3500mDeep metagenome emphasizing their truly bathypelagic nature . The low recruitment in the deep viromes in comparison with the ones of the photic zone can be due to the special conditions of the deep Mediterranean Sea which is much warmer ( >13°C ) and contain lower concentrations of inorganic nutrients N and P than waters of similar depth in open oceans . This special situation might allow the persistence of specific microbial communities adapted to aphotic regions [31] and hence of the viruses associated with them . These data suggest that , at least in the Mediterranean Sea , there is a clear evidence of a local viral distribution and diversity ( more marked in deep waters ) .
Eleven seawater samples were collected at different depths , filter pore size and season ( stratified or mixed ) during consecutive years in the Western Mediterranean . Metadata of the samples are summarized in S1A and S1B Fig . Samples from 2012 to 2015 ( MedDCM-JUL2012 , MedDCM-SEP2013 , MedDCM-SEP2013-LF , MedWinter-DEC2013-20m , Med-SEP2014-15m , Med-SEP2014-30m , MedDCM-SEP2014 , MedWinter-JAN2015-20m , MedWinter-JAN2015-20m-LF , MedWinter-JAN2015-20m , MedWinter-JAN2015-20m-LF , MedDCM-SEP2015_HS ) [34 , 35 , 38] [36] were recovered at 20 nautical miles off the coast of Alicante ( 38 . 06851°N , 0 . 231994°W; bottom depth of 200 m ) . Additionally , in 2015 another nine samples ( Med-OCT2015-15m , Med-OCT2015-30m , Med-OCT2015-45m , Med-OCT2015-60m , Med-OCT2015-75m , Med-OCT2015-90m , Med-OCT2015-1000m and Med-OCT2015-2000m ) [36] were collected at approximately 60 nautical miles off the coast of Alicante ( 37 . 35361°N , 0 . 286194°W ) . Five more samples coming from different locations in the Eastern Mediterranean were used [25] . Med-Io16-70mDCM , Med-Io7-77mDCM and Med-Io17-3500mDeep recovered from the Ionian Sea , at depths of 70 , 77 and 3500 meters , respectively . Finally , two samples collected from the Aegean Sea , at 75m ( Med-Ae1-75mDCM ) and at 600m deep ( Med-Ae2-600mDeep ) were also included in the analysis [25 , 34] . All seawater samples were sequentially filtered on board through 20 μm nylon mesh and 5 and 0 . 22 μm pore size polycarbonate filters ( Millipore ) . All filters were immediately frozen on dry ice and stored at -80°C until processing . DNA extraction was performed from 0 . 22 and 5 μm filters as previously described [58] . Metagenomes collected on September and October 2015 were sequenced using Illumina Hiseq-4000 ( 150bp , paired-end read ) ( Macrogen , Republic of Korea ) . The remaining metagenomes were sequenced using Illumina Hiseq-2000 ( 100bp , paired-end read ) ( BGI , Hong Kong ) obtaining sequence data in a range between 15 and 20 Gb . Individual metagenomes were assembled using IDBA-UD [59] . The resulting genes on the assembled contigs were predicted using Prodigal [60] . tRNA and rRNA genes were predicted using tRNAscan-SE [61] , ssu-align [62] and meta-rna [63] . Predicted protein sequences were compared against NCBI NR , COG [64] and TIGRFAM [65] databases using USEARCH6 [66] for taxonomic and functional annotation . GC content was calculated using the GeeCee program from the EMBOSS package [67] . Proteins were clustered using CD-HIT [68] at 60% sequence identity and > 80% alignment on the shorter sequence . One of the viromes ( MedDCM-Vir ) was obtained from the DCM of the Mediterranean Sea ( 65 m deep ) on August 29th , 2011 . DNA was amplified by MDA and sequenced by Illumina to provide nearly 18 Gb of sequence data as was described in [24] . The other viromic sample ( MetaVir-2013 ) was collected from the Mediterranean DCM at 55m ( 38 . 06851°N , 0 . 231994°W; bottom depth of 200 m ) on 6 September 2013 . Sample was processed in the same way as the other virome MedDCM-Vir [24] . However , the amount of DNA obtained was sufficient to sequence and it was not necessary to use any amplification treatment . Phages were concentrated using tangential flow filtration ( TFF ) with a 30 kD polyethersulfone membrane from Vivaflow ( VF20P2 ) . The resulting phage concentrate was ultracentrifuged ( Optima XL 1000K Ultracentrifuge , Beckman ) for 1 h at 4°C using a Type 70 Ti rotor ( Beckman ) at 30 , 000 rpm ( 92 , 600 g ) . The pellet was treated with 2 . 5 units DNase I at 37°C for 1 hr , and 70°C for 10 min to remove bacterial DNA . DNA was sequenced using Illumina Hiseq-2000 ( 100bp , paired-end read ) ( BGI , Hong Kong ) . In order to confirm the viral origin of the contigs we performed a manual inspection based on the resemblance to known phages similar to methods that have been previously described [24 , 25] . Complete genomes were identified searching for overlapping sequences in the 3′ and 5′ region ( at least 30bp ) . These contigs were clustered using an all-versus-all BLASTN comparison with a cut-off of 90% sequence identity and 20% coverage . We have used different host prediction approaches to identify the putative host of the viral contigs . These methods have been previously described [24] and include tRNA matches , CRISPR spacers , presence of AMGs , all-versus-all comparison and terminase phylogeny . Furthermore , all the contigs were annotated and assigned if a majority of genes gave best BLAST hits against the NR database ( >75% nucleotide identity and >50% coverage ) to the same phage . Subsets of 20 million reads ≥ 50bp ( where applicable ) were taxonomically classified against the NR database using DIAMOND [69] with a minimum of 50% identity and 50% alignment . The resulting alignment was later analyzed with MEGAN6 Community Edition [70] , and both Unweighted Pair Group Method with Arithmetic Mean ( UPGMA ) taxonomic tree and canonical correspondence analysis ( CCA ) were inferred with the cluster analysis option and a Bray-Curtis ecological distance matrix . The abundance and distribution of the VCs obtained in this study were performed using recruitment against the complete dataset of Tara Oceans metagenomes [71] and viromes [15] , metagenomes from this study ( S1 Fig and Table 1 ) and also deep-sea viral metagenomes from the Malaspina expedition [45] and POV dataset [16] . Metagenomic recruitment of the reads were compared using BLASTN [72] and hits obtained were used to compute the RPKG ( reads recruited per Kb of genome per Gb of metagenome ) values that provide a normalized number comparable across various metagenomes . Complete phage genomes were compared to several well-classified Caudovirales ( Podoviridae , Myoviridae and Siphoviridae ) reference phages downloaded from the NCBI , in addition to known marine phage genomes and previously published marine phages ( APXXX and KTXXX ) [24 , 25] . Dice coefficient between genomes was computed from summed calculated TBLASTX scores as previously reported [24] . This metric was transformed to a dissimilarity metric and values were log10 converted to reduce the distance between extreme values . A neighbour joining tree was constructed from the complete distance matrix using the phangorn package [73] in R and formatted in Dendroscope [74] . SNPs between phage genomes were identified using nucmer program in the MUMmer3+ package [75] .
|
These data provided a glimpse of the genetic diversity and variability of viral sequences without introducing the amplification biases produced when studying viromes . Metagenomes contain abundant viral material due to cells retrieved while undergoing viral lysis or as temperate viruses inserted in the chromosome . Using very stringent criteria , we have managed to assemble large viral genomes from Mediterranean metagenomes . This large-scale study using direct assembly from metagenomes , i . e . from the cellular fraction , clearly shows that metagenomes are an important tool to study environmental viral communities containing complementary information , which is missing in viromes , that should be taken into consideration when studying viral genetic diversity . Thus , in this study we have described more than 1 , 300 viral genomic fragments larger than 10Kb , of which 36 represented complete viral genomes , including the first deep sea virophage , one novel Marine Group II euryarchaeota virus ( magrovirus ) and others infecting Cyanobacteria , SAR11 or SAR116 . All these new viral contigs were obtained from a collection of 24 metagenomes representing a broad range of geographical and ecological biomes from the Mediterranean Sea .
|
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2017
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Genome diversity of marine phages recovered from Mediterranean metagenomes: Size matters
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Cells in developing organisms are subjected to particular mechanical forces that shape tissues and instruct cell fate decisions . How these forces are sensed and transmitted at the molecular level is therefore an important question , one that has mainly been investigated in cultured cells in vitro . Here , we elucidate how mechanical forces are transmitted in an intact organism . We studied Drosophila muscle attachment sites , which experience high mechanical forces during development and require integrin-mediated adhesion for stable attachment to tendons . Therefore , we quantified molecular forces across the essential integrin-binding protein Talin , which links integrin to the actin cytoskeleton . Generating flies expressing 3 Förster resonance energy transfer ( FRET ) -based Talin tension sensors reporting different force levels between 1 and 11 piconewton ( pN ) enabled us to quantify physiologically relevant molecular forces . By measuring primary Drosophila muscle cells , we demonstrate that Drosophila Talin experiences mechanical forces in cell culture that are similar to those previously reported for Talin in mammalian cell lines . However , in vivo force measurements at developing flight muscle attachment sites revealed that average forces across Talin are comparatively low and decrease even further while attachments mature and tissue-level tension remains high . Concomitantly , the Talin concentration at attachment sites increases 5-fold as quantified by fluorescence correlation spectroscopy ( FCS ) , suggesting that only a small proportion of Talin molecules are mechanically engaged at any given time . Reducing Talin levels at late stages of muscle development results in muscle–tendon rupture in the adult fly , likely as a result of active muscle contractions . We therefore propose that a large pool of adhesion molecules is required to share high tissue forces . As a result , less than 15% of the molecules experience detectable forces at developing muscle attachment sites at the same time . Our findings define an important new concept of how cells can adapt to changes in tissue mechanics to prevent mechanical failure in vivo .
The shape of multicellular organisms critically depends on the presence of mechanical forces during development [1 , 2] . Forces not only generate form and flows within tissues [3 , 4] but can also control cell fate decisions [5 , 6] and trigger mitosis [7] . There are various ways to quantify forces at the cellular or tissue level [8 , 9]; however , mechanical forces experienced by proteins in cells have only recently become quantifiable with the development of Förster resonance energy transfer ( FRET ) -based molecular tension sensors [10] . These sensors contain a donor and an acceptor fluorophore connected by a mechanosensitive linker peptide , which reversibly unfolds and extends when experiencing mechanical forces . As a result , such sensors report forces as a decrease in FRET efficiency caused by an increase in distance between the fluorophores . Since previous studies analyzed molecular forces using in vitro cell culture systems [11–17] and insights from in vivo experiments are still limited [18–21] , it remains largely open how mechanical loads are processed at the molecular level in tissues of living organisms . Integrins are a major and highly conserved force-bearing protein family . They connect the actomyosin cytoskeleton to the extracellular matrix and are essential for numerous mechanically regulated processes in vivo or in vitro [22 , 23] . However , in vivo it is particularly unclear how integrin-based structures are mechanically loaded because forces have so far only been analyzed in focal adhesions , which are typically not found in soft tissues [11–13 , 17] . Therefore , we chose to investigate Drosophila muscle attachment sites in vivo , which experience high mechanical forces during development [24] and depend on integrin-based attachment of muscle fibers to tendon cells [22 , 25] . For the molecular force measurements , we selected the integrin activator and mechanotransducer Talin , which is essential for all integrin-mediated functions and binds with its globular head domain to the tail of β-integrin and with its rod domain to actin filaments [26 , 27] . Thus , Talin is in the perfect position to sense mechanical forces across integrin-dependent adhesive structures . In contrast to measurements performed previously in vitro [12] , we find that less than 15% of the Talin molecules experience significant forces at developing muscle attachments in vivo , suggesting that high tissue forces are sustained by recruiting a large excess of Talin molecules to muscle attachments . Reducing the Talin levels leads to rupture of muscle attachments in response to high forces during adult muscle contractions . This demonstrates the significance of high Talin levels for the robustness of muscle attachments under peak mechanical load .
To enable quantitative force measurements , we generated various Drosophila Talin tension sensor and control flies by modifying the endogenous talin ( rhea ) gene using a two-step strategy based on clustered regularly interspaced short palindromic repeats ( CRISPR ) /CRISPR-associated protein 9 ( Cas9 ) genome engineering and ϕC31-mediated cassette exchange ( Fig 1A , S1 Fig ) [28] . This strategy enabled us to generate an entire set of Talin tension sensor fly lines with yellow fluorescent protein for energy transfer ( YPet ) and mCherry FRET pairs and 3 different mechanosensitive linker peptides [11 , 13] , Flagelliform ( F40 ) , Villin headpiece peptide ( HP ) , and HP’s stable variant ( HPst ) , reporting forces of 1–6 piconewton ( pN ) , 6–8 pN , and 9–11 pN , respectively ( Fig 1B ) . The sensor modules were inserted both internally between the Talin head and rod domains ( F40-TS , TS , stTS ) at the analogous position used in mammalian Talin to report forces in vitro [11 , 17] and C-terminally as a zero-force control ( C-F40-TS , C-TS , C-stTS ) . Furthermore , the individual fluorescent proteins were inserted at both positions as controls ( I-YPet , I-mCh , C-YPet , C-mCh ) . All stocks are homozygous viable and fertile and do not display any overt phenotype indicating that the Talin tension sensor proteins are functional . To assess the functionality of Talin-TS more rigorously , we first analyzed Talin-TS localization in adult hemithoraxes and found that Talin-TS localizes to myofibril tips as expected ( Fig 2A–2D ) . Second , we performed western blot analysis and found the expected band shifts for tension sensor module incorporation into Talin protein isoforms ( Fig 2E ) . Third , we quantified sarcomere length in flight muscles and found the expected length of 3 . 2 μm in wild-type ( WT ) [29] and talin-TS flies ( Fig 2F–2H ) . Fourth , we tested flight ability [30] and found that neither the insertion of the sensor module nor the individual fluorescent proteins into the internal position nor the insertion of the sensor module at the C-terminus causes flight defects ( Fig 2I ) . Fifth , we confirmed that Talin-TS ( or Talin-I-YPet ) is expressed correctly at all developmental stages ( embryo , larva , and pupa ) and is detected most prominently at muscle attachment sites as previously reported for endogenous Talin ( Fig 2J–2O ) [31] . Finally , we assessed the molecular dynamics of Talin-TS at flight muscle attachments using fluorescence recovery after photobleaching ( FRAP ) . We compared the internal tension sensor to Talin-C-YPet , which is tagged at a functionally verified position [32] , and found that internal tagging of Talin does not alter its molecular dynamics . Both the mobile fraction as well as the recovery half time are indistinguishable from C-terminally tagged Talin ( Fig 2P–2S ) . Together , these data demonstrate that the tension sensor module is properly incorporated into Talin and the resulting protein is functional . Thus , Talin-TS is suitable for the quantification of mechanical tension across Talin in any tissue and at any developmental stage of Drosophila in vivo . To ensure that our approach is comparable to previous Talin force measurements in cultured mammalian cells , we established muscle fiber cultures by incubating primary myoblasts in vitro for 5 to 7 d [33 , 34] . Isolated myoblasts from talin-I-YPet embryos differentiated into striated , often multinucleated muscle fibers and efficiently adhered to the underlying plastic substrate ( Fig 3A and 3B ) . In these cells , Talin-I-YPet localizes to adhesions at the fiber tips and at myofibril ends as well as to costameres , which connect myofibrils at the sarcomeric Z-discs to the cell membrane [35] . Primary muscle fibers generated from talin-I-YPet , talin-TS , and talin-C-TS embryos display similar morphologies ( Fig 3C–3E ) and contract spontaneously ( S1 Movie ) . Adhesions at the fiber tips do not move during these contractions , whereas costameres are mobile and thus are not fixed to the plastic substrate ( Fig 3F ) . For establishing force measurements using these primary fiber cultures , we performed fluorescence lifetime imaging microscopy ( FLIM ) to determine the FRET efficiency of the Talin tension sensor containing the HP-sensor module ( TS ) compared to the zero-force control ( C-TS ) . We created distinct masks for Talin FRET signals either in the entire fiber or specifically in cell-substrate adhesions at the fiber tips or in costameres along myofibrils ( Fig 3G–3J ) . Consistent with previous Talin force measurements in cultured fibroblasts [11 , 17] , we observed a reduction in FRET efficiency of TS compared to the control C-TS within the entire fiber , indicating that Talin indeed experiences mechanical forces in these adherent , primary muscle fibers ( Fig 3K ) . As expected , we find higher average forces across Talin at muscle-substrate adhesions compared to the rest of the cell . In costameres , which are not fixed to the plastic substrate , the FRET efficiency of TS is indistinguishable from the control , indicating that forces across Talin at costameres are lower and do not exceed 6 to 8 pN ( Fig 3K ) . Together , these data demonstrate that the Drosophila Talin-TS reports similar Talin forces at adhesions of cultured muscle fibers as were previously described for Talin in focal adhesions of mammalian fibroblasts [11 , 12 , 17] . To quantify forces across Talin in vivo , we chose the developing muscle–tendon attachments of the flight muscles as a model system , which critically depend on integrin and Talin function [24 , 31] . At 20 hours after puparium formation ( h APF ) , the developing myotubes have initiated contact with the tendon epithelium , and immature muscle attachment sites are formed ( Fig 4A ) . While they mature , the myotubes compact and the tendon epithelium forms long cellular extensions . By 30 h APF , the myotubes have reached their maximally compacted stage ( Fig 4A ) and have initiated myofibrillogenesis . Thereafter , the muscles elongate and grow to fill the entire thorax by the end of the pupal stage [29] . Previous studies using laser-induced microlesions in developing tendons had shown that increasing mechanical tension is built up in the muscle–tendon tissue from 18 h to 22 h APF and that this tension is required for ordered myofibrillogenesis [24 , 36] . However , tissue tension at the maximally compacted stage of the muscle fibers at 30 h APF had not been analyzed yet . Therefore , we cut the tendon cells at 20 h and 30 h APF and performed time-lapse imaging to quantify the tendon tissue recoil . As a proxy for tissue tension , we calculated the initial recoil velocity from the first 2 frames after the cut ( 300 ms ) and found that it remains high at 30 h APF ( Fig 4B–4G , S2 Movie and S3 Movie ) . To ensure that the high tissue tension is also present in the muscle fibers , we cut the muscle at 20 h and 30 h APF ( Fig 4A ) . Cutting the muscle fibers in a single focal plane is not sufficient to cut the entire fiber in two . However , laser lesions in the muscle induce muscle contractions at 30 h APF but not at 20 h APF ( S2 Fig , S4 Movie and S5 Movie ) . This demonstrates that the immature myofibrils present at 30 h APF are contractile and are stably connected to muscle attachments . A similar observation was made before in Drosophila abdominal muscles , in which laser-induced lesions cause a Ca2+ pulse that triggers contraction of the immature myofibrils [37] . To sever the entire muscle fibers , we cut repeatedly in a 10-μm–thick z-stack and tracked the recoil of the muscle attachments at 20 h and 30 h APF ( Fig 4H–4L , S6 Movie and S7 Movie ) . Due to the z-stack acquisition , our time resolution was limited to 5 s , and therefore we could not determine the initial recoil velocity precisely . Instead , we quantified the average recoil velocity in the first 5 s and found that it increases from 20 h to 30 h APF , suggesting an overall increase in muscle fiber tension between 20 h and 30 h APF ( Fig 4M ) . In conclusion , tissue tension in the muscle–tendon system remains high and possibly increases further from 20 h to 30 h APF , both in the tendon and the muscle tissue . After establishing that tissue forces build up in the muscle–tendon system and remain high until 30 h APF , we measured Talin forces between 18 h and 30 h APF in living pupae at the anterior muscle attachment sites of the dorsal-longitudinal flight muscles using the HP-sensor module ( Fig 5A and 5B and workflow in S3 Fig ) . For calculating the FRET efficiency , we determined the fluorescence lifetime of only the donor in flies expressing YPet at the internal position of Talin ( S4A Fig ) . In addition , we excluded the possibility that FRET between neighbouring molecules ( intermolecular FRET ) affects our measurements throughout the entire time course ( Fig 5C ) and confirmed that our lifetime measurements are independent of signal intensity ( S4B Fig ) . We noted that the FRET efficiency of the zero-force control sensor slightly increases over the time course , possibly because the increasing crowding at the attachments restricts the conformational freedom of the sensor and thus may favor FRET ( Fig 5D ) . Therefore , we measured the FRET efficiency of the control sensor in addition to the tension sensor at all developmental time points . In this way , we detected a significant drop in FRET efficiency for Talin-TS compared to the control Talin-C-TS at 18 to 28 h APF ( Fig 5D ) . The FRET efficiency reduction at muscle attachment sites was significantly smaller compared to the in vitro measurements of cultured muscle fibers ( Fig 3K ) or of cultured mammalian fibroblasts [11] . At 30 h APF , no difference in FRET efficiencies was detected , suggesting that there is little or no tension across Talin at this time point . Together , these data suggest that only a small percentage of Talin molecules at muscle attachments experience forces above 6 pN at 18 to 28 h APF . The remaining molecules could either bear no force or forces below 6 pN that cannot be detected by the HP-sensor module . Contrary to our expectation , the average force across Talin decreases during muscle compaction while tissue tension builds up and myofibrils are assembled . To substantiate these findings , we compared flies carrying the HP-based Talin sensor ( 6–8 pN ) to those with the stable variant HPst ( 9–11 pN ) , which only differs in 2 point mutations . We found similar and highly reproducible differences in FRET efficiency ( Fig 5E , S4C Fig ) indicating that , at 20 to 24 h APF , some Talin molecules even experience forces of ≥10 pN at muscle attachment sites . Comparison of TS to its stable variant ( stTS ) revealed a significant difference in FRET efficiency at 20 h APF , while the respective zero-force controls were indistinguishable ( Fig 5E ) . This demonstrates that a proportion of the mechanically engaged Talin molecules experience a range of forces between 7 and 10 pN at muscle–tendon attachments in vivo , further emphasizing that the observed differences are force specific . To test whether the remaining Talin molecules experience forces that are too low to be detected by the HP or HPst sensor modules , we generated flies with the F40 sensor module , which is sensitive to forces of 1 to 6 pN [13] . Again , we quantified a decrease in FRET efficiency relative to the control at 20 h and 24 h APF , but FRET efficiency differences remained small , and no change was observed at 30 h APF ( Fig 5F ) . Thus , a large proportion of the Talin molecules at muscle attachment sites are not exposed to detectable mechanical forces during development . To quantify the proportion of mechanically engaged Talin molecules at 20 h and 24 h APF , we applied biexponential fitting to our FLIM data and calculated the ratio of open versus closed sensor ( Fig 5G , see Methods for details ) . This analysis revealed that only 13 . 2% and 9 . 6% of all Talin molecules are mechanically engaged at 20 h and 24 h APF , which contrasts in vitro measurements of focal adhesions that are characterized by a Talin engagement ratio of about 70% [12] . Each mechanically engaged Talin molecule needs to be bound to an integrin , therefore we tested whether the integrin levels at muscle attachment sites may be limiting the amount of force-bearing Talin molecules . However , integrins and Talin are present at comparable levels at muscle attachment sites at 20 h and 30 h APF ( S5 Fig ) . Thus , it is unlikely that a lack of integrins is the primary reason for the surprisingly small proportion of Talin molecules experiencing detectable forces . As Talin is thought to play an important mechanical role during tissue formation , we wanted to test whether such a small proportion of mechanically engaged Talin molecules in vivo could still contribute a significant amount of tissue-level tension . We therefore quantified the absolute amount of Talin molecules present at muscle attachment sites by combining in vivo fluorescence correlation spectroscopy ( FCS ) with quantitative confocal imaging ( see workflow in S6A–S6D Fig ) . From FCS measurements in the muscle interior , we calculated the counts per particle ( CPP ) value , i . e . the molecular brightness of a single Talin-I-YPet particle in each pupa . Because such a particle may correspond to a Talin monomer or dimer , we compared the Talin-I-YPet brightness to the brightness of free monomeric YPet expressed in flight muscles and found no significant difference ( Fig 6A ) . We conclude that Talin is mostly monomeric in the muscle interior . Next , we calculated the Talin concentration at muscle attachment sites by calibrating confocal images using the molecular brightness ( CPP ) information from the FCS measurements . Using a dilution series of Atto488 , we ascertained that the fluorescence intensity increases linearly with the concentration over multiple orders of magnitude in our confocal images ( S6E Fig ) . The resulting images with pixel-by-pixel Talin concentration values ( Fig 6B ) indicate an average concentration at the muscle attachment of 5 . 9 μM ( 20 h ) , 10 . 9 μM ( 24 h ) , and 30 . 9 μM ( 30 h ) ( Fig 6C ) . Thus , the local concentration of Talin molecules increases approximately 2-fold from 20 h to 24 h APF and 5-fold to 30 h APF , indicating that Talin may contribute to the high tissue stress by its strong recruitment to maturing muscle attachment sites . To confirm this hypothesis , we estimated the density of Talin molecules on the membrane by dividing the number of Talin molecules per pixel by the estimated membrane area in the confocal volume ( Fig 6D , see Methods for details ) . This resulted in about 400 , 700 , and 2 , 300 Talin molecules per μm2 at 20 , 24 , and 30 h APF , respectively , which corresponds to 20 nm × 20 nm space per molecule at 30 h APF . This space can easily accommodate the size of a Talin head domain ( about 4 nm × 10 nm ) [38] , and the estimated density is comparable to previous studies of integrins in focal adhesions [39] . By combining our force quantifications with the estimated Talin density at muscle attachment sites , we calculated the Talin-mediated tissue stress to be in the order of 0 . 4 to 0 . 5 kPa at 20 h to 24 h APF ( see Methods for details ) . These values are remarkably close to a previously published stress estimate of 0 . 16 kPa determined by traction force microscopy in focal adhesions of cultured cells [40] . Thus , Talin does contribute a significant amount of tissue stress despite the small proportion of mechanically engaged molecules ( Fig 6D ) . To investigate the physiological relevance of the high Talin levels at muscle attachments , we aimed to reduce the Talin concentration . The simplest way would be to examine heterozygous animals with only 1 functional Talin copy . However , crossing talin-I-YPet to a talin null allele resulted only in a minor reduction of Talin levels ( to about 80% of the WT level ) at 20 h and 30 h APF muscle attachments ( S7A–S7E Fig ) . Consequently , we did not detect any significant differences in the molecular forces across Talin in these heterozygous animals ( S7F Fig ) . Hence , we applied RNA interference ( RNAi ) to reduce Talin levels . As knockdown of Talin with a general muscle GAL4 driver—such as Mef2-GAL4—is embryonic lethal [30] , we used the late flight-muscle–specific Act88F-GAL4 driver [41] . Act88F-GAL4–driven talin RNAi ( talin-IR ) resulted in a reduction of Talin levels to about 50% at flight muscle attachments at 90 h APF , which is shortly before the adult flies eclose ( Fig 7A–7E ) . Apart from the reduced Talin levels , the muscle attachments look normal , and all flight muscles remain attached at 90 h APF . As flight muscles at 90 h APF display a wavy shape and their cuticle has not hardened yet , we instead performed force measurements in adult flies , which have straightened flight muscles and are ready to fly . Talin force measurements in adult flight muscle attachments revealed a significant reduction in FRET efficiency for Talin-TS compared to the zero-force control . This indicates that a proportion of the Talin molecules indeed experience forces above 6 to 8 pN in adults under resting nonflying conditions ( Fig 7F , S8 Fig ) and the additional Talin could buffer peak muscle forces during flight . To test this hypothesis , we investigated whether the reduction of Talin levels by RNAi has consequences during adult stages when flies actively fly and thus produce very high forces on muscle attachments . Indeed , talin knockdown flies display a muscle detachment phenotype , whereas in control flies , all muscles remain attached ( Fig 7G–7J ) . In conclusion , high Talin levels are required for stable muscle attachments that withstand the high forces generated by active muscle contractions in adult animals .
Our findings highlight the importance of investigating tissues in their natural mechanical environment in vivo . While the forces per Talin molecule and the tissue stress in vivo are in the same order of magnitude as in previous in vitro studies of focal adhesions [11 , 12 , 40] , a surprisingly small proportion of Talin molecules ( <15% ) experience detectable forces during muscle development in vivo . An obvious question arising , therefore , is: what are the other Talin molecules doing at muscle attachment sites , for which we cannot detect significant mechanical forces ? Likely , the pool of mechanically engaged Talin molecules exchanges dynamically with the other Talin molecules present at the muscle attachment site . Talin molecules may even remain anchored to integrin and actin , without actomyosin pulling on them continuously . Such a dynamic system would allow the rapid adjustment to changes in tissue forces and thereby prevent rupture of the muscle–tendon attachment upon a sudden increase in tissue stress . In line with this hypothesis , we demonstrated that a high Talin level is particularly important when active muscle contractions result in high forces on the attachments . Talin was just recently proposed to act as a “shock absorber” based on cell culture experiments [26] . In focal adhesions of cultured cells , the length of Talin can fluctuate dynamically on the time scale of seconds , with Talin being transiently extended from 50 nm up to 350 nm [42] . This can be explained by reversible folding and unfolding of some of the 13 helical bundles in the Talin rod upon actomyosin-dependent stretching of Talin . The hypothesis that Talin acts as a shock absorber is consistent with our finding that only some molecules experience forces at the same time under baseline conditions , whereas additional molecules may dampen a force increase . A similar force-induced reversible unfolding mechanism was recently proposed for particular immunoglobulin domains in the giant sarcomeric protein titin during muscle contraction cycles at estimated forces of 6 to 8 pN [43] . Thus , it is conceivable that muscle attachments prepare for peak forces during muscle contraction cycles by the recruitment of large amounts of Talin during development . In addition , the unfolding of the Talin rod domains makes binding sites accessible , leading to the recruitment of vinculin [44] . Magnetic tweezer-based in vitro studies suggested that the rod domain R3 unfolds at about 5 pN [45] and the remaining rod domains unfold when forces larger than 8 pN are applied [46] . Our in vivo force measurements are consistent with those observations suggesting that low pN forces change the Talin structure and make vinculin binding sites accessible , thereby allowing a mechanotransduction response . Previous estimates of forces transmitted by integrins based on studies of focal adhesions in vitro cover a wide range of forces . Studies using extracellular sensors with synthetic integrin ligands ( that report forces based on double-stranded DNA rupture ) suggest that integrins can experience very high forces in cells plated on glass ( more than 54 pN ) [47 , 48] . However , other data generated with FRET-based extracellular sensors suggest that about 70% of the integrins in focal adhesions experience low forces ( less than 3 pN ) [49] . These in vitro systems have the advantage that they are accessible for precise manipulations; however , the artificial mechanical environment may have a strong impact on the amount of force experienced by the individual proteins and the number of molecules that are mechanically engaged . Our study provides , to our knowledge , the first insights into molecular forces acting on integrin-mediated attachments in vivo . Here , we focused on developing muscle attachments in pupae; however , our newly established Talin tension sensor fly lines should enable future force measurements in all integrin-based processes in Drosophila leading to more insights into mechanobiology in vivo . In this study , we found that only a small proportion of Talin molecules ( <15% ) are experiencing forces higher than 6 to 8 pN at developing muscle attachments and thus hypothesize that tissues prevent mechanical failure in vivo with the following mechanism: a large pool of molecules dynamically share the mechanical load , such that a sudden increase in tissue tension can be rapidly buffered by mechanically engaging additional molecules already present at the attachment site . These additional molecules could either be unbound and then rapidly recruited or already bound but not yet under force . Mechanical failure of integrin-mediated attachments in vivo needs to be avoided at all cost , particularly in muscle fibers or cardiomyocytes , to prevent fatal consequences for the animal . Therefore , creating a mechanical buffer system to withstand peak forces is an important concept for the survival of animals .
All fly work was performed at 27°C to be consistent with previously published work , unless otherwise stated . For details on the genome engineering strategy resulting in Talin tension sensor and control stocks generated in this study ( talin-F40-TS , talin-C-F40-TS , talin-TS , talin-C-TS , talin-stTS , talin-C-stTS , talin-I-YPet , talin-C-YPet , talin-I-mCh , and talin-C-mCh ) , see below . Muscles were labelled using Mef2-GAL4 [50] with UAS-mCherry-Gma [51] . To label the tendon and muscle tissue simultaneously , Mef2-GAL4 and stripe-GAL4 [52] were used in combination with UAS-brainbow [53] . For quantifying Talin-GFP levels , a MiMIC GFP-trap line was used [54]; for Integrin-GFP levels , a homozygous viable GFP knockin line was used [55] . The deficiency line rhea79 was used as a talin null allele [31]; to achieve Talin knockdown , Act88F-GAL4 [41] was crossed to UAS-talin-IR ( TF40399 , obtained from the VDRC stock center [56] ) at 25°C . Tension sensor and control stocks were generated by combining CRISPR/Cas9-mediated genome engineering with ϕC31-mediated cassette exchange as described previously [28] . See S1 Fig for a detailed depiction of the two-step strategy . For step 1 , single guide RNAs ( sgRNAs ) were designed with the help of an online tool maintained by the Feng Zhang lab ( http://crispr . mit . edu/ ) [57] and transcribed in vitro . After testing sgRNA cutting efficiency in Cas9-expressing S2-cells [58] , 2 sgRNAs ( 70 ng/μL ) were injected into Act5C-Cas9 , DNAlig4169 embryos together with the dsRed donor vector ( 500 ng/μL ) containing a dsRed eye marker cassette flanked by attP sites and homology arms . Successful homologous recombination events were identified by screening for red fluorescent eyes and verified by PCR and sequencing . “Ends-in” events were excluded . We call the resulting fly lines talin-I-dsRed and talin-C-dsRed . For step 2 , vasa-ϕC31 plasmid ( 200 ng/μL ) was injected together with attB-donor vector ( 150 ng/μL ) . Successful exchange events were identified by screening for the absence of dsRed , and correct orientation of the cassette was verified by PCR . Adult hemithoraxes were dissected and stained similar to as previously described [59] . Specifically , the wings and abdomen were cut off the thorax of adult flies with fine scissors , and the thoraxes were fixed for 15 min in 4% PFA in relaxing solution ( 20 mM sodium phosphate buffer [pH 7 . 0] , 5 mM MgCl2 , 5 mM ATP , 5 mM EGTA , 0 . 3% Trition-X-100 ) . After washing once with PBST ( PBS with 0 . 3% Triton-X-100 ) , the thoraxes were placed on double-sided tape , and the legs were cut off . Next , the thoraxes were cut sagittally with a microtome blade ( dorsal to ventral ) . The thorax halves were placed in PBST , washed once , and blocked in normal goat serum ( 1:30 ) for 30 min at room temperature ( RT ) on a shaker . Primary antibodies ( anti-Talin antibody: 1:500 , 1:1 mixture of E16B and A22A , DSHB ) were incubated overnight at 4°C on a shaker . Hemithoraxes were then washed 3 times 10 min in PBST at RT and stained with secondary antibody ( Alexa488 goat antimouse IgG , 1:500 , Molecular Probes ) and phalloidin ( Rhodamine or Alexa647 conjugate , 1:500 or 1:200 , respectively , Molecular Probes ) in PBST for 2 h at RT in the dark . After washing 3 times with PBST for 5 min , hemithoraxes were mounted in Vectashield containing DAPI with 2 spacer coverslips on each side . YPet signal after fixation was bright enough for imaging without further amplification . At 32 h APF , pupae were freed from the pupal case and dissected in PBS in a silicone dish using insect pins [59] . The head and the sides were cut using fine scissors to remove the ventral half of the pupa . Next , the thorax was cut sagittally , and the thorax halves were cut off the abdomen and placed in fixing solution ( 4% PFA in PBST ) for 15 min . The thorax halves were then stained with phalloidin and DAPI like the adult hemithoraxes but without shaking and were mounted using 1 spacer coverslip . At 90 h APF , pupae were dissected like adults after freeing them from the pupal case ( see above ) . Samples were imaged on a Zeiss LSM 780 scanning confocal microscope with Plan Apochromat objectives ( 10× air , NA 0 . 45 for overview images and 40× oil , NA 1 . 4 for detail images ) . For thick samples , a z-stack was acquired and maximum-projected using the ImageJ variant Fiji [60] . Sarcomere length was quantified as previously described using the Fiji plug-in MyofibrilJ ( https://imagej . net/MyofibrilJ ) [29] . Briefly , an area with straight , horizontal myofibrils is analyzed by Fourier transformation to find the periodicity of the sarcomeres . One area was analyzed for each hemithorax stained with phalloidin and imaged at 40× and zoom 4 . Western blotting was performed according to standard procedures . Specifically , 15 flies each were homogenized in 100 μL 6× SDS loading buffer ( 250 mM Tris [pH 6 . 8] , 30% glycerol , 1% SDS , 500 mM DTT ) and heated to 95°C for 5 min . The amount of 200 μL water was added , and the equivalent of 0 . 5 fly ( 10 μL ) and 1 fly ( 20 μL ) , respectively , were loaded onto a NuPAGE Novex 3–8% Tris-Acetate Gel . The transfer to the membrane was carried out overnight with 20 V at 4°C . The membrane was blocked ( 5% blotting grade blocker , BioRad ) and then incubated overnight at 4°C with a 1:1 mixture of anti-Talin antibodies E16B and A22A ( 1:1 , 000 in block ) . For detection , HRP antimouse antibody and Immobilon Western Chemiluminescent HRP Substrate ( Millipore ) were used . Male flies ( 1–3 d old , aged at 25°C ) were thrown into a 1 m × 8 cm plexiglass cylinder with 5 marked sections [56] . Flightless flies fall to the bottom of the tube immediately , whereas strong fliers land in the top 2 sections and weak fliers in the third and fourth section . Flight assays were performed in triplicates with 10–20 males each and were repeated twice . Embryos from the cross yw; talin-I-YPet to w; Mef2-GAL4 ; UAS-mCherry-Gma were collected on apple juice agar plates for 24 h and dechorionated in 50% bleach ( 0 . 024% hypochlorite ) for 3 min . Living embryos were mounted in 50% glycerol before imaging . L3 larvae from the same cross were immobilized by immersing them in 60°C water for about 1 s [30] and mounted using a plexiglass slide with a groove and 1 spacer coverslip on each side in 50% glycerol . Five-by-1–tile scan z-stacks were acquired using a 10× objective to image the entire larva . White pre-pupae were collected and aged at 27°C to the desired time point . Before imaging , a window was cut into the pupal case above the thorax , and the pupae were mounted on a custom-made slide with a groove as previously described [61] . Living adults ( 0–2 d after eclosion ) were mounted similarly: after cutting off the legs to prevent the flies from moving too much , up to 5 flies were each placed in a small drop of 50% glycerol ( with 0 . 13% Triton to ensure that the fluid can wet the water-repellent surface of the cuticle ) on a coverslip on their dorsal sides . The wings were then spread out in the drops on the coverslip , and the flies were aligned in a row anterior to posterior . Next , the coverslip was flipped over and placed on a custom-made slide with a groove and 2 spacer coverslips , such that the groove accommodated all 5 flies . In this way , the anterior muscle attachment sites of the dorsal most flight muscles can be imaged directly through the adult cuticle . The flies on each slide were imaged immediately after mounting to minimize the amount of time that they had spent confined to the slide before the measurement . Living 24 h APF talin-C-YPet or talin-TS pupae were imaged at 25°C on a Leica SP8 scanning confocal microscope equipped with an argon laser . A 63× water objective ( HC PL APO CS , NA 1 . 2 ) was used at zoom 2 to image flight muscle attachment sites first for 5 frames before the bleach ( 512 × 512 px ) , then a region of interest ( ROI; 120 × 40 px ) was bleached for 1 frame using all 4 argon laser lines ( 458 nm , 476 nm , 488 nm , and 514 nm ) , and finally the fluorescence recovery was followed for 61 frames with a 5 s time resolution . The resulting 5-min movies were analyzed with the Fiji plug-in FRAP profiler ( http://worms . zoology . wisc . edu/ImageJ/FRAP_Profiler . java ) by comparing the bleached region to a control region of the muscle attachment to correct for gradual bleaching during image acquisition . FRAP curves were each normalized ( 1 = pre-bleach intensity; 0 = intensity directly after bleaching ) and then fit with a single exponential , yielding the recovery half time and the mobile fraction . Movies in which the attachment moved out of plane or out of the bleached region were excluded from the analysis . The experiment was performed on 3 independent experiment days . Primary cells were isolated from Drosophila embryos and differentiated as previously described [33 , 34] with the following modifications: embryos ( 5–7 h old , aged at 25°C ) were collected from smaller cages on only one 9-cm molasses plate per genotype . Embryos were homogenized with a Dounce homogenizer using a loose-fit pestle in 4 mL Schneider’s Drosophila medium ( Gibco 21720–024 , lot 1668085 ) and , after several washing steps ( using 2 mL medium ) , were resuspended to a concentration of 3 × 106 cells/mL . Finally , cells were plated in 8-well ibidi dishes ( 1 cm2 plastic bottom for microscopy with ibiTreat surface ) coated with vitronectin ( optional ) at a density of 3–9 × 105 cells/cm2 and differentiated for 5 to 7 d at 25°C in a humid chamber . Primary muscle fibers were fixed on day 6 after isolation with 4% PFA in PBS for 10 min at RT on a shaker . Phalloidin-staining ( Alexa647-conjugate; Molecular Probes ) was performed overnight in the dark at 4°C . Fixed cells were imaged in PBS on a Zeiss LSM 780 with a 40× oil objective ( Plan Apochromat , NA 1 . 4 ) . Live imaging of twitching primary cells was performed on a Leica SP5 confocal with a 63× water objective ( HCX PL APO 63×/1 . 2 W CORR λBL ) , acquiring the transmission light channel and the YPet channel simultaneously . Laser cutting and imaging was performed similar to a previous study on a custom-built setup with a spinning disc unit and a UV laser ( 355 nm , 100 mW nominal power ) [37] . Here , flight muscles and the connected tendon tissue were imaged at 20 h and 30 h APF in stripe-GAL4 , Mef2-GAL4 , UAS-brainbow pupae expressing palmitoylated mCherry as a marker in the tendon and muscle tissue or in talin-I-YPet pupae with Talin-I-YPet as marker for muscle attachment sites . For performing line cuts in a single z-plane , movies were acquired with a 300-ms time resolution for 150 frames ( 45 s ) using a 40× water objective ( NA 1 . 1 , Leica ) . After the first 10 frames , an 80- to 100-μm–long line was cut ( UV laser pulse repetition rate: 1 kHz , 2 pulses every 0 . 5 μm ) into the tendon or muscle tissue , and the recoil was followed over time . For performing line cuts in a 10-μm–thick z-stack in the muscle fibers , z-stack movies were acquired with a z-spacing of 1 μm and an exposure time of 300 ms per slice , resulting in 5 . 3 s acquisition time per stack . A total of 10 frames were acquired ( 42 . 5 s ) . During the second frame , 5 line cuts were performed , thereby cutting the tissue every 2 μm in z . A single z-plane of the resulting movie was chosen to analyze the tissue recoil . To quantify the tissue recoil , a line ( 20 px width ) was drawn along the direction of the movement in Fiji , and a kymograph with the average intensity along the line over time was created using the plug-in KymographBuilder [62] . In the kymograph , the movement of the tendon tissue or the muscle attachment was tracked manually by using the multipoint tool and the measure function . The initial recoil velocity of the tendon tissue was calculated from the first 2 frames after the cut . The recoil velocity of the muscle attachment after cutting the muscle in a z-stack was calculated from the position of the attachment in the first frame after the cut ( at 5 . 3 s ) compared to the position before the cut . Primary muscle fibers and pupae were imaged live on a Leica SP5 microscope equipped with a pulsed white light laser ( NKT Photonics , 80 MHz ) , a time-correlated single photon counting ( TCSPC ) -FLIM detector ( FLIM X16 , LaVision BioTec ) , and a 545/30 nm emission filter ( Chroma ) . Primary muscle fibers were imaged with a 63× water objective ( HCX PL APO 63×/1 . 2 W CORR λBL ) , and pupae were imaged with a 40× water objective ( HC PL APO 40×/1 . 1 W CORR CS2 ) . Photon arrival times were detected with a resolution of 0 . 08 ns in a 12 . 5 ns time window between laser pulses . The FLIM data were analyzed using a custom-written MATLAB ( MathWorks ) program [11 , 12] . First , an intensity image was created to manually draw an ROI around the target structure ( adhesions/costameres in primary cells or muscle attachment sites in pupae , also see S3 Fig ) . To create a binary mask of the target structure , Multi-Otsu thresholding with 3 classes was applied to the signal in the ROI blurred with a median filter ( 3 × 3 pixels ) , and holes in the mask containing the brightest class were filled . Photon arrival times of all photons inside the mask were plotted in a histogram , and the tail of the curve was fitted with a monoexponential decay yielding the fluorescence lifetime τ . Fits with more than 5% relative error in lifetime determination were excluded from further analysis . For dimmer samples ( primary fiber cultures and intermolecular FRET pupae ) , we used a 10% relative error cut-off . The FRET efficiency E was calculated according to the following formula , with τDA being the lifetime of the donor in presence of the acceptor and τD the lifetime of the donor alone: E=1−τDAτD ( 1 ) For all measurements , τD was determined as the median lifetime of Talin-I-YPet in the same experimental conditions . Experiments were repeated 2 to 5 times on different experiment days with 10 to 15 pupae/cells imaged per genotype and day . We determined the number of mechanically engaged ( = open ) tension sensor Nopen relative to the total number of molecules Ntotal at the muscle attachment site using biexponential fitting similar to as previously described [12] . Briefly , we assumed that the fluorescence decay from a tension sensor FLIM measurement can be described by 2 lifetimes: the lifetime of the open sensor τnoFRET and the lifetime of the closed sensor undergoing FRET τFRET . The lifetime of the open sensor τnoFRET approximately corresponds to the lifetime of the donor alone , because of the large contour length increase upon opening of the sensor . Thus , we determined the lifetime τnoFRET by using a monoexponential fit on Talin-I-YPet data as described above . The lifetime τFRET was determined from zero-force control ( Talin-C-TS ) data . Since the Talin-C-TS sample contains fully fluorescent sensor ( τFRET ) and sensor with nonfluorescent mCherry acceptor ( τnoFRET ) , we used a biexponential fit with fixed τnoFRET to determine τFRET . The 2 lifetimes τnoFRET and τFRET were then fixed and used to fit Talin-TS and Talin-C-TS data biexponentially , thereby determining the relative contributions of photons from molecules with these two lifetimes . From this , the relative number of molecules with τnoFRET and τFRET was calculated , taking into account that FRET reduces the number of photons detected in the donor channel . Finally , the ratio Nopen/Ntotal was determined by normalizing the Talin-TS values to the respective Talin-C-TS values . For the relative quantification of Talin-GFP and Integrin-GFP ( βPS-GFP , Mys-GFP ) levels at flight muscle attachments , living 20 h and 30 h APF pupae ( mounted as described above ) were imaged on a Zeiss LSM 780 scanning confocal microscope with a 40× oil objective ( Plan Apochromat , NA 1 . 4 ) using the same laser power and gain settings for Talin- and Integrin-GFP pupae . Muscle attachments were traced manually with the free-hand selection tool in Fiji using a fixed line width ( 40 px for 20 h APF and 20 px for 30 h APF ) . The intensity in the area along the line was averaged for each pupa . For each experiment day , the median Talin-GFP intensity of all pupae was set to 1 , and the relative Integrin-GFP intensity was calculated . Finally , the data from 3 independent experiment days were merged . Because the Talin-GFP allele is not homozygous viable , both the Talin-GFP and the Integrin-GFP flies were crossed to WT flies for this experiment . For quantifying Talin-I-YPet levels in heterozygous pupae , talin-I-YPet flies were crossed to talin null flies ( deficiency rhea79 ) [31] , and homozygous talin-I-YPet animals were used as a control . In addition to images acquired on the Zeiss LSM 780 microscope as described above , confocal images from the corresponding FLIM data set ( S7F Fig ) were used for quantification . For quantifying Talin-I-YPet levels at muscle attachments at 90 h APF upon talin knockdown with Act88F-GAL4 , z-stacks were acquired on the Zeiss LSM 780 microscope with a 10× air objective ( Plan Apochromat objectives , NA 0 . 45 ) . In a maximum-projected image of the thorax , anterior and posterior flight muscle attachments were traced manually with the free-hand selection tool in Fiji using a line width of 4 px . For this experiment , the flies were crossed at 25°C because at 27°C Act88F-GAL4 is detrimental . Living talin-I-YPet pupae were analyzed at 20 , 24 , and 30 h APF by a combination of confocal microscopy ( LSM 780 , Zeiss ) and FCS using a 40× water objective ( C-Apochromat 40×/1 . 20 W Korr UV-VIS-IR ) and the built-in GaAsP detector in single photon counting mode . Prior to the experiment , the correction collar and pinhole position were adjusted with fluorescent Rhodamine 6G in aqueous solution ( 30 nM in Tris [pH 8] ) using the same type of cover glass ( Marienfeld , High Precision , 18 × 18 mm , 170 ± 5 μm thickness ) as for mounting the pupae [61] . To calibrate the detection volume ( excitation 514 nm laser light ) , we measured FCS ( 120 s recordings ) at 3 different positions 20 μm above the cover glass surface . Autocorrelation curves were analyzed with our open-source software PyCorrFit [63] ( version 1 . 0 . 1 , available online at http://pycorrfit . craban . de/ ) . For fitting Rhodamine 6G data , we used a model accounting for triplet transitions and three-dimensional diffusion ( denoted “T-3D” in PyCorrFit ) . The detection volume Veff was calculated based on the measured diffusion time ( τdiff ) and the published diffusion coefficient D = 414 μm2/s [64]: Veff=S⋅ ( 4π⋅D⋅τdiff ) 3/2 ( 2 ) For all measurements , the axis ratio of the detection volume S = 5 was consistently fixed [65] . In living pupae , fluorescent proteins ( YPet or Talin-I-YPet ) were measured by FCS using a park and probe procedure [66]: in images , 3 positions in the muscle interior next to the muscle attachment site were manually selected for FCS ( 10× 40 s recordings ) . For fitting of Talin-I-YPet autocorrelation curves ( time bins > 1 μs ) , a two-component three-dimensional diffusion model with 2 nonfluorescent dark states ( denoted “T+T+3D+3D” in PyCorrFit ) was applied . Transient dark states were assigned either to triplet transitions ( τtrip1 , T1 ) in the time range of 1–20 μs and photochemical flickering ( τtrip2 , T2 ) in the time range of about 200–600 μs [67] . The first diffusion time was assigned to protein diffusion in the muscle interior , whereas the second diffusion term was merely a descriptive term accounting for slow long-tail behaviour that cannot be avoided in a crowed intracellular environment [66] . Autocorrelation curves derived from visibly unstable intensity traces were excluded from further analysis . Due to the high endogenous expression levels , the contribution of noncorrelated background was negligible . Thus , the molecular brightness , i . e . , the CPP value , of Talin-I-YPet was determined by dividing the average intensity I ( brackets indicate the average ) by the number of molecules in the focal volume N , which is dependent on the autocorrelation amplitude G ( 0 ) of the autocorrelation function G ( τ ) and the dark fractions T1 and T2 from the fit: CPP=〈I〉N=〈I〉⋅G ( 0 ) ⋅ ( 1−T1−T2 ) ( 3 ) Because freely diffusing YPet diffuses faster than Talin-I-YPet , the signal fluctuations related to flickering and diffusion cannot be distinguished in YPet measurements . Therefore , the autocorrelation curves of free YPet were fitted by a simplified model function accounting only for transient triplet states and 2 diffusive terms , of which the first combines contributions of both protein diffusion and flickering ( denoted “T-3D-3D” in PyCorrFit ) . To estimate true particle numbers , we corrected for triplet transitions and flickering globally by using the average fractions T1 and T2 from corresponding Talin-I-YPet measurements performed with the same excitation power density: CPPYPet=〈I〉〈N〉=〈I〉⋅〈G ( 0 ) 〉⋅ ( 1−〈T1 , Talin‐I‐YPet〉−〈T2 , Talin‐I‐YPet〉 ) ( 4 ) The diffusion constant of freely expressed YPet was in good agreement to other fluorescent proteins in the cytoplasm of living cells , suggesting that the point spread function positioned in the muscle cell is still diffraction limited . This finding justifies the external calibration of the detection volume by Rhodamine 6G . For quantification of the absolute Talin-I-YPet concentration at muscle–tendon attachment sites , the developing flight muscles were imaged in photon counting mode ( 512 × 512 px , pixel dwell time PT = 50 μs ) . Saturation of the detector was carefully avoided by keeping I ( x , y ) below 2 MHz . The counts in each pixel of an image were calibrated by the molecular brightness ( CPP ) value determined for Talin-I-YPet in the interior of the same muscle fiber by FCS [66] . Due to the monomeric state of Talin-I-YPet , intensity values stored in each pixel I ( x , y ) could be directly transformed into numbers of Talin molecules: N ( x , y ) =I ( x , y ) CPP⋅PT ( 5 ) Using the Avogadro constant ( NA ) and the detection volume ( Veff ) as determined by Rhodamine 6G measurements , we then calculated concentration maps: c ( x , y ) =N ( x , y ) NA⋅Veff ( 6 ) Finally , the muscle attachment sites were isolated in the Talin-I-YPet concentration maps by creating a mask with the same thresholding algorithm as used for FLIM-FRET . The concentration values were averaged across pixels within the mask resulting in a mean concentration value per pupa . A prerequisite for this approach is that the count values per pixel in the acquired confocal images increase linearly with the concentration of the analyte . To test this , we made an Atto488 1:10 dilution series and acquired confocal images 50 μm into a drop of each dilution on a coverslip ( covered to prevent evaporation ) . Quantification of the images indeed revealed a linear relationship between the photon count values and the analyte concentration over 5 orders of magnitude . Thus , low photon count values from Talin-I-YPet in the muscle interior can be directly compared to the high photon count values at the muscle attachment sites . To estimate Talin density on the membrane from pixel-by-pixel concentration values , we divided the average number of molecules in the focal volume at the muscle attachment sites by the membrane area in the focal volume . The focal volume was determined by Rhodamine 6G FCS measurements as described above . For the shape of the focal volume , we assumed an ellipsoid with the long axis ( z ) being 5 times the short axis ( x = y ) . Therefore , for a focus volume of 0 . 32 fL , the membrane area in the z-y plane is 0 . 63 μm2 . Taking into account that there are 2 membranes ( one from the tendon and one from the muscle ) and that the membrane is not flat ( ruffles approximately increase the area 2-fold as determined from EM images [68] ) , the total membrane area in the focal volume is about 2 . 5 μm2 . To estimate Talin-mediated tissue stress , we calculated force threshold of sensor × Talin density × proportion of mechanically engaged Talin = 7 pN × 400 molecules/μm2 × 13 . 2% = 0 . 37 kPa for 20 h APF; and 7 pN × 700 molecules/μm2 × 9 . 6% = 0 . 47 kPa for 24 h APF . Note that these values are lower estimates because individual molecules might experience forces higher than 7 pN . Box plots display the median as a horizontal line , and the box denotes the interquartile range . Whiskers extend to 1 . 5 times the interquartile range from the median and are shortened to the adjacent data point ( Tukey ) . In addition , all data points are shown as dots . Tests used for statistical evaluation are indicated in the figure legends . All data and statistical tests are listed in S1 Data . FLIM-FRET data were analyzed using custom-written MATLAB ( MathWorks ) code as published previously [11 , 12] . The code is available upon request .
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Cells in our body are constantly exposed to mechanical forces , which they need to sense and react to . In previous studies , fluorescent force sensors were developed to demonstrate that individual proteins in adhesion structures of a cell experience forces in the piconewton ( pN ) range . However , these cells were analyzed in isolation in an artificial plastic or glass environment . Here , we explored forces on adhesion proteins in their natural environment within a developing animal and used the muscle–tendon tissue in the fruit fly Drosophila as a model system . We made genetically modified fly lines with force sensors or controls inserted into the gene that produces the essential adhesion protein Talin . Using these force sensor flies , we found that only a small proportion of all the Talin proteins ( <15% ) present at developing muscle–tendon attachments experience detectable forces at the same time . Nevertheless , a large amount of Talin is accumulated at these attachments during fly development . We found that this large Talin pool is important to prevent rupture of the muscle–tendon connection in adult flies that produce high muscle forces during flight . In conclusion , we demonstrated that a large pool of Talin proteins is required for stable muscle–tendon attachment , likely with the individual Talin molecules dynamically sharing the mechanical load .
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2019
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A small proportion of Talin molecules transmit forces at developing muscle attachments in vivo
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Sleep plays a role in memory consolidation . This is demonstrated by improved performance and neural plasticity underlying that improvement after sleep . Targeted memory reactivation ( TMR ) allows the manipulation of sleep-dependent consolidation through intentionally biasing the replay of specific memories in sleep , but the underlying neural basis of these altered memories remains unclear . We use functional magnetic resonance imaging ( fMRI ) to show a change in the neural representation of a motor memory after targeted reactivation in slow-wave sleep ( SWS ) . Participants learned two serial reaction time task ( SRTT ) sequences associated with different auditory tones ( high or low pitch ) . During subsequent SWS , one sequence was reactivated by replaying the associated tones . Participants were retested on both sequences the following day during fMRI . As predicted , they showed faster reaction times for the cued sequence after targeted memory reactivation . Furthermore , increased activity in bilateral caudate nucleus and hippocampus for the cued relative to uncued sequence was associated with time in SWS , while increased cerebellar and cortical motor activity was related to time in rapid eye movement ( REM ) sleep . Functional connectivity between the caudate nucleus and hippocampus was also increased after targeted memory reactivation . These findings suggest that the offline performance gains associated with memory reactivation are supported by altered functional activity in key cognitive and motor networks , and that this consolidation is differentially mediated by both REM sleep and SWS .
Memory consolidation begins the moment new information is encoded and is a process where initially fragile memories are stabilised , strengthened , and reorganised in the brain [1] . Learning a new motor skill , for example , requires episodes of repeated practice , and is also supported by offline consolidation periods where stabilisation and gains in performance are observed [2] . Such performance improvement is reflected by plastic changes within key motor memory networks over time [3–5] , and several studies contrasting sleep and wake consolidation periods suggest that sleep provides the optimal conditions for this offline processing to occur [6–13] . The spontaneous reactivation of cerebral activity after learning is hypothesised to underscore such plasticity during sleep and the associated performance gains [14–17] . This “memory replay” has been observed in multiple brain regions during sleep in rodents [18–23] and humans [24–26] . Moreover , neural replay has been linked to sleep-dependent improvements in skilled motor movements [21] , while indirect disruption of this replay impacts upon spatial learning [22] and synaptic plasticity [23] . Targeted memory reactivation ( TMR ) during sleep , where the replay of specific memories can be cued via presentation of learning related sounds or odours [19 , 27–34] , provides further behavioural evidence that reactivation supports the consolidation of procedural skill in humans [28 , 30 , 31] . However , it is unknown whether these performance improvements after TMR are supported by underlying changes in activity within motor memory networks , changes that provide an indirect measure of underlying plasticity . The neurophysiological correlates of consolidation after TMR have been demonstrated for declarative memories [32 , 33] , but not procedural , and it remains unclear how they relate to the behavioural effects of TMR . Overnight procedural memory consolidation is linked to enhanced functional activation within striatum , hippocampus , cerebellum , and motor cortical regions , as well as striato-hippocampal and medial prefrontal-hippocampal ( mPFC-HPC ) connectivity [7–12 , 35] . Interactions between these networks are thought to assist the development of a refined motor representation and subsequently guide sleep-dependent consolidation [35] . Given that reactivation is thought to drive the plasticity associated with sleep [14–17] , we hypothesised that TMR would modulate such changes in functional activity and connectivity . The role of rapid eye movement ( REM ) sleep in procedural memory reactivation and consolidation is debated [36] . REM was initially linked with consolidation of procedural memory tasks [37–39] , and learning-related brain regions have been shown to reactivate during REM [24 , 25] . However , several studies now suggest REM may not be critical for procedural memory [36 , 40 , 41] . Furthermore , recent TMR studies link reactivation during slow-wave sleep ( SWS ) [28 , 30] and non-rapid eye movement ( NREM ) [31] with consolidation of motor tasks , while reactivation work in rodents focuses largely on NREM [18–21 , 23 , 42] . The interleaved cycles of REM and NREM periods could be important for consolidation [14 , 43] , with REM providing synaptic consolidation of memories that were already reactivated during NREM [14] , yet data linking REM with memory reactivation is lacking . In this paper , we set out to explore the role of both REM and NREM in consolidation by examining how individual differences in REM and SWS influence brain function after TMR . We aimed to test this by cueing a modified version of the serial reaction time task ( SRTT ) [44] during SWS and measuring subsequent differences in functional activity and connectivity during retest the following day using functional magnetic resonance imaging ( fMRI ) . Participants were required to react to visual stimuli appearing at one of four possible positions on screen , corresponding to four buttons on a response pad . Stimuli followed two repeating 12-item patterns presented in separate blocks . The two sequences were associated with different sets of tones ( either high or low in pitch , Fig 1 ) . One sequence ( cued ) was reactivated during nocturnal SWS by replaying the associated tones in sequence , while the other sequence ( uncued ) was not . Brain activity and behavioural measures of speed and accuracy were compared while performing cued and uncued sequences at postsleep retest . We were particularly interested in exploring how these differences in functional activity were influenced by SWS and REM . We predicted: ( 1 ) TMR would lead to faster reaction times ( RTs ) for the cued sequence . ( 2 ) TMR would result in a cueing-dependent increase in cerebral activation within structures that are important for sequence consolidation , namely the striatum , hippocampus , cerebellum , medial prefrontal cortex ( mPFC ) , and motor cortical areas [7–12 , 35] . ( 3 ) Since SWS duration is associated with consolidation [45] and TMR effects [46 , 47] , we predicted that changes in activation within the aforementioned structures would be associated with SWS . ( 4 ) Lastly , because procedural memory consolidation has also been linked with REM sleep [37–39] and stage 2 sleep [48 , 49] , while the neurophysiological correlates of consolidation have also been linked with overnight changes in performance [7 , 8 , 10–12 , 35 , 50] , we expected that functional activation changes might also be related to these factors .
To examine the neural responses associated with a procedural memory that has undergone TMR during sleep , we contrasted activity during performance of the cued sequence with performance of the uncued sequence at retest ( p < 0 . 05 , whole brain corrected ) . This basic contrast revealed no increases , but a decrease in activity for the cued sequence in a cluster-spanning left caudate and anterior cingulate gyrus , and a second left occipital/cuneus cluster ( Fig 3A ) . Next , we investigated whether other factors were related to the cueing effect by running the same cued > uncued contrast again with five regressors added at the second level: duration ( mins ) of SWS ( SWStime ) , duration of REM ( REMtime ) , duration of stage 2 ( Stage2time ) , the number of replayed sequences ( replays ) and the procedural cueing effect . Prior work has shown that the length of SWS predicts behavioural consolidation effects after both normal sleep [45] and TMR [46 , 47] . Our cues were presented during SWS; therefore , we expected this regressor to reveal cueing effects in regions that underscore motor learning . As hypothesised , the contrast [ ( cued > uncued ) * SWStime] showed significantly stronger responses for the cued sequence in bilateral caudate and hippocampi ( Fig 3B , Table 3 for complete list of responses ) . We observed significantly decreased activity for the cued sequence in bilateral sensorimotor cortex ( SMC ) , and right frontal eye fields ( FEF ) ( Table 4 ) . In sum , a longer duration of SWS was associated with increased responses to the cued sequence within predicted subcortical regions that are critical to procedural learning ( caudate and hippocampus ) , while other key cortical motor regions showed decreased responses ( SMC and FEF ) . When time spent in stage 2 was examined [ ( cued > uncued ) * Stage2time] the pattern of activity was similar to that observed with the SWS regressor , with significantly increased activity for the cued sequence in the same right caudate cluster , and decreased activity in left SMC . REM has also been linked to motor sequence memory reactivation and consolidation [24 , 25 , 37–39 , 42]; therefore , we next considered TMR effects with REMtime as the regressor of interest [ ( cued > uncued ) * REMtime] . This showed significant clusters of increased activation for the cued sequence in a number of motor regions , including bilateral cerebellum , right premotor cortex ( PMC ) , and left SMC ( Fig 3C , Table 3 ) . Additionally , left dorsolateral prefrontal cortex ( dlPFC ) and bilateral superior parietal clusters also showed greater activity for the cued sequence . Interestingly , this regressor also revealed decreased activity for the cued sequence in a right caudate cluster , which overlapped with the right caudate cluster that showed increased activity when considering SWS ( Table 4 ) . Thus , REM and SWS were associated with changes in activity after cueing in separable motor learning regions and also had opposite relationships with activity levels in the right caudate . The number of sequences that were played as cues during sleep could potentially have influenced changes in functional activity . When examining the number of replays as the second-level regressor [ ( cued > uncued ) * replays] , we found increased activity in the right SMC , indicating that more replays were associated with a larger response for the cued sequence in these areas . Conversely , activity in the right caudate decreased for the cued sequence; therefore , the replays regressor showed the reverse pattern to the SWS regressor . Next , the amount of overnight improvement in performance has previously been linked to neurophysiological changes [7 , 8 , 10–12 , 35 , 50]; therefore , we also examined the procedural cueing effect as a regressor [ ( cued > uncued ) * procedural cueing effect] . This did not identify increases in any of the predicted regions ( Table 3 ) , and there were no significant decreases . After identifying localised activation differences associated with TMR during SWS , we sought to examine the functional connectivity of task-related regions that showed sensitivity to TMR . This was achieved with four psychophysiological interaction ( PPI ) analyses seeded in right and left hippocampus and right and left caudate nucleus , all based on peak coordinates identified in relation to the SWStime regressor [ ( cued > uncued ) * SWStime] . Each analysis explored how connectivity from the seed region to the whole brain differed between cued and uncued sequences ( p < 0 . 05 , whole brain corrected ) . Crucially , both hippocampal seeds showed enhanced connectivity with key motor regions during cued relative to uncued sequence performance . Left hippocampus ( −22 , −34 , 6 ) showed greater connectivity to right PMC , right putamen , left putamen , and thalamus , and a cluster spanning bilateral thalamus and midbrain ( Fig 4 , Table 5 ) . Connectivity between this seed and bilateral middle temporal gyrus was also enhanced . The right hippocampus seed ( 26 , −34 , 2 ) showed greater connectivity with left caudate and right fusiform face area ( FFA ) . The left caudate seed ( −12 , 20 , 12 ) showed enhanced connectivity with bilateral thalamus , right temporal pole , left FFA , and left lingual gyrus . The right caudate seed showed increased connectivity with left superior parietal cortex . There was just one instance of reduced functional connectivity for the cued sequence , between the left caudate seed ( −12 , 20 , 12 ) and left cerebellum . To summarise , TMR was associated with increased subsequent connectivity and activation within regions associated with procedural learning . This altered pattern of brain activity may underpin the behavioural enhancements we observed .
We show that targeted reactivation of a procedural memory alters functional activity and connectivity of motor memory networks in the human brain . The enhanced response speed for the cued sequence occurred alongside increased caudate and hippocampal responses associated with time spent in SWS , and increased hippocampal-caudate connectivity . Furthermore , REM sleep was linked with cueing-related activity changes in additional motor regions including SMC , PMC , and cerebellum . Together , these results support distinct contributions of different sleep stages to consolidation , with SWS facilitating consolidation in key subcortical regions ( striatum and hippocampus ) that are known to support sequence learning [2–4 , 7–13 , 35] , while REM sleep facilitates consolidation in cortical and cerebellar networks that are specific to motor learning ( cerebellum and motor cortical regions ) [2–5 , 7–9] . The finding that REM is associated with changes in functional activation , even though TMR occurred during preceding periods of SWS , is of particular significance because it suggests a link between NREM memory reactivation and the processing that occurs in subsequent REM sleep . REM’s role in the reactivation and consolidation of procedural memories is controversial [36 , 41] . It was initially linked to procedural learning by some experimental findings [37–39] , but most examples of neuronal replay occur in NREM sleep [18–21 , 23 , 42] , and the targeted reactivation of procedural memories has only succeeded with cues presented during NREM [28 , 30 , 31] . As a result , prominent models of reactivation and systems consolidation prioritise NREM processes [14 , 15 , 17] . The idea of interacting periods of SWS and REM was first put forward by the “sequential hypothesis” [43] , which proposes that REM strengthens and stabilises processes begun during preceding SWS periods , enabling synaptic consolidation to stabilise memories after being reorganised during SWS [14] . Our findings support this model and indirectly suggest that reactivated procedural memories may undergo processing in separable REM and SWS networks . Importantly , we found cueing-related increases in the responses of bilateral caudate nuclei and hippocampi that were associated with time in SWS . Long-term systems consolidation for motor skills is characterised by a gradual shift of the representation from caudal to ventral striatum , alongside decreasing recruitment of corticocerebellar circuits [4] . However , procedural memory consolidation over just one night tends to follow a pattern of changes very similar to that of our cued sequence , involving increased responses in corticostriatal networks [7–11 , 35] . The increase in hippocampal response for the cued sequence is important for several reasons . Such enhanced activity is associated with overnight changes in motor sequence performance [7 , 10 , 35] , and the hippocampus is hypothesised to be critical for engaging sleep-dependent sequence consolidation [53] . Such plasticity within striatum and hippocampus could potentially be driven by spontaneous reactivation during sleep [18 , 20 , 24 , 25] , supported by our observation that TMR during sleep can bias functional changes in these regions . Interactions between the striatum and hippocampus have been suggested to underscore procedural learning and consolidation , perhaps mediated by connections with mPFC [12 , 35] . Consistent with this , we found that TMR during sleep influenced striato-hippocampal connectivity , with enhanced connectivity between right hippocampus and left caudate , and between left hippocampus and a cluster-spanning bilateral thalamus and putamen . This supports the idea that TMR during SWS can modify connectivity patterns within the brain networks underpinning performance [33] , and extends this to procedural memory . This result was predicted based on prior MSL research by Albouy and coworkers [10 , 11 , 35] , showing that interactions between striatum and hippocampus are associated with overnight performance gains . The mPFC is thought to mediate between hippocampus and striatum during skill acquisition and consolidation [12 , 35] . Neither activity nor connectivity in mPFC differed significantly between our sequences at retest , but this region may still have played a role during acquisition and consolidation . Together , these findings suggest that the functional interaction between hippocampus and striatum underscores consolidation of MSL , and our data support the idea that reactivation during SWS is the mechanism for this process . We propose that the changes in striatohippocampal connectivity reflect stabilisation and perhaps reorganisation of the sequence memory representation , which allows faster motor output when performing the sequence at retest . Our observation that TMR-dependent changes in caudate and hippocampal activity were related to SWS adds to our previous finding that SWS is linked to the impact of TMR on behavioural measures [46] , and that a shorter period of SWS containing TMR provides the same offline gains as a longer period of SWS [47] . We now additionally suggest that the amount of SWS obtained also determines the extent of neural reorganisation in relation to reactivation of a procedural memory . While the SWS-associated functional increases for the cued memory occurred in subcortical regions known for their roles in many types of learning , REM-associated increases related to cortical and cerebellar regions that are for the most part motor learning specific . These include increased activity in bilateral cerebellum , right ventral PMC and left SMC . SMC is critical for processing complex finger movements [55] , while PMC forms a loop with the striatum and thalamus during motor performance and is thought to interact dynamically during learning to create a sequence memory [4] . Our findings are consistent with other demonstrations of increased cerebellar activity after sleep compared to wake [7] , which may indicate a higher demand for error monitoring after consolidation [56] . Collectively , these regions comprise much of the corticocerebellar network , including SMC , ventral PMC , and cerebellum [57] , which may suggest a preference for corticocerebellar processing during REM sleep . At this relatively early stage of systems consolidation , increased activity in these areas may facilitate faster motor output of the cued sequence . Additionally , we observed increased activity for the cued sequence in dlPFC and superior parietal cortices in association with REM . These regions are known to interact with the striatum during early MSL and consolidation [4 , 58 , 59] , so this may reflect the formation of an efficient cued sequence representation . Interestingly , REM and SWS were linked to opposing patterns of activity in SMC and striatum: cueing-related SMC responses decreased in association with SWS and increased in association with REM , while right caudate activity decreased in association with REM and increased in association with SWS . Furthermore , an additional motor cortical region involved in directing eye movements and visual attention , the FEF [60] , showed decreased activation for the cued sequence in relation to SWS . These results could indicate a competitive interaction between subcortical SWS and cortical REM networks , although future research should examine this by manipulating reactivation in both sleep stages . Our connectivity analysis also revealed that for the cued sequence , the left hippocampus was more connected to right PMC , and bilateral thalamus and midbrain . Thalamus and striatum form a segregated loop with cortical motor regions in order to process motor information [4] , alongside contributions from midbrain nuclei [61]; therefore , this result may indicate enhanced hippocampal contributions to this circuit after TMR . This enhanced connectivity may be the consequence of communication between hippocampal and cortical regions during reactivation , a process that is proposed to underscore systems consolidation during sleep [14] . Additionally , the left caudate was more connected to bilateral thalamus and midbrain for the cued sequence , while the right caudate was more connected to left superior parietal cortex . This agrees with recent observations that connectivity between striatum , thalamus , and superior parietal cortex were involved in MSL acquisition and consolidation [9] . Tighter coupling of these motor circuits as a result of TMR may support enhanced performance of the cued sequence . We found only one example of reduced functional connectivity for the cued sequence , between the left caudate and left cerebellum , and this decoupling of cerebellum is often observed as motor skills become automatized [3 , 4] . Since this analysis utilised seed regions from the SWS regressor , it could potentially identify whether parts of the SWS network were driving the REM network regions . However , there were no overlapping clusters from the REM regressor and the PPI; therefore , the relationship between the two networks remains unclear , and this is perhaps a question future studies should explore by manipulating both sleep stages and replay . In sum , these findings demonstrate that cued reactivation influences functional interactions across a range of networks involved in MSL . Notably , although longer SWS duration was associated with enhanced response in bilateral caudate nuclei after TMR , comparison of cued and uncued sequences without any additional covariates showed decreased activity in left caudate . An overnight decrease in striatal response is in line with some prior MSL studies that contrast the brain activity associated with sleep and wake retention intervals [6 , 12] , although others show activation increases [7 , 8 , 10] . These disparate findings most likely stem from subtly different designs . Our current design differs still more , due to its focus on sleep stages and their interaction with consolidation after TMR . However , we acknowledge that by introducing regressors such as SWStime into our analyses , we potentially confound our findings with other factors that relate to these regressors , such as prior sleep pressure . The stage 2 regressor identified a small number of regions that were also associated with SWS , with increased activity for the cued sequence in the right caudate and decreased activity in left SMC . Stage 2 duration has previously been correlated with procedural consolidation [48 , 49] , as have the sleep spindles that are a prominent feature of this stage [49 , 62 , 63] ( S1 Text ) , and some have proposed that reactivation during stage 2 provides the optimal neurophysiological conditions for systems consolidation [15] . The overlap we observed between results for SWS and stage 2 suggests that similar forms of consolidation may occur in these regions across the entirety of NREM sleep . This prompted us to examine NREM sleep as a whole ( SWS+S2 duration ) . The NREM covariate provided virtually identical results to the SWS covariate , indicating a strong influence of SWS ( S1 Text ) . The number of sequences played to participants was positively correlated with SWS duration ( r = 0 . 49 , p = 0 . 03 ) due to our opportunistic method of cueing across SWS epochs during the first half of the night ( i . e . , participants with more early night SWS received more cues ) ; therefore , both were included in the fMRI model to identify the unique variance associated with each . We had no a priori hypotheses for this regressor , since the number of cues that are presented during sleep has previously shown no relationship with the behavioural or neural effects of TMR [27–33 , 46 , 47] . Unexpectedly , replays were linked with a small subset of regions that were also associated with REM sleep , with increased activity in right SMC and decreased right caudate when performing the cued sequence . This result suggests that the number of reactivation cues does influence the physiological consolidation process , despite not correlating with behavioural measures of consolidation . The similarity between this result and the REM regressor could even suggest that the extent of cueing in NREM determines subsequent processing of those memories in REM sleep . Neuronal firing sequences in rodents [18 , 20–23 , 42] and regional blood flow changes in humans [24–26] have both demonstrated spontaneous learning-related reactivation during sleep in areas that are critical to learning , including the hippocampus [18 , 26 , 42] , striatum [20 , 24 , 25] , and motor cortical regions [21 , 23] . Recently , reactivation in rodent primary motor cortex was linked to acquisition and sleep-dependent consolidation of a new motor skill , as well as subsequent changes in neuronal firing properties [21] . Coupled with this , TMR has been shown to bias learning-specific neuronal firing sequences during sleep in rodents [19] and trigger similar neural responses in the hippocampus and parahippocampus during SWS in humans [27 , 33] . Reactivation in the current study very likely engages similar processes , and this activity during NREM paves the way for the altered brain function observed after sleep . Together , these findings convincingly couple learning-related reactivation during NREM with memory consolidation . However , the mechanism by which REM sleep then acts upon a reactivated memory trace remains to be explored . There are some limitations to the current work . Our behavioral cueing effect was apparent during early blocks at retest but not later blocks where our sequence-specific measure was calculated . As a result , we cannot be certain whether the cueing effect at early sequence blocks was due to unspecific improvements in sensorimotor mapping or sequence learning . Thus , it is possible that TMR integrated the tones more tightly with the cued sequence , allowing faster responses . Prior work in which only sequence-specific skill has been shown to benefit from sleep-dependent consolidation [51–53] and TMR during sleep [28 , 31] provides some confidence that the difference we observed was sequence specific . The lack of an effect at later blocks most likely reflects the cued sequence approaching ceiling performance prior to the uncued sequence . It should also be noted that the two sequences share some basic features ( e . g . , triplets such as 2-4-3 ) , meaning it is possible that TMR benefitted these features in the uncued sequence . The fact that we find significant performance differences in early blocks and in our prior work [28] suggests the sequences did form separate memory representations that could be cued separately , despite these shared features . A procedural task with more separable memory representations might produce more robust cueing effects at the neural and behavioral level . To conclude , we show that TMR of a procedural memory alters functional activity and connectivity changes in striatum and hippocampus , and this altered function may explain the behavioural effects associated with TMR . We provide tantalising hints that REM sleep , as well as SWS , after TMR is important for neural changes that support enhanced postsleep performance of a procedural skill . These findings further our understanding of sleep’s unique role in memory consolidation by showing that offline skill enhancement depends on the reactivation of specific memory traces , and the associated changes in neural activity rely upon processing that may unfold across several subsequent stages of sleep .
Twenty-five ( 16 males ) healthy participants aged 18–35 y ( mean age = 23 . 8 y , SD ± 4 . 2 ) volunteered . Three were excluded because of ceiling performance at learning , falling asleep during the fMRI scanning session , and disrupted SWS as a result of cueing . Data from the remaining twenty-two ( 14 male ) participants aged 18–35 y ( mean age = 23 . 5 y , SD ± 4 . 3 ) were analysed . Prestudy questionnaires determined that participants had no history of psychiatric diseases , neurological , sleep , or motor disorders and kept a normal sleeping pattern in the week prior to the experiment . Participants were free of any form of medication , except for females using the contraceptive pill . They were asked to abstain from caffeine and alcohol 24 h prior to testing and between test sessions and to avoid napping on the experimental day . All participants were right-handed , confirmed by a score of 80% or more on the Edinburgh Handedness scale [64] . Informed written consent was acquired in accordance with the University of Manchester ( ID: 11367 ) and the University of Liverpool ( ID: RETH000585IREC ) ethics committees . Prior to the scanning session , a qualified radiographer from the University of Liverpool screened participants to assess their suitability for MRI . Participants arrived at 7–8pm for the first session and were fitted for polysomnography ( PSG ) . They then performed an adapted SRTT [44] containing psuedorandomly interleaved blocks of two 12-item sequences , A ( 1-2-1-4-2-3-4-1-3-2-4-3 ) and B ( 2-4-3-2-3-1-4-2-3-1-4-1 ) , with no runs of more than two blocks of the same sequence ( Fig 1 ) . Sequences followed the constraints that each item appeared three times , was present once in each half of the sequence , and could not appear sequentially ( e . g . , 1–1 ) . Blocks containing three repetitions of the sequence were separated by a consistent 15-s gap where RT and error rate feedback was presented . Sequences A and B were counterbalanced across cueing conditions so that half were cued during sleep with sequence A and half with sequence B . Each sequence was accompanied by pure tones , four high-pitched tones were used for one sequence ( fifth octave; A/B/C#/D ) , and four lower pitched tones were used for the other ( fourth octave; C/D/E/F ) . Participants performed 20 blocks of each sequence , followed by four random blocks containing no repeating sequence , ( “R” displayed centrally ) , containing high- ( two blocks ) and low-pitched tones ( two blocks ) Trials contained an auditory tone and visual cue in one of four spatial locations , corresponding to a four-button box used with all fingers of the left hand ( Fig 1 ) . “A” or “B” appeared centrally on the screen to indicate the sequence . Participants were asked to respond as quickly and accurately as possible and were not asked to explicitly learn the sequences . Visual cues were objects or faces appearing in the same position for both sequences . Participants were told the nature of cues ( objects/faces ) was irrelevant . Stimuli remained on screen until a correct response was made , followed by a 300 ms intertrial interval . Participants were invited to sleep overnight in the Neuroscience and Psychology of Sleep ( NaPS ) Laboratory at the University of Manchester , where they were monitored with PSG . Lights out was at 11pm . Brown noise was presented throughout the night . During periods of SWS , one sequence’s tones were replayed just loud enough to be audible above the brown noise ( at approximately 48 dB ) , in the same order as learning and at a speed similar to mean presleep performance , in blocks of 2 min replay ( CUE ) , followed by 2 min silence ( NO-CUE ) . Replay was only instigated after 3 min of what the experimenter considered to be stable SWS , in line with AASM criteria . Sequence A and B were counterbalanced across cued and uncued conditions , and tones ( high/low pitch ) were counterbalanced across sequences . Cues were stopped upon signs in the EEG of arousal or leaving SWS . Participants were woken up at 7–8am . The retest session took place 11am–12pm during fMRI , consisting of 24 sequence blocks ( 12 cued and 12 uncued ) , followed by 24 random blocks ( 12 blocks containing cued tones and 12 containing uncued tones ) . “REST” was displayed centrally during 15 s breaks between blocks . Order of learning ( i . e . , whether participants began a session with sequence A or B ) , replay , and retest was counterbalanced across participants . Lastly , free recall was measured outside the scanner with participants marking sequence order on paper . The Stanford Sleepiness Scale assessed alertness prior to learning and retest sessions [65] . All experimental scripts were executed using MATLAB 6 . 5 ( The MathWorks Inc . , Natick , MA , 2000 ) and Cogent 2000 ( Functional Imaging Laboratory , Institute for Cognitive Neuroscience , University College , London ) . Sounds were presented via a pair of Sony noise cancelling headphones during the learning session , via PC speakers during sleep replay , and via an MR compatible headphone system ( MR Confon ) during retest ( fMRI ) . A serial four-button box attached to a Domino multicontroller from Micromint recorded participant responses , with a time resolution of approximately 1 ms . Functional MRI data were acquired using an eight-channel head coil with a Siemens 3T Allegra MR scanner . The BOLD signal was recorded with T2*-weighted fMRI images obtained via a gradient echo-planar imaging ( EPI ) sequence . We acquired 50 oblique transaxial slices at 25-degree tilt , in an ascending sequence , voxel size 3 x 3 x 2 . 8 mm , matrix size of 64 x 64 , flip angle of 80 degrees , repetition time ( TR ) of 2 , 960 ms , and echo time ( TE ) of 30 ms . A structural T1-weighted image was also acquired , using a 3D IR/GR sequence with a matrix size of 224 x 256 x 176 , cubic voxels with isotropic resolution of 1 mm3 , TR of 2 , 040 ms , TE of 5 . 57 ms , inversion time of 1 , 100 ms , and flip angle of eight degrees . Three measures of behavioural performance improvement were calculated by comparing presleep to postsleep performance in terms of both accuracy and RT: ( 1 ) Early sequence improvement: mean performance on the first four blocks of SEQ_C and SEQ_U at retest subtracted from mean performance on the last four blocks of SEQ_C and SEQ_U at learning . This measure identifies whether any cueing effects are present immediately upon retest . ( 2 ) Late sequence improvement: mean performance on the last four blocks of SEQ_C and SEQ_U at retest subtracted from mean performance on the last four blocks of SEQ_C and SEQ_U at learning . This measure identifies whether any cueing effects are present toward the end of the retest session . ( 3 ) Sequence-specific improvement: this utilised a well-established method to separate sequence skill from learning of sensorimotor mapping between response keys and visual stimuli , by subtracting sequence from random performance [28 , 52–54] . For the learning session , we subtracted performance on the last four blocks of SEQ_C and SEQ_U from the two blocks of RAND_C and RAND_U that also occurred at the end of the learning session . For the retest session , we subtracted the last four blocks of SEQ_C and SEQ_U from the first four blocks of RAND_C and RAND_U , which were performed immediately afterwards . Lastly , we calculated “sequence-specific improvement” by subtracting the retest score from the learning score [28] . Together , these measures index the way TMR influences performance of sequences across the retest period . RTs >1 , 000 ms were excluded , while trials with multiple button presses prior to the correct press were included . Explicit recall was assessed in line with previous work [28] , whereby participants consciously recalled sequence order and marked it on paper . Individual items within a segment containing >2 consecutive correct items and in the correct sequence position were considered correct . We also calculated how strong the cueing effect was for each participant , in terms of their RT performance and their explicit sequence knowledge . The “procedural cueing effect” was obtained by subtracting early sequence improvement ( defined above ) for the cued from the uncued sequence . The “explicit cueing effect” was calculated by subtracting explicit sequence knowledge for the cued from the uncued sequence ( note that this was only measured after consolidation ) [28] . These behavioural measures were used to correlate with EEG and fMRI analyses . Mixed ANOVA and paired sample t tests were used for planned comparisons of cued and uncued sequence RT and recall . Associations between behavioural measures and EEG features were tested with Pearson’s correlations . Where Shapiro-Wilk tests indicated a non-normal distribution , Wilcoxon signed-rank tests or Spearman’s Rho correlations were used . All statistical tests were two-tailed , significance level p < 0 . 05 . All means presented in the text ± standard deviation . Electrodes were affixed at standard locations , F3 , F4 , C3 , C4 , C5 , C6 , CP3 , CP4 , CP5 , CP6 , P7 , P8 , O1 , and O2 , referenced to the combined mean of left and right mastoid , according to the 10–20 system . Also attached were left and right electro-oculagram , left and upper electromyogram and forehead ground electrode . Impedance below 5Ω was verified , and the digital sampling rate was 200 Hz . Data were scored according to standard criteria [66] by two experimenters , the second of which was blind to CUE/NO-CUE periods . Mean time spent in sleep stages ( Table 2 ) was based on n = 21: one participant was excluded due to loss of EOG channels in the latter part of the night ( after TMR had concluded ) . Welch’s method was used for power spectral density analyses , with alpha power ( 8–12 Hz ) at occipital channels averaged over separate concatenated time series for CUE and NO-CUE periods via MATLAB 2010 . Functional imaging data were analysed using Statistical Parametric Mapping 8 software ( SPM8; Wellcome Department of Cognitive Neurology , London , UK ) . The first two volumes of each functional EPI run were removed to allow for T1 equilibration . Two participants were excluded from analysis for excessive movement >3 . 5 mm . Functional images were realigned to correct for motion artifacts using iterative rigid body realignment , minimizing the residual sum of squares between all scans and the first scan . Functional images were then spatially normalised to the Montreal Neurological Institute brain ( MNI space ) , resampled to voxel size 2 x 2 x 2 mm . Lastly , a spherical Gaussian smoothing kernel ( full-width half maximum = 8 mm ) was applied to each participant’s normalised data . Statistical analysis of MRI data at the single subject level used the general linear model ( GLM ) [67] . Blocks of cued and uncued sequences were modelled as boxcar functions , and button presses for individual trials were also modelled as single events with zero duration . These were temporally convolved with the hemodynamic response function ( HRF ) . The design matrix also included six nonconvolved head motion regressors and , lastly , baseline activation was modelled with a constant regressor . A first-order autoregressive model with added white noise was used to model serial correlations , estimated with a restricted maximum likelihood algorithm . A high pass filter was utilised by using a cut off period of 128 s , removing low frequency noise . Contrast parameter images were generated for each participant with balanced linear t-contrasts , including one-sample t tests for the cued > uncued contrast . These contrast images were subsequently entered into a second-level random effects analysis . To determine whether the difference between cued and uncued sequences was associated with other factors , we included sleep parameters ( minutes spent in stage 2 , SWS , and REM sleep ) , the number of replayed sequences and the procedural cueing effect as covariates in a single second-level analysis . All analyses were whole brain corrected via a Monte Carlo simulation [68] . This modelled the entire imaging volume across 1 , 000 iterations , assuming a type I error of p < 0 . 05 at a voxel-wise uncorrected threshold of p < 0 . 005 , and recommended a cluster extent threshold of 51 contiguous voxels . Clusters falling entirely in white matter were not reported . We examined the functional connectivity between regions using PPI . Four separate PPI’s were conducted . Each spherical seed region ( radius 6 mm ) was based on peak coordinates of the group response to the cued > uncued contrast with SWStime as a second-level covariate . Coordinates were chosen from the results when SWStime was the regressor of interest because this identified regions that were hypothesised a priori to show changes in functional connectivity after TMR , based on previous work [8 , 9 , 11 , 12 , 33] . For each participant , the time course of activity for a sphere with a radius of 6 mm around the peak coordinate of the seed region was extracted and deconvolved , forming the physiological factor . We were interested in how connectivity with each seed varied after TMR during sleep , therefore our psychological factor was the contrast ( cued > uncued ) . For each participant , our PPI design matrix included three regressors: the physiological factor , the psychological factor , and the interaction ( physiological versus psychological ) , in addition to the button press regressor convolved with the HRF , and the six nonconvolved motion regressors . Contrast images for the PPI regressor were then generated using a one-sample t test . These images formed a second-level random effects analysis . The results represented regions whose functional connectivity was sensitive to whether the sequence had been cued during sleep or not . PPI data was thresholded in the same manner as localised data , i . e . , 51 contiguous voxels of p < 0 . 005 were considered significant at p < 0 . 05 based on our Monte-Carlo simulation . The coordinates used for the PPI analyses are listed below: Left caudate nucleus −12 , 20 , 12; right caudate nucleus 16 , 8 , 20; left hippocampus −22 , −34 , 6; right hippocampus 26 , −34 , 2 .
|
After a motor skill is learned , the memory undergoes "offline" processing so that improvement occurs even without further practice . Sleep has been shown to enhance this consolidation and , in the process , to reorganize the brain regions involved . However , it remains unclear how sleep does this , and whether different sleep stages have different contributions . One popular idea is that the memory trace is reactivated during slow-wave sleep—a period of sleep characterized by synchronized activity at a slow frequency and high amplitude , as recorded by electroencephalography ( EEG ) —which drives memory reorganization within the brain . To test this in humans , we took advantage of "targeted memory reactivation , " where replay of specific memories is cued by presentation of a sound that was present during learning . After sleep , motor performance was faster for cued memories , suggesting that the trace was consolidated during sleep . Coupled with this , brain activation and connectivity in several motor-learning areas was enhanced for the cued memory . Furthermore , some changes in brain activity were associated with time spent in slow-wave sleep , while others were associated with time spent in rapid-eye movement sleep . These observations provide further insight into sleep's unique role in memory consolidation by showing that offline skill enhancement depends on the reactivation of specific memories , and the associated changes in neural activity may rely upon processing that unfolds across different stages of sleep .
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2016
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Cued Reactivation of Motor Learning during Sleep Leads to Overnight Changes in Functional Brain Activity and Connectivity
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It has been a long-standing goal in systems biology to find relations between the topological properties and functional features of protein networks . However , most of the focus in network studies has been on highly connected proteins ( “hubs” ) . As a complementary notion , it is possible to define bottlenecks as proteins with a high betweenness centrality ( i . e . , network nodes that have many “shortest paths” going through them , analogous to major bridges and tunnels on a highway map ) . Bottlenecks are , in fact , key connector proteins with surprising functional and dynamic properties . In particular , they are more likely to be essential proteins . In fact , in regulatory and other directed networks , betweenness ( i . e . , “bottleneck-ness” ) is a much more significant indicator of essentiality than degree ( i . e . , “hub-ness” ) . Furthermore , bottlenecks correspond to the dynamic components of the interaction network—they are significantly less well coexpressed with their neighbors than nonbottlenecks , implying that expression dynamics is wired into the network topology .
Protein networks are a topic of great current interest , particularly after a growing number of large-scale protein networks have been determined [1–6] . Protein–protein interaction networks and regulatory networks are the key representatives for biological networks with undirected and directed edges [7–12] . Previous topological studies were mainly focused on analyzing degree distributions and finding motifs within these networks [7–9 , 11 , 13 , 14] . All of these networks are scale-free with power-law degree distributions , and hubs ( proteins with high degrees ) in the network represent the most vulnerable points [7–9 , 14] . Recently , another topological feature of the network has received attention—betweenness , which measures the total number of nonredundant shortest paths going through a certain node or edge [15 , 16] . Betweenness was originally introduced to measure the centrality of the nodes in networks [15] . By definition , most of the shortest paths in a network go through the nodes with high betweenness . Therefore , these nodes become the central points controlling the communication among other nodes in the network . More recently , Girvan and Newman proposed that the edges with high betweenness are the ones that are “between” highly interconnected subgraph clusters ( i . e . , “community structures” ) ; therefore , removing these edges could partition a network [16] . Furthermore , Dunn et al . found that protein clusters within interaction networks defined by this edge betweenness method tend to share similar functions [17] . Here , we revisited the original meaning of betweenness as a measure of the centrality of the nodes in a network . If we think of protein networks ( in particular , regulatory networks ) in analogy to a transportation network , proteins with high betweenness are similar to heavily used intersections , such as those leading to major highways or bridges ( see Figure 1 ) . If these major intersections were blocked , there would be huge traffic jams , causing the whole transportation system to fail . Therefore , we called these high-betweenness proteins bottlenecks , and hypothesized that these bottlenecks , just like hubs , represent important points in biological networks as well . For simplicity , we defined protein bottlenecks as the proteins with the highest betweenness; hubs , as the proteins with the highest degree ( see Methods ) . In fact , previous studies have shown that protein bottlenecks are indeed more likely to be essential [18 , 19] . This holds true in three different eukaryotic protein-interaction networks: yeast , worm , and fly [19] . However , Goh and his colleagues also found that , in these interaction networks , the betweenness of a node is correlated to its degree [20] . Therefore , it is not clear whether protein bottlenecks are important because they have high betweenness or because they also tend to be hubs . Moreover , Han et al . found that there are two categories of protein hubs within the yeast protein-interaction network: “party hubs” interact with most of their partners simultaneously , whereas “date hubs” bind theirs asynchronously [21] . Because protein bottlenecks in the interaction network connect different functional clusters—as mentioned above in [17]—it is conceivable that bottlenecks with high degrees should have a higher tendency to be date hubs . Here , we analyzed the biological significance of betweenness in terms of protein functions , expression correlation , and its relationships with protein hubs .
Because bottlenecks are key connectors in protein networks , we hypothesized that these proteins would represent important points in networks . Therefore , we first examined the essentiality of bottlenecks in different networks in yeast ( see Methods ) . We found that bottlenecks in both regulatory and interaction networks indeed tend to be essential proteins with high significance ( see Figure 2A ) , in agreement with previous studies [18 , 19] . As discussed above , previous studies have shown that , in biological networks , hubs tend to be essential [7 , 9] , and betweenness of a node is correlated with its degree [20] . We found that degree and betweenness are indeed highly correlated quantities in the networks we analyzed ( Pearson correlation coefficient of 0 . 49 , p < 10−15 for the interaction network; Pearson correlation coefficient of 0 . 67 , p < 10−15 for the regulatory network; p-values measure the significance of the Pearson correlation coefficient scores according to t distributions; i . e . , many bottlenecks also tend to be hubs ) . Therefore , we further investigate which one of these two quantities is a better predictor of protein essentiality in both regulatory and interaction networks . To disentangle the effects of betweenness and degree , we divided all proteins in a certain network into four categories: ( 1 ) nonhub–nonbottlenecks; ( 2 ) hub–nonbottlenecks; ( 3 ) nonhub–bottlenecks; and ( 4 ) hub–bottlenecks ( see Figure 1 ) . Even though the two quantities are highly correlated , the number of hub–nonbottlenecks and nonhub–bottlenecks is enough for reliable statistics ( see Table S1 ) . This is in agreement with the previous observation by Huang and his colleagues , who found that proteins with high betweenness but low degree ( i . e . , nonhub–bottlenecks ) are abundant in the yeast protein interaction network [18] . As we discussed above , numerous previous studies have shown that the degree of a protein determines its essentiality in scale-free networks ( i . e . , proteins with higher degrees are more likely to be essential ) [7 , 9] . Both interaction and regulatory networks have been shown to be scale-free networks [7 , 9 , 22] . Here , we observed that bottlenecks ( both nonhub–bottlenecks and hub–bottlenecks ) have a strong tendency to be products of essential genes , whereas hub–nonbottlenecks are surprisingly not essential . Thus , we determined that it is the betweenness that is a stronger determinant of the essentiality of a protein in the regulatory network , not the degree ( Figure 2B ) . In contrast to regulatory networks , the interaction network is undirected with no obvious information flow . Furthermore , nonneighboring pairs in the interaction network have no noticeable relationships , as they are neither coregulated nor coexpressed [23] . Therefore , it is reasonable to assume that in interaction networks , hubs are more important than bottlenecks . Our calculations confirmed this hypothesis ( see Figure 2B ) : although nonhub–bottlenecks are significantly more likely to be essential than nonhub–nonbottlenecks ( p < 10−5; see Methods for the calculation of p-values in Figures 2 and 3 ) , the difference is not nearly as substantial as that between hub–nonbottlenecks and nonhub–nonbottlenecks ( p < 10−267 ) . Similar results were also found in different interaction networks ( see Figure S4 ) . The difference between nonhub–bottlenecks ( low essentiality ) and hub–nonbottlenecks ( much higher essentiality ) confirms that degree is a much better predictor of essentiality in the interaction network . Signal transduction pathways are a special case of protein–protein interactions [24] . There are well-defined information flows in these pathways . Nonhub–bottlenecks participating in signaling transduction pathways clearly are more likely to be products of essential genes ( see Figure 3 ) . Besides directionality , another important but often overlooked aspect of interaction networks is that there are two major classes of interactions: permanent and transient [25 , 26] . Within permanent interactions , bottlenecks are connectors holding different , functionally important complexes together . However , within transient interactions , bottlenecks merely interact with different complexes at different times . In this sense , “transient” bottlenecks are not really bottlenecks . They are classified as “bottlenecks” by our algorithm simply because of the fact that current interaction networks are a collection of individual networks under various conditions . As a result , the function of these transient bottlenecks is likely to be not as important as that of permanent ones . Therefore , we hypothesized that bottlenecks would be more likely to be essential in permanent rather than in transient interactions . We tested our hypothesis in the yeast interaction network . Defining permanent interactions as those participating in protein complexes , we analyzed all complexes from the Munich Information Center for Protein Sequences ( MIPS ) complex catalog [27] . ( Previous studies have shown that most of the MIPS complexes are stable , permanent complexes . However , there are 52 proteins in this catalog without direct evidence of stable interactions with others [26] . We removed these proteins from our analysis . ) Because the catalog is far from complete , we also considered all interactions forming a clique ( a complete subgraph ) of size 5 or bigger as permanent , because protein complexes are often considered as cliques in interaction networks [28 , 29] . Any interaction not participating in a clique of size 3 or bigger was considered transient . Our calculations confirmed our hypothesis: nonhub–bottlenecks within permanent interactions tend to be essential , while those within transient ones do not ( see Figure 3 ) . For completeness , we also analyzed hubs and bottlenecks in other kinds of protein networks . Specifically , we analyzed the topology of three very different kinds of protein networks , namely the metabolic network ( where links connect enzymes that share a metabolite ) [23] , the genetic network ( where links connect proteins that have genetic interactions ) [30] , and the phosphorylation network ( where links connect a kinase with its substrates ) [31] . The edges in the phosphorylation and metabolic networks are directed , whereas those in the genetic network are undirected ( see Table S2 and http://www . gersteinlab . org/proj/bottleneck ) . The correspondence of protein interaction bottlenecks to connectors both in complexes and in pathways leads us to investigate their dynamic properties . To this end , we examined their coexpression with their neighbors . It has been previously observed that interacting protein pairs are more likely to coexpress than noninteracting protein pairs [32] . Likewise , protein complex members have been shown to be highly coexpressed [25] . Given this information , we hypothesized that bottlenecks would tend to have a below-average expression correlation with their neighbors , since they tend to represent proteins that connect different complexes or pathways . Indeed , in all the datasets examined , we find that bottlenecks have a much lower average expression correlation with their neighbors than other nodes . Surprisingly , the difference is much more pronounced when focusing on hubs only ( i . e . , the difference is more significant between hub–nonbottlenecks and hub–bottlenecks than between nonhub–nonbottlenecks and nonhub–bottlenecks ) . The majority of hub–nonbottlenecks are relatively well coexpressed with their neighbors , whereas most hub–bottlenecks are not very well coexpressed ( see Figure 4 ) . What appears especially striking is that bottlenecks always have low coexpression with their neighbors , whereas hubs can have a relatively high average coexpression with their neighbors , but only if they are nonbottlenecks . We find that while nonbottlenecks simply follow the same distribution as the rest of the datasets , the nonhub–bottlenecks tend to have a lower expression correlation . Central complex members have a low betweenness and are hub–nonbottlenecks . Because of the high connectivity inside these complexes , paths can go through them and all their neighbors . On the other hand , hub–bottlenecks tend to correspond to highly central proteins that connect several complexes or are peripheral members of central complexes . The fact that they have a high betweenness suggests that these proteins are not , however , simply members of large protein complexes ( which is true for nonbottleneck–hubs ) , but are those members that connect the complex to the rest of the graph; in a sense , real connectivity bottlenecks . While hub–nonbottlenecks mainly consist of structural proteins , hub–bottlenecks are more likely to be part of signal transduction pathways ( see Table S3 ) . Furthermore , hub–bottlenecks are ( by construction ) the most efficient in disrupting the network upon hub removal ( see Figure S3 ) . This relates nicely to the date/party-hub concept by Han et al . [21]: hub–bottlenecks tend to be date-hubs , whereas hub–nonbottlenecks tend to be party-hubs . Nonhub–bottlenecks generally coexpress less well with their neighbors than nonhub–nonbottlenecks , in line with the observation that betweenness is a good predictor of average correlation with neighbors . Nonhub–bottlenecks also rarely are complex members and are in large part made up of regulatory proteins and signal transduction machinery .
In this study , we find surprising links between network topology and both protein phenotype and expression dynamics . In analogy to the well-known network hubs , we examined the properties of so-called network bottlenecks in yeast . A first surprising finding is the distinction between interaction and regulatory networks in the relative importance of bottlenecks to hubs . While in most topological features , regulatory networks have been thought of as similar to interaction networks , we clearly see a distinction between those two network types that leads to a direct biological interpretation . Regulatory networks have directed edges; there is an implicit information flow within the network , which makes it more similar to the transportation system . A transcription factor ( TF ) can regulate many target genes indirectly through other TFs . Deletion of TF bottlenecks thus leads to the disruption of a large number of direct and indirect regulations between TFs and their targets and is lethal to the cell . For example , Swi1p is a nonhub–bottleneck TF required for sporulation and other cellular processes [33] . Swi1p is not a hub with only 23 targets . But , it is controlled by four TFs , and also regulates four others [34 , 35] . Because of this unique topological position , approximately 10 , 000 shortest paths between TFs and their targets within the whole regulatory network run through this gene , making it an important bottleneck . As a result , Swi1p is essential for viability in yeast [36] . On the other hand , protein–protein interaction networks have undirected edges; there is no obvious information flow within the network . Therefore , some people may even argue that in these interaction networks , betweenness , as well as the definition of bottlenecks , is more of a topological conceptualization from an abstract graph-theory point of view without clear biological meanings . Our calculations confirm accordingly that degree is a much better predictor of essentiality in interaction networks . More interesting , in some subnetworks within interaction networks where betweenness does have biological implications ( e . g . , subnetworks involved in signaling transduction or permanent interactions ) , protein bottlenecks indeed have a higher tendency to be essential . All of these correlations between topological measurements ( namely , degree and betweenness ) that we discovered here are quite intuitive if we carefully examine the topological meanings of these measurements and the biological interpretation of these networks . Moreover , our approach of focusing on nonhub–bottlenecks is useful for finding proteins that mediate different processes and are involved in cross-talk . An example is Cak1p ( see Figure 5 ) , which is a cyclin-dependent kinase-activating kinase involved in two key signaling-transduction pathways . It activates Cdc28p , an important regulator of the cell cycle . Cak1p also induces Smk1p , a mitogen-activated protein kinase involved in sporulation [37 , 38] . Besides these two proteins , Cak1p only has two other interaction partners ( YDR279W and Sgv1p ) , making its total degree 4 . Therefore , it is not a hub in the interaction network . However , since it coordinates two major signaling-transduction pathways , it is an important nonhub–bottleneck in the network with a high betweenness of 16 , 832 . 95 paths . Finally , due to its unique topological position in the network , CAK1 is an essential gene in the cell . More interestingly , it is also a close homolog of the human cancer gene CDK6 ( BLAST E-value < 10−10 ) . This example shows that bottlenecks potentially could be applied in various medical and pharmaceutical contexts to identify key proteins . Generally , the protein interaction network and gene expression data are generally viewed as independent . While there were several studies addressing correlations among them , they focused largely on local properties [32] . Likewise , while many studies addressed relations between the interaction network and protein function , they only make use of local network features , such as distance [39–42] . Here , we show that both coexpression and essentiality are highly correlated with a global network feature , betweenness . This finding lets us view the interaction network in a different light—some dynamic information is wired into the topology . This finding reinforces the “date-hub” and “party-hub” concept suggested by Han et al . [21] . It appears that the property of betweenness separates the bimodal distribution of average coexpression in hubs . Thus , the so-called date-hubs correspond mostly to hubs with high betweenness ( hub-bottlenecks ) , while the “party-hubs” correspond mostly to hubs with low betweenness ( hub–nonbottlenecks ) . This finding , however , implies relationships between dynamics and topological properties in the interaction network that were hitherto unknown . It is possible to argue that there is a certain level of noise in our interaction dataset , even though it is a highly reliable set [23 , 43] . To demonstrate that our results are not due to some specific noise in our dataset , we repeated all calculations on other high-quality interaction datasets ( namely , the filtered yeast interactome [FYI] [21] and the DIP core [44] ) as well . These different datasets all exhibit similar results ( see Figures S1 and S4A ) . Finally , a principal contribution of this paper is the consistent calculation of betweenness on directed and undirected graphs . We also performed our calculations on all currently available yeast protein networks with directed and undirected edges . Most of these networks are much smaller than the interaction and regulatory networks . So , calculating robust statistics is not currently possible , but we believe that as these other networks grow in size in the future , betweenness will prove to be a useful quantity for many protein networks , particularly those with directed edges . As described in Methods , we plan to regularly update our website ( http://www . gersteinlab . org/proj/bottleneck ) with betweenness calculations as these networks grow . In summary , we present an integrated analysis of two complementary topological network properties across different network types . This combined approach uncovers previously unknown connections between network topology , protein essentiality , and expression dynamics . We believe that integrated approaches like the one presented here will be of paramount importance in future predictive models .
Interaction data was gathered from a number of different published high-throughput datasets and published databases [2–5 , 27 , 34 , 45 , 46] . Independent genomic features and Bayesian integration were used to eliminate noise from the dataset [23 , 43] . Different datasets ( e . g . , the FYI [Vidal et al . ] [21] or the DIP core [Eisenberg et al . ] [44] ) exhibit the same behavior ( see Figures S1 and S4A ) . To avoid biases from large complexes ( i . e . , the ribosome and the proteasome ) , we repeated our calculations after removing both these complexes ( see Figures S2 and S4B ) . The regulatory network was created by combining five different datasets [1 , 2 , 22 , 34 , 35 , 47] . We excluded DNA-binding enzymes ( e . g . , PolIII ) from the regulatory network . The essential genes in yeast genome were determined experimentally through a PCR-based gene-deletion method [36] . The metabolic network was taken from the Kyoto Encyclopedia of Genes and Genomes ( KEGG ) [48] and all proteins that share a metabolite were considered linked . The genetic network data was downloaded from the GRID [49] and consists of several large-scale screens of genetic interactions [30 , 50] . Expression data was taken from the Rosetta compendium expression dataset [51] . All datasets and the calculated betweenness of each protein node within these networks are available at http://www . gersteinlab . org/proj/bottleneck . Because most of these networks are far from complete , we will update the networks and , more important , the associated betweenness of each node as they grow in size in the future . We defined hubs as all proteins that are in the top 20% of the degree distribution ( i . e . , proteins that have the 20% highest number of neighbors ) . Accordingly , we defined bottlenecks as the proteins that are in the top 20% in terms of betweenness . Varying this cutoff from 10% to 40% had no significant impact on our results ( see Figures S5–S7 ) . To calculate node betweenness within networks [16 , 52] , we used an improved version of the algorithm developed by Newman and Girvan . ( 1 ) Initialize the betweenness of every vertex v in the network Bv = 0 . ( 2 ) Starting from a vertex i , a breadth-first tree is built with i on the top and those that are farthest from i at the bottom [53] . Each node is put at a certain level of the tree based on its shortest distance from i . ( 3 ) A variable pi = 1 is assigned to i . As we are building the tree , for every vertex j , where K is the set of nodes that directly connect to j and are at the immediate proceeding level ( i . e . , predecessors of j ) . ( 4 ) Another variable bj , with an initial value of 1 , is also assigned to every vertex j in the tree . ( 5 ) Starting from a bottom vertex j , the value of bj is added to the corresponding variable of the predecessor of j . If j has more than one predecessor , each predecessor k gets the value of: Therefore: ( 6 ) Perform step 5 for every vertex in the tree . ( 7 ) For every vertex j in the tree , Bj = Bj + bj . ( 8 ) Repeat steps 2–7 for every vertex in the network . Qualitatively , proteins with high betweenness are considered as bottlenecks . To facilitate our calculations and discussion , however , we quantitatively defined bottlenecks as the top 20% proteins with the highest betweenness values , in agreement with the conventional cutoff for protein hubs [9] . Please note that for networks with directed edges , the directionality of the edges have to be taken into consideration . p-Values in Figures 2 and 3 measure whether the difference is significant between the testing and control groups . They are calculated using the cumulative binomial distribution: where N is the total number of genes in the data; co is the number of observed genes with a specific property ( e . g . , essentiality ) in the testing group; and p is the probability of finding a gene with the same property in the control group . In this manner , we are testing whether genes with a specific property are overrepresented compared with the control group . If they are underrepresented , then P ( c < co ) = 1 − P ( c ≥ co ) .
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A network is a graph consisting of a number of nodes with edges connecting them . Recently , network models have been widely applied to biological systems . Here , we are mainly interested in two types of biological networks: the interaction network , where nodes are proteins and edges connect interacting partners; and the regulatory network , where nodes are proteins and edges connect transcription factors and their targets . Betweenness is one of the most important topological properties of a network . It measures the number of shortest paths going through a certain node . Therefore , nodes with the highest betweenness control most of the information flow in the network , representing the critical points of the network . We thus call these nodes the “bottlenecks” of the network . Here , we focus on bottlenecks in protein networks . We find that , in the regulatory network , where there is a clear concept of information flow , protein bottlenecks indeed have a much higher tendency to be essential genes . In this type of network , betweenness is a good predictor of essentiality . Biological researchers can therefore use the betweenness as one more feature to choose potential targets for detailed analysis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"evolutionary",
"biology",
"saccharomyces",
"computational",
"biology"
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2007
|
The Importance of Bottlenecks in Protein Networks: Correlation with Gene Essentiality and Expression Dynamics
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Genome-wide scans of genetic variation can potentially provide detailed information on how modern humans colonized the world but require new methods of analysis . We introduce a statistical approach that uses Single Nucleotide Polymorphism ( SNP ) data to identify sharing of chromosomal segments between populations and uses the pattern of sharing to reconstruct a detailed colonization scenario . We apply our model to the SNP data for the 53 populations of the Human Genome Diversity Project described in Conrad et al . ( Nature Genetics 38 , 1251-60 , 2006 ) . Our results are consistent with the consensus view of a single “Out-of-Africa” bottleneck and serial dilution of diversity during global colonization , including a prominent East Asian bottleneck . They also suggest novel details including: ( 1 ) the most northerly East Asian population in the sample ( Yakut ) has received a significant genetic contribution from the ancestors of the most northerly European one ( Orcadian ) . ( 2 ) Native South Americans have received ancestry from a source closely related to modern North-East Asians ( Mongolians and Oroquen ) that is distinct from the sources for native North Americans , implying multiple waves of migration into the Americas . A detailed depiction of the peopling of the world is available in animated form .
According to current models , modern humans arose in Africa and spread around the world , with little or no genetic contribution from the hominid populations that they displaced [1] , [2] , [3] . Genetic diversity decreases progressively with land distance from East Africa [4] providing support for a “serial dilution” model in which diversity was lost progressively in sequential bottlenecks associated with small founder population sizes as new territories were colonized [5] , [6] . However , the good fit of serial dilution models might principally reflect recent admixture , which will tend to smooth diversity clines . Numerous questions remain about how many independent bottlenecks occurred as new continents were colonized , the exact land routes involved , and whether there have been genetically important migrations that do not conform to a model of progressive outward expansion [7] , [8] , [3] . Statistical inference of colonization history represents a considerable challenge . A reasonably detailed description would include ( 1 ) the times of major population splits , ( 2 ) the effective sizes of each distinct population and/or a list of major bottlenecks and ( 3 ) times of major admixture events , when previously distinct populations met and the contributions of the distinct populations to the new hybrid population . Even a complex population based history does not fully describe migration patterns , since isolation by distance can also be important . DNA is passed down through generations in linear segments whose boundaries are determined by meiotic crossovers . Modeling the segment-by-segment inheritance of genetic material is technically challenging even assuming simple demographic scenarios [9] . Adding modern and ancient population subdivision makes computations more complex and introduces the problem of choosing amongst a very large number of possible split and merger scenarios . We take an approach that models the segmental pattern of human inheritance and also allows comparison between numerous distinct historical scenarios . The approach is predicated on populations arising in an order that can be inferred from the data . For any given ordering of the populations in the sample , we use the copying-with recombination model of Li and Stephens [10] to reconstruct all of the chromosomes . Different orderings of the populations can be compared based on the overall likelihood of generating the entire set of chromosomes in the sample . Since all the data we analyze is from contemporaneous samples , the assumption of an ordering is incorrect if interpreted literally . However , under a serial dilution model , for example , it is natural to think of populations arising sequentially during radiation from Africa . Subseqent migrations and admixture have complicated this picture but a sufficient signal of these early events remains that the ordering our approach generates can for the most part be interpreted reasonably easily . For example , the “Out of Africa” bottleneck has left a signal of greater genetic diversity in Africans , both at the nucleotide [11] and haplotype levels [12] in the great majority of African and non-African populations , whatever their subsequent demographic history . One of the properties of the Li and Stephens model is that the likelihood of an ordering will generally be higher if the most diverse haplotypes are created first . Our analysis finds the same strong signal that is evident in the summary statistics of diversity; for the dataset of Conrad et al [12] the likelihood of generating two populations , one of which is African , is always higher if the African population is first . In addition to the order in which populations were founded , we would also like to learn about patterns of ancestry . For each new population , a subset of individuals from the previously formed populations is designated as a “donor pool . ” In the model , each new haploid genome or “haploid” is formed by copying chromosomal segments from the donor pool or from previously created haploids in the same population ( for notational simplicity we assume that every individual consists of two haploids that each contain one of the two copies of the 22 autosomes ) . The model allows different donor pool combinations to be compared according to the likelihood of generating all the chromosomes in the new population . The number of individuals from each population in the donor pool with the highest likelihood provides an indication of the relative importance of different ancestral sources . For convenience , we refer to the donors using the labels of the modern populations they come from , but they in fact represent surrogates for the shared common ancestors of the donor and recipient populations . The generation of individuals from a single population is illustrated for a hypothetical example in Figure 1 .
We tested our inference method using data simulated under a coalescent model [13] , [14] , with individuals sampled from five populations , labelled A-E , that were generated by sequential bottlenecks ( Figure 2- ( a ) ) . Parameters were guided by previous demographic estimates [15] , with the first bottleneck approximately corresponding to the “Out of Africa” event . In 10 independent realisations of the same scenario ( 5 with simulated recombinational hotspots , 5 without ) , the model correctly inferred both the order in which the populations were founded and which populations gave rise to each new one ( Figure 2- ( b ) ) and did not infer any additional , spurious sources of ancestry . We then complicated the model by giving populations D and E ancestry from two sources ( Figure 2- ( c ) ) . The model continued to infer the correct ordering for the formation of the populations and correctly identified the single sources for populations B and C and the two sources for population E in every case . However , in 7 of the 10 simulations , the ancestry of population D was inferred incorrectly , with the model either failing to include population A as an ancestor ( as shown in Figure 2- ( d ) ) , mistakenly including population B , or both ( Table S1 ) . We conclude that , at least for relatively simple scenarios , the model provides an accurate indication of historical relationships between populations but does not always correctly identify minority sources of ancestry , in particular when admixture is ancient . One potential confounding factor in SNP data is ascertainment bias . The SNPs that are chosen for genotyping are often ascertained based on a limited sample of individual who come from one or a small number of ethnic groups ( typically Europeans ) . For example , in the data of Conrad et al . , heterozygosity of the SNPs was actually highest in the Middle East , Central and South Asia and Europe , although these populations are known to be less diverse than Africans . Our method reconstructs haplotypes and therefore we expect it to depend principally on patterns of haplotype sharing and diversity , which a priori should be less sensitive to the ascertainment protocols of individual SNPs . Indeed , in the data of Conrad et al . , the haplotype diversity is highest in Africans [12] . In order to test for an effect of ascertainment bias , we performed inference in two extreme ascertainment schemes: one in which we selected SNPs for all populations based only on those that were heterozygous in population C , and one in which we selected SNPs for all populations based only on those that were heterozygous in population E . The former might represent ascertainment based only on European or Middle Eastern populations . The latter would represent an even more extreme and biased ascertainment , such as ascertaining SNPs using only native Americans . We used 10 of the simulations described above ( the ones without recombination hotspots ) . In 9/10 cases , results were not discernably different from those based on using all SNPs . In the remaining simulation , population B and C were swapped in the inferred ordering under both ascertainment schemes . We conclude that even extremely biased ascertainment has a modest effect on inference . Our results might also be confounded by the incomplete nature of the sample and by the many complexities of human population history . We have performed additional simulations in order to assess how complications to the scenarios shown in Figure 2 would affect inference . We first evaluated the effect of leaving a population out of the simulated datasets ( population D ) . For all four simulations ( two as illustrated in Figure 2-a , one with and one without recombination “hotspots , ” and two as illustrated in Figure 2-c , one with and one without recombination “hotspots” ) , population C was chosen as a significant donor population for E . Remaining inference was correct ( i . e . no other spurious donors were detected , and for the simulations illustrated in Figure 2-c , the model picked up the additional contribution from population B . ) This is what is expected: with the appropriate donor population missing , our model chooses as its replacement the population that contributed the majority of genetic material to the missing donor population . Complex patterns of admixture might considerably complicate inference . We modified the scenarios shown in Figure 2-a and Figure 2-c by adding recent admixture , either from D to C or from A to C . Examples are shown in Figures 3-a and 3-c . A genetic contribution from population D to C had little effect on inference in 10 different simulations ( Figure 3-d ) . These results show that “back admixture” , for example migrations into Africa , will generally not be detectable by our method . In this simulated example at least , the back admixture did not affect the rest of the inference . The effect of a recent contribution from population A to population C was more substantial . In 5/10 cases ( four for the scenario shown in Figure 3-a ) the inferred order of populations B and C were swapped ( Figure 3-b ) . The swapping of the populations leaves the genetic connections between the populations correct but inferences on which are sources and which are sinks are confused by the multi-layered migrational history . We used the same approach to infer the order of birth and ancestral sources of the 53 populations in the Human Genome Diversity Panel using the data from 2 , 540 linked SNPs across 32 autosomal regions genotyped by Conrad et al [12] . The highest likelihood scenario is shown in Figure 4 and Movie S1 . By visually inspecting these results , we have identified nine phases in the colonization of the world . This subdivision is subjective and the phases should not be thought of as occurring strictly in chronological order . For example , East Asia and Europe are peopled almost independently , making their relative position in the ordering nearly arbitrary . Furthermore , Melanesia has multiple sources that reflect ancient and recent migrations that introduced very distinct genetic material ( see [16] for a review ) . Its inferred place in the ordering reflects the most recent of these migrations . Nevertheless , the phases do reflect progressive outward expansion , analogous to that implied by serial dilution models . 1 . Sub-Saharan Africa . The first population in the ordering are the San , who are hunter gatherers that live in Southern Africa . Before the Bantu expansion over the last 3 , 000 years , the ancestors of the San occupied most of Southern Africa , but they have been progressively displaced and currently are restricted to a few pockets [17] . The San contributed ancestry to the next four populations ( the Biaka Pygmies , Bantu from South Africa and Kenya , and Mbuti Pygmies ) but none subsequent to that . The Bantu are inferred to have contributed to each subsequent African population . 2 . North Africa . The Mozabites are the only African population in the sample from above the Sahara . In our analysis , they are the 8th and final African population to arise and are also distinctive because they represent the first population that uses less donor individuals ( 46 from the Mandenka , Yoruba , and Kenyan Bantu ) than their predecessor the Mandeka , who used 64 donors from four populations . We interpret the smaller number of donors as evidence for a bottleneck in the history of the Mozabites , that is not shared by the other African populations in the sample . The small number of donor populations implies that only a subset of the human populations present at the time of the bottleneck contributed to the Mozabite lineage . 3 . Central Eurasia . There is no clear pattern to the order of colonization of central Eurasia , with the initial Central Asian populations ( Makrani , Uygur ) interspersed with those from the Near East ( Bedouin , Palestinians ) and the eastern edge of Europe ( the Adygei ) . All of these populations have Mozabites as donors , with the first three populations also using Kenyan Bantu . For these three , all 28 Mozabite individuals were used in generating each of the three populations , making it possible that some of the Bantu chromosomes would have been replaced by additional Mozabites or other North or East Africans if they were present in the sample . Overall , non-African populations can each trace approximately 3/4 of their ancestry via the Mozabites ( Movie S2 , Table S4 ) . The total number of donors increases progressively from 39 for the Makrani to 141 for the Adygei . The high interconnectedness of these populations presumably reflects the absence of region-specific bottlenecks and/or multiple episodes of gene flow between Eurasian populations subsequent to the initial colonization event ( s ) . 4 . Central Europe . Aside from the Adygei , the first European populations to arise are the French , Tuscans , and Italians . These three populations have an average of 260 donors , including those from the Mozabites and several Near Eastern and Central Asian populations . This is a larger number than for any non-European population in the sample and highlights the diverse sources of European ancestry . 5 . Pre-Han East Asia . The first 8 East Asian populations ( Cambodia , Mongolia , Oroqen , Xibo , Yi , Tu , Daur , Naxi ) have 50-84 donors , including all 32 individuals from two central Asian populations , the Uygur and the Hazara ( except the Tu who use 24/32 ) . This represents an entirely distinct source of ancestry from European populations , who each receive less than 10% of their ancestry via the Uygur and almost none via the Hazara ( Movie S2 , Table S3 ) . The only other external donors are the Pathan ( contributing 12 chromosomes to Mongolians ) and the Burusho , Sindhi and Mozabites , who contribute 23 , 15 , and 4 donors to the Cambodians respectively . We interpret the paucity of donors and the consistence of ancestry patterns as evidence for a single East Asian bottleneck . 6 . The extremities of Europe . The final four European populations ( the Sardinians , Russians , Orcadians and Basque ) all lie on the extremities of the continent . As well as having many European donors , these populations also have a large number from the Near East and Central Asia , consistent with Europe absorbing multiple waves of migrants . The Russians have 375 donors , more than for any other population , including from the Yi , Tu , and Mongolians , indicative of admixture with Far-Eastern populations . The Basque have 4 Hezhen donors but are otherwise similar to other Europeans . 7 . The Han expansion . The Han receive their ancestry exclusively from other East Asian populations ( including the more westerly Xibo ) and represent a principal source of ancestry for several subsequent populations that also have principally East Asian ancestry ( She , Japanese , Dai , Lahu , Han from Northern China , and Miao ) . 8 . The Americas . The Colombians are the first Amerind population . 47% of their ancestry can be traced via the Hazara , which is marginally less than typical East Asian populations such as the Han ( 54% ) or Xibo ( 59% ) ( Movie S2 , Table S3 ) . However , within the descendents of the putative EastAsia bottleneck , their donor pool is diverse , implying that none of the populations in the sample provides a good proxy for the original group or groups that crossed the Bering straight . The Colombians also have French donors , which may reflect post-Colombian admixture . The second American population , the Pima , represents the first North American population . As well as using all 7 Colombians as donors , it uses 8 Mongolians and 4 Oroquen . Neither of these populations acted as donors to the Colombians , suggesting distinct colonization events from different sources . Subsequent American populations did not have any non-Amerind donors , except for the Mayans who have Bantu and Tuscan donors , presumably due to post-Columbian admixture [18] . 9 . Pacific Islands . All but two of the East Asian populations that donate to the Colombians also donate to the Melanesians , and the Japanese are again the most numerically important with 20 donors . However , the Melanesians have several additional sources of ancestry . These include three populations which are products of the East Asian bottleneck ( Oroquen , Han , and Pima ) , in addition to Central Asian populations ( Burusho and Brahui ) and Russians . Three Mozabite donors are also estimated , which falls slightly below our conservative threshold for significance ( Methods ) . In total , the Melanesians trace 38% of their ancestry via the Hazara , which is less than East Asian or Amerind populations and implies independent sources of ancestry . The Papuans receive ancestry only from Melanesians and Cambodians , suggesting a shared common bottleneck . One concern for this dataset is that the number of individuals varies widely among populations ( from 6 to 45 ) . We investigated whether this might have a substantial effect on our results by correlating the number of individuals in each population with both its position in the inferred ordering ( Figure S1 ) and the total number of donors it received ( Figure S2 ) . Using simple linear regression , no strongly significant correlation was found in either case ( p-value > 0 . 05 ) .
In our inferred scenario , Pima are the first North American population in the ordering and receive ancestry from the first South American population , the Colombians . The Pima have two additional donor populations , the Oroquen and Mongolians , both of whom reside in Mongolia and neither of which are donors to Colombians . This result is intruiging because it suggests independent sources for North and South Americans and hence multiple waves of migration into the continent , contradicting the current consensus based on available data [23] . We tested the robustness of this inference by swapping the two populations in the ordering and re-inferring donors using the same protocol . The Pima replaced their Colombian donors with a small number of East Asians who were donors to the Colombians ( 4 donors each from Naxi and She ) , but the Mongolians and Oroquen remained majority donors . This result mirrors what is found in our simulations; if a donor population is missing ( or also present in insufficient numbers in the sample ) then it will typically be replaced by one or more of its own donors . The Colombians gained the Pima and lost a substantial number of other donor populations , but kept several from populations that did not contribute to the Pima in either ordering ( Daur , Hezhen , Xibo and Burusho ) . These results are consistent with substantial gene flow between North and South America but also imply that these have not been strong enough to overwhelm a clear signal of independent colonization . These results also suggest a geographically and historically very plausible scenario: The populations colonizing North East Asia whose members crossed the Bering Strait and whose descendents eventually reached South America were replaced by a population more closely related to modern East Asians ( and specifically modern Mongolians ) . This population subsequently also crossed the Bering Strait and contributed substantially to the ancestry of North American Amerinds . This second wave of migration provides an explanation for the relationship between distance from Siberia and genetic similarity to Siberians [23] , which was previously attributed to serial dilution [23] . It also explains why an analysis of the population structure of the Pima and two South American populations based on genome-wide SNP data , using the admixture model of STRUCTURE [24] , inferred that the South American populations had a single source of ancestry but the Pima had received approximately half of their ancestry from a second , additional source [25] . Simulation results have shown that the admixture model of STRUCTURE can be surprisingly successful in detecting ancient admixture , even in the absence of source populations , if the number of markers used is sufficiently large [26] . In our inferred scenario there is little gene flow between East Asian and Europeans and the Yakut is the only East Asian population to have two European donors; the Russians and the Orcadians . The Russian contribution is not surprising because the Yakut live in North East Russia . The Orcadian contribution is particularly noteworthy because removing these donors reduces the log-likelihood of generating the Yakut chromosomes by 2 . 5 times more than removing donors from any other population ( Table S2 ) . The Orcadians are also the only other European population to donate to other East Asians , namely the Han from Northern China and the Hezhen , who are also amongst the most Northerly East Asian populations in the sample . On this basis we hypothesize that there has been an episode of gene flow from Europe to East Asia . We tested the robustness of this inference by putting Orcadians last in the ordering . The Yakut replaced the Orcadians with Sardinians , who are a major donor to the Orcadians . The Hezhen and the Han from Northern China did not acquire new European donors , consistent with the gene flow from Europe being less quantitatively important to these two populations than to the more Northerly Yakut . Orcadians did not gain any East Asian donors by being placed last in the ordering , strengthening the inference that the direction of the gene flow was from Europe to East Asia . Our results provide evidence for two continent-scale bottlenecks , the first affecting non-Africans and the second affecting East Asians , with both groups having a small number of donors from outside the region . Unfortunately , the limitation of both our method and the sampled populations make it difficult for us to make detailed inferences about the nature of these bottlenecks . Most of the ancestry of non-Africans comes via the only only North African population in the sample , the Mozabites , who are also the last African population to be formed . However , their intermediate position might reflect back migration from the Middle East and/or Europe[27] , [28] , [29] . Simulation results suggest that our method is likely to miss this type of back admixture . Indeed , if Mozabites are allowed to receive ancestry from any populations and not only those that precede them in the ordering , they get approximately 70% from these two regions , consistent with the results of STRUCTURE for the same populations [30] . In any case , a much better sample of East and North African populations would be required to elucidate the nature of the bottleneck . A similar problem of interpretation occurs for the East Asian bottleneck . A majority of the ancestry of East Asians comes via two central East Asian populations , the Uygur and the Hazara . However these populations could have come to resemble East Asians through back migration . Indeed , if these populations are placed last in the ordering , then more than 40% of their donors are East Asian . If donors for the East Asian populations are inferred while excluding the Uygur and the Hazara from the dataset , the first populations have a somewhat larger number of donors from a wider range of Central or West Asian populations ( Brahui , Makrani , Balochi , Sindhi and Adygei ) than shown in Movie S1 , but populations later in the ordering revert to having predominantly East Asian donors , supporting a strong East Asian bottleneck that contrasts with the wide sources of ancestry of Europeans . The major simplification of our model is to assume that the populations were founded in an order . Since the DNA samples came from living humans , the ordering does not reflect age , but instead bottlenecks and admixture events that distinguish more recently formed populations from older ones . Complexities in human history make this ordering somewhat arbitrary . For example , the Melanesians have been founded by multiple waves of migrations . Their position late in our ordering reflects the substantial proportion of their ancestry that comes from East Asians . However they also have other , independent sources of ancestry that reflect migrations that are likely to predate those that gave rise to the modern East Asian populations . Information on the timing of different waves of migration could potentially be obtained from more extensive DNA sequence datasets by examining the sizes of the blocks of DNA that are inherited from different donor populations . Recent admixture would result in individuals sharing large contiguous segments from particular donor populations [26] , [31] . Recent shared ancestry would result in individuals receiving large contiguous segments from particular donor haploids . A fully realistic history would avoid any ordering of the modern populations . One potential avenue for extending the current approach to achieve this goal would be to impute chromosomes from “ancestral populations , ” which would both represent populations that existed in the past and also act as efficient donors for the modern haplotypes . Generation of such populations poses a number of statistical and computational challenges but could potentially allow a chronological , multi-layered history to be inferred . Accurate reconstruction of historical migrations depends crucially on the use of appropriate samples and any geographical interpretation can be confounded by major population movements . Further , it should ideally be demonstrated that the results are robust to which parts of the genome are used in analysis . Further methodological innovation and genome-wide SNP datasets from diverse human populations [25] , [32] should allow unprecedented detail in the reconstruction of the ancestry of extant humans .
We used the 32 autosomal regions in Conrad et al [12] , each of which consisted of approximately 80 biallelic SNPs across 330 kilobases of the genome . SNP data were collected for a total of 927 individuals sampled from 53 different populations , with sample sizes ranging from 6 to 45 individuals per population . Data were kindly provided to us as haplotypes , which were phased using fastPHASE [33] on each region as previously described [12] . Li and Stephens [10] described a likelihood based model that captures the principal features of the genealogical process with recombination while remaining computationally tractable for large datasets . Under the model , the chromosomes are generated in order , with chromosomes being copied segment-by-segment from those earlier in the ordering . In our notation , every individual consists of two haploids , each consisting of a single phased haplotype per genotyped region . The L total SNPs in each haploid are listed one region at a time , in order within each region . Suppose that we wish to generate a particular haploid h* , using j pre-existing donor haploids h1 , … , hj . Let ρ represent the crossover recombination rate per unit physical distance across the genome , assumed fixed . The conditional probability Pr ( h* | h1 , … , hj; ρ ) is structured as a Hidden Markov model , where the hidden state Xl represents the existing haploid from the set h1 , … , hj that haploid h* copies from at each site l = 1 , … , L . The switches in copied-from haplotype are modelled as a Poisson process with rate ρ/j . The transition probabilities for X between sites l and l+1 are as follows: ( 1 ) where dl is the physical distance between SNPs l and l+1 . If l and l+1 are on separate genetic regions , we set dl = ∞ . The observed state sequence component of the Hidden Markov Chain , the probability of observing a particular allele given the haploid that h* is copying from at a given SNP , allows for “imperfect” copying that depends on a per site mutation parameter : ( 2 ) Here hj , l refers to the allelic type of haploid j at SNP l . The mutation parameter is fixed , as in [10] , as Watterson's estimate with one expected mutation event per site , i . e . [34] for J total haploids . To calculate Pr ( h* | h1 , … , hj; ρ ) , a summation is performed over all permuations of the copying process , i . e . a summation over all possible x , which can be accomplished efficiently using the forward algorithm ( e . g . [35] ) . In the analyses presented here , we used an alteration of ( 1 ) above , using the “PAC-B” version described in [10] . Note that the probability of recombination events ( i . e . switches ) and mutations goes down as the number of haploids j increases . This mirrors a key property of data generated under the coalescent , that the probability that a segment from an additional chromosome will be identical by descent with a segment from chromosomes 1…j increases with j . This property also means that different orderings will have different likelihoods that at least in part reflect the demographic history of the individuals in the sample . For example , if a subset of individuals in the sample have a particularly high level of diversity , then the overall likelihood will generally be higher if these individuals are generated early rather than late in the ordering . In previous implementations of the Li and Stephens algorithm , it has been assumed that each new haplotype is made using all previous haplotypes . This leads to the formula for the probability of observing J haploids , conditional on ρ: ( 3 ) where as in [10] . However , in the context where individuals come from differentiated populations , a higher likelihood may be obtained by using only a subset of the pre-existing individuals as donors . In order for a donor individual to increase the likelihood of generating h* , there needs to be chromosomal segments , whether large or small , that are more similar to h* than any of the others in the donor pool . Individuals from populations that are more differentiated from h* than others in the donor pool are likely to contain few such segments . Further , every individual increases the value of j by 2 , and for each segment that is copied a 1/j term appears in the likelihood , corresponding to choosing amongst the j donor haploids . Thus the presence of differentiated individuals in the donor pool can decrease the overall likelihood . Here we are interested in investigating ancestry at the population level . We therefore make some assumptions about orderings and donors that are justifiable if the individuals within each population share the same demographic history . In practice , population labels are initially defined based on geographic and ethnic criteria , and the degree of homogeneity within the labelled populations can be assessed on multilocus genetic data [18] . These assumptions considerably reduce the computational complexity of the problem . Within each population , haploids are assumed to be generated – and donors are used in generating them – in the order they appear in the input file . In generating a set of haploids H across K populations , we further assume that: 1 . The K populations are generated in sequence according to an order of colonization U = ( u1 , … , uK ) , where uk denotes the kth population in the order . To simpify notation , we subscript each population by its position in the ordering , with 1 representing the initial population and K the final population to be colonized . 2 . Each population k has a fixed set of donor individuals from previous populations in the order , Dk . The membership of Dk is determined by k−1 integers , , reflecting the number of individuals from previous populations 1 , … , k−1 that donate genetic material to population k . 3 . Within a population k , haploids are made in order using the previous haploids as donors , i . e . for , the ith haploid genome of population k , the total donor pool . 4 . The formation of each population k involves a single genome-wide recombination rate , ρk . Let represent the number of donor individuals from populations 1 , … , K−1 for each of populations 2 to K , and let Φ = ( ρ1 , … , ρK ) denote the set of recombination rates involved in forming all populations K . Then the probability of the haploid data of all populations , H , conditional on U , M , and Φ , is: ( 4 ) where nk denotes the number of individuals in population k . We want to maximise ( 4 ) across all possible orderings of populations , donor sets and recombination rates . This represents a very large search space . We used a hill climbing approach and some MCMC updates to find a good solution . We first set out to generate an inital order of colonization , U ( 0 ) , using a pairwise analysis . For each of the K ( K−1 ) permutations of pairs of populations , we calculated the probability of forming all haploids in both populations using ( 3 ) . Specifically , for each pairwise combination , we calculated ( 3 ) twice , once using a haploid ordering where all of one population's haploids are formed first and the other where they are formed last . For each calculation , we maximized over ρ using 200 iterations of Markov Chain Monte Carlo ( MCMC ) . In particular , for each MCMC iteration r , a new proposal of log10 ρ , log10ρ ( r ) , was selected from a uniform ( −1 , 1 ) distribution shifted to be centered on the previous value of log10 ρ . This new value of ρ was then accepted or rejected via a Metropolis-Hastings step , i . e . ρ ( r ) was accepted with probability min ( a1 ) , where , or otherwise rejected . ( Here we take a uniform prior on log10 ρ between −7 and 3 . ) We compared the final probability values at r = 200 for each of the two orderings , awarding 1 point to the population that was first in the highest likelihood ordering . Our initial ordering U ( 0 ) was based on the number of points received by each population , with the highest scoring population considered the first population formed . Ties were broken randomly; in the data of Conrad et al [12] , there were nine instances where two populations had the same number of points and two instances where three populations had the same number of points ( Table S5 ) . We calculated the likelihood for U ( 0 ) and for subsequent orderings using a greedy algorithm for each k to obtain values of M and Φ . For each k , first ( 4 ) was evaluated using all possible individuals as donors , i . e . , maximizing over ρk using 200 iterations of MCMC as described above , giving . Next , the change in the likelihood obtained by setting , fixing , was evaluated for each for which . If each of these changes decreased the likelihood , the algorithm stopped . Otherwise , for the p which resulted in the highest increase in likelihood , was set to 0 and ρk was re-maximised conditional on this new value of Dk using a further 200 MCMC iterations , and the algorithm continued . We used an iterative procedure to obtain orderings with progressively higher overall likelihood . Specifically , for each , we calculated the likelihood of the ordering U* = ( u1… , uk+1 , uk , … , uK ) . In each iteration , we accepted all changes in ordering that increased the likelihood or left it the same , the only exeptions being where two or more such changes were incompatable with each other . In these cases , we accepted those changes that improved the likelihood the most . This procedure was repeated until the changes either decreased the likelihood or reversed a change that had previously been made . For the data of Conrad et al [12] , 13 such iterations were performed , providing the ordering U ( 13 ) ( Table S5 ) . The overall log-likelihood improved by 344 in these 13 iterations . For the simulated data , no changes in ordering were accepted . For the data of Conrad et al [12] but not the simulated data , we performed an analogous procedure to generate U ( 14 ) but comparing all possible conFigure urations of triplets of orderings , i . e . U* = ( u1 , … , uk , uk+1 , uk+2 , … , uK ) , U* = ( u1 , … , uk , uk+2 , uk+1 , … , uK ) , U* = ( u1 , … , uk+1 , uk+2 , uk , … , uK ) , U* = ( u1 , … , uk+1 , uk , uk+2 , … , uK ) , U* = ( u1 , … , uk+2 , uk , uk+1 , … , uK ) , and U* = ( u1 , … , uk+2 , uk+1 , uk , … , uK ) . We accepted 4 such changes , improving the log-likelihood by a further 67 . We then recalculated new optimal values of ρk for this ordering , which improved the log-likelihood by a further 60 , and checked pairwise population swaps based on these new values . None of the proposed swaps increased the likelihood further , so this gave us our final ordering ( Table S5 ) . The greedy algorithm assumes that for each population k , the preceeding populations contribute either all or none of their chromosomes to the donor pool Dk . In order to find a solution which allowed fractional contributions from donor populations , we used an MCMC approach , conditional on this final ordering and final values of ρk , . Let be the donor pool at iteration r , with the number of donor haploids from population p to population k at iteration r . Initially , we set for all and . We then performed the following steps at each iteration r = 1 , … , R: 1 . randomly choose one of k's donor populations 1 , … , ( k−1 ) with uniform probability; call this population p 2 . randomly choose with uniform probability 3 . if r is an even number , set 4 . if r is an odd number , set 5 . if or then reject the change , i . e . . 6 . Otherwise , accept the change with probability min ( a , 1 ) , where . For both the simulated data and our application to the data of Conrad et al [12] , contributions were deemed significant if the average number of donors exceeded 2 . For our simulated data , we used the results of a single MCMC run with 5 , 000 iterations , including 1 , 000 Burn-in iterations . For the data of Conrad et al [12] , different MCMC runs converged on slightly different local optima , as a result of the complexity of the search space . We therefore used a consensus of the results of the greedy solution and two independent MCMC solutions . For each MCMC run , we initially ran the algorithm for 10 , 000 iterations , including 2 , 000 iterations of burn-in . In 17 cases ( both runs of Japanese , Lahu , Maya , Pima and Papuan and one run of Dai , Italian , Sardinian , Surui , Tujia , Karitiana and She ) the algorithm initially got stuck in a local optimum but then jumped to a significantly better solution ( >30 improvement in log-likelihood ) after the burn-in was complete . We therefore continued the run for a further 10 , 000 iterations , using the last 8 , 000 to estimate the posterior . In each of these 17 instances no further large improvement in likelihood occurred during these 10 , 000 iterations , indicating convergence on a local optimum . The consensus ( Table S2 ) included donor populations that were significant in at least two of the three solutions and for which the number of donor individuals , averaged across the three solutions , was also greater than 4 .
To test our method's performance under simple demographic scenarios , we performed several sets of simulations using the coalescent-based simulation software msHOT [14] , [13] . In particular , we performed simulations under a sequential bottleneck model , using five populations and four bottleneck events ( Figure 2 ) . We performed simulations for two different scenarios , as shown in Figure 2-a and Figure 2-c . For both scenarios , the population size of A beyond t = 3500 generations is 10 , 000 chromosomes , bottleneck size is 2 , 000 for the initial colonizations of each of B-E , and present-day population size is 25 , 000 for A-E . In the simulatons with admixture , D has 75% contribution from C and 25% from A; E has 75% contribution from D and 25% from B . The number of sampled individuals ranged between 6 ( for population A ) and 45 ( for population B ) . This range was chosen to match that found in the data of Conrad et al [12] . For each scenario , we performed ten independent simulations . In each we simulated 32 genetic regions of size ≈330kb and 80 SNPs for each population . We considered two different models of recombination ( five simulations under each model ) . The first model consisted of a constant recombination rate ρsim across all 32 regions , with ρsim = 1 . 0/kb . Here ρsim = 4N0c , where c is the rate of crossover recombination as before and N0 is the present-day population size of each population , i . e . N0 = 25000 . This rate closely matches the observed average rate of recombination in humans , assuming a present-day population size of 25 , 000 . The second model included recombination hotspots , or narrow areas of the genome with intense recombination activity relative to the surrounding region . For the latter recombination model , hotspot parameters were chosen to mimic current observations on typical hotspot characteristics [36] , [37] , [38] , [39] . The number of hotspots was selected from a Poisson distribution such that they occured genomewide every 40kb on average . Each hotspot's width in kilobases was sampled from a uniform ( 1 , 2 ) . Its intensity λ , or relative rate of recombination compared to regions outside of hotspots , was sampled such that log10λ∼Uniform ( 1 . 0 , 2 . 5 ) . This intensity distribution restricts hotspots to have recombination rates between 10-316 times that of background rates , with 50% of hotspots expected to have intensities between 10 and 32 . Outside of hotspots , the rate of recombination in all regions was fixed at ρsim = 0 . 2325/kb . Finally , we imposed an additional restriction that hotspots had to be at least 5kb apart in a region . These parameters resulted in a genomewide average recombination rate of ≈1 . 0/kb , with 15 maximum hotspots per region and roughly 78% of the total recombination occuring in the 3 . 7% of the sequence genomewide designated as hotspots . These numbers match – or are slightly more extreme than – current observations [38] . After simulating the haplotypes for each region based on the above parameters using msHOT , SNPs were randomly chosen to mimic allele frequencies present in the data of Conrad et al [12] in the following manner . The 0th , 10th , … , 90th , and 100th quantile values of SNP allele frequencies for all populations combined were found for the Conrad et al [12] data across all regions . SNPs were then selected in the simulated data such that , for 80 total SNPs per region , ≈10% were between the 0 and 10th quantile values of the real data , ≈10% were between the 10th and 20th quantile values of the real data , etc . Histograms of the allele frequencies of our simulated data after ascertaining in this manner were roughly comparable to that of the data of Conrad et al [12] ( data not shown ) . The data we analyzed consisted of haplotypes estimated by the authors of Conrad et al [12] using the program fastPHASE [33] . Therefore we used fastPHASE to estimate the haplotypes of our simulated data after selecting SNPs based on the ascertainment strategy described above . That is , we pretended the haplotype information from the msHOT simulations was unknown and phased the genotype data using fastPHASE v . 1 . 2 . 0 on each region , for each of the five simulated populations separately . We used roughly the same fastPHASE parameters as [12] , using H = 500 , T = 20 , and C = 25 , with K = 20 clusters for populations with more than 40 haplotypes and K = 10 clusters otherwise ( see the fastPHASE documentation for a full description of these parameters and [12] for a full description of their phasing strategy ) . For the scenarios with recent forwards or backwards admixture , recent admixture was added such that 0 . 25% of the “sink” population was comprised of new migrants from the donor population each generation , starting 20 generations ago and continuing until present-day . Otherwise the simulations were the same as those based on Figure 2-a and Figure 2-c described above ( five for each under each recent admixture scenario ) , without recombination hotspots .
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Humans like to tell stories . Amongst the most captivating is the story of the global spread of modern humans from their original homeland in Africa . Traditionally this has been the preserve of anthropologists , but geneticists are starting to make an important contribution . However , genetic evidence is typically analyzed in the context of anthropological preconceptions . For genetics to provide an accurate and detailed history without reference to anthropology , methods are required that translate DNA sequence data into histories . We introduce a statistical method that has three virtues . First , it is based on a copying model that incorporates the block-by-block inheritance of DNA from one generation to the next . This allows it to capture the rich information provided by patterns of DNA sharing across the whole genome . Second , its parameter space includes an enormous number of possible colonization scenarios , meaning that inferences are correspondingly rich in detail . Third , the inferred colonization scenario is determined algorithmically . We have applied this method to data from 53 human populations and find that while the current consensus is broadly supported , some populations have surprising histories . This scenario can be viewed as a movie , making it transparent where statistical analysis ends and where interpretation begins .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods",
"Simulations"
] |
[
"evolutionary",
"biology/human",
"evolution",
"genetics",
"and",
"genomics"
] |
2008
|
Inferring Human Colonization History Using a Copying Model
|
The ability of any organism to sense and respond to challenges presented in the environment is critically important for promoting or restricting colonization of specific sites . Recent work has demonstrated that the host metabolite D-serine has the ability to markedly influence the outcome of infection by repressing the type III secretion system of enterohaemorrhagic Escherichia coli ( EHEC ) in a concentration-dependent manner . However , exactly how EHEC monitors environmental D-serine is not understood . In this work , we have identified two highly conserved members of the E . coli core genome , encoding an inner membrane transporter and a transcriptional regulator , which collectively help to “sense” levels of D-serine by regulating its uptake from the environment and in turn influencing global gene expression . Both proteins are required for full expression of the type III secretion system and diversely regulated prophage-encoded effector proteins demonstrating an important infection-relevant adaptation of the core genome . We propose that this system acts as a key safety net , sampling the environment for this metabolite , thereby promoting colonization of EHEC to favorable sites within the host .
Escherichia coli is an extremely diverse Gram-negative bacterial species , commonly establishing itself as a commensal member of the microbiota early after birth in healthy humans and animals [1] . However , owing to a large degree of genome plasticity , numerous pathogenic forms of E . coli dubbed ‘pathotypes’ have emerged and can be classified broadly according to the site of the body in which they cause infection [2–4] . Pathotypes largely associated with enteric illness include enterohaemorrhagic E . coli ( EHEC ) , enteropathogenic E . coli ( EPEC ) , enteroaggregative E . coli ( EAEC ) , enterotoxigenic E . coli ( ETEC ) , enteroinvasive E . coli ( EIEC ) and diffusely adherent E . coli ( DAEC ) , which are responsible for varying degrees of diarrheal disease by unique mechanisms . Extraintestinal pathogenic E . coli ( ExPEC ) colonise and compete in the gastrointestinal tract but have the capacity to disseminate to distal sites . Mostly notably these include urinary tract pathogenic E . coli ( UPEC ) and the lesser-explored meningitis associated E . coli ( MNEC ) [4–6] . Classically , tropism to a particular site has largely been attributed to the specificity of bacterial adhesins to host receptors . Arguably the best example is Type 1 fimbriae , responsible for binding to D-mannose residues on mucosal cells that are central to UPEC adhesion and virulence [7] . However , receptor complement varies and adhesins are often highly immunogenic and therefore their production is a tightly regulated process [8] . Recent work has highlighted the importance of host metabolites in modulating the expression of bacterial colonization factors at sites of infection [9] . EHEC ( most notably the O157:H7 serotype ) is an aggressive food-borne isolate that primarily colonizes the terminal rectum of ruminants asymptomatically and the large intestine of humans , resulting in haemorrhagic colitis from very low infectious doses and in extreme cases can cause fatal haemolytic uremic syndrome [10 , 11] . Fucose , a major component of mucin glycoproteins and abundant energy source in the large intestine , is sensed by EHEC using a two-component sensory system , FusKR , which in turn affects both virulence gene expression and colonization [12] . Similarly , ethanolamine a major component of both bacterial and mammalian cell membranes is not only important for nitrogen metabolism but is also used as a molecule in cell-to-cell signaling to activate virulence gene expression in the gastrointestinal tract [13] . The presence of particular metabolites has also been reported to act as repressive signals that limit colonization in unfavorable environments . Biotin , an essential co-factor found in abundance in the small intestine , has been recently shown to inhibit EHEC colonization at this site by modulating global gene expression thus promoting passage towards the large intestine where EHEC favorably colonizes and where biotin concentrations are much reduced [14] . These studies demonstrate an emerging understanding of how specific pathotypes sense and respond to the minutiae of conditions present at various sites encountered within the host whilst highlighting the mechanistically diverse nature of this process . Colonization of EHEC is mediated by a type III secretion system ( T3SS ) encoded on a large pathogenicity island ( PAI ) known as the locus of enterocyte effacement ( LEE ) . The LEE-encoded T3SS allows intimate attachment to host cells mediating the attaching and effacing ( A/E ) phenotype , a hallmark of LEE-associated pathogens [15] . The EHEC LEE encodes 41 open reading frames ( ORFs ) mostly across five polycistronic operons , named LEE1 through LEE5 [16] . As well as encoding the necessary machinery and primary effectors of this T3SS , the LEE also carries two master regulatory systems that control LEE expression at the core level–the LEE encoded regulator ( Ler ) and the global regulator of Ler activation ( GrlA ) [17–20] . Key research investigating physiologically relevant signals that EHEC encounter during infection has revealed the LEE as a hub for environmental sensing and thus control of colonization within the correct niche [9] . We recently reported that the host metabolite D-serine could selectively inhibit expression of the LEE-encoded T3SS in EHEC [21] . D-serine is a metabolite found in abundance at various extraintestinal sites in the human body , including the urinary tract and the brain , and modulates virulence gene expression of ExPEC such as the UPEC strain CFT073 whilst also being used as a carbon source [22–24] . This is achieved by the conversion of D-serine to pyruvate and ammonia via the D-serine tolerance locus , dsdCXA [25 , 26] . This locus is truncated however in many intestinal strains of E . coli resulting in an inability to metabolize D-serine and rendering them susceptible to the toxic effects of this amino acid [27] . Intriguingly , we found that the ability to metabolize D-serine did not alleviate inhibition of the LEE , thus separating the virulence and metabolic phenotypes and offering an explanation as to why EHEC isolates have not acquired this pathogenicity island [21] . Our results suggested that acquisition of the LEE is a key factor in restricting the individual to the intestinal tract where inhibitory molecules such as D-serine are in sub-inhibitory abundance and is an example of niche adaptation for this pathotype . D-serine represses virulence through modulation of the LEE transcriptional network [21] . However , the precise mechanism by which D-serine was specifically sensed by EHEC remained obscure . In this study we have identified a D-serine sensory locus . This system includes a D-serine inner membrane transporter , YhaO , and a LysR-type transcriptional regulator , YhaJ , that are both required for full virulence in EHEC . We reveal that YhaO is a functional D-serine transporter in both EHEC and UPEC but is regulated uniquely in each background , and that YhaJ is required for its expression under LEE-inducing conditions ( growth in MEM-HEPES at 37°C ) . Furthermore , we demonstrate that YhaJ directly regulates Ler expression by enhancing activation of the major LEE promoter . These genes are highly conserved across the E . coli phylogeny but this work demonstrates the adaptive capacity of the E . coli core genome towards new and important functions . We propose that YhaO has been recruited by EHEC upon acquisition of the LEE to maintain an active response system capable of transporting and sensing environmental D-serine , thus ensuring appropriate colonization factor expression and in turn , niche specificity of this pathotype .
Our previous work had identified D-serine as a key host metabolite affecting EHEC colonization and niche specificity [21] . However , how D-serine was sensed by EHEC remained an unanswered question . Exposure to D-serine results in activation of the SOS stress response and repression of the LEE-encoded T3SS . Based on this aforementioned data , we postulated a sensing mechanism would be co-expressed with the LEE to facilitate detection of environmental D-serine during colonization of host tissue . Investigation of published microarray data during growth in MEM-HEPES ( that induces maximal LEE expression in vitro ) revealed genes that were co-regulated with the LEE [28] . This subset of genes was screened using Pfam to identify any exhibiting possible functions associated with serine metabolism or transport . The most highly upregulated gene was yhaO ( Z4463 ) , encoding an uncharacterized putative serine inner membrane transporter , displaying a 43 fold increase in expression ( P ≤ 0 . 0005 ) . Adjacent to yhaO are yhaM ( Z4462 ) , encoding a putative serine dehydratase and yhaJ ( Z4459 ) a LysR-type transcriptional regulator ( LTTR ) ( Fig 1A ) . This cluster of genes was of interest as its genetic organization and putative functions were similar to that of the D-serine tolerance locus from UPEC , dsdCXA ( Fig 1A ) , encoding a D-serine transporter , DsdX , and a D-serine dehydratase , DsdA , both of which are regulated by a LTTR , DsdC [23 , 26] . A further gene , yhaK ( Z4460 ) , encoding a redox-sensitive bicupin that is also positively regulated in human urine , a D-serine-rich environment , is oriented divergently from yhaJ ( Fig 1A ) [29 , 30] . Reverse transcriptase-PCR analysis of these genes confirmed their transcription under LEE-inducing conditions and also identified co-transcription of yhaO and yhaM in a similar manner to dsdX and dsdA from CFT073 ( S1 Fig ) . D-serine is considered toxic to certain E . coli isolates that lack dsdCXA , including EHEC [27 , 31] . This made the discovery of yhaOMKJ highly intriguing and begged numerous questions about its functionality and role in EHEC . Our previous investigation into the effects of D-serine on virulence gene expression in EHEC revealed that carriage of dsdCXA was widespread primarily across extraintestinal isolates but also commonly found in intestinal isolates that do not carry the LEE PAI [21] . We used this comparative genomics approach here to investigate if yhaOMKJ is restricted to any particular lineage ( s ) of E . coli . We compared the carriage of yhaOMKJ and dsdCXA using the presence or absence approach in 1581 unique genome sequences of E . coli and the closely related Shigella sp . In contrast to dsdCXA , which is carried in 38% of genomes ( the vast majority being LEE-negative ) , yhaOMKJ is highly conserved across the entire E . coli phylogeny with all four genes being retained in over 94% genomes ( Fig 1B ) . A low frequency of pseudogene appearances occur in the genomes analyzed for yhaO , yhaM and yhaJ ( 3 . 29% , 0 . 44% and 1 . 83% respectively ) . Attrition in yhaJ shows a preference within Shigella isolates ( S1 Table ) . Of the 1581 genomes analysed , 86% of yhaJ pseudogenes were classified as Shigella isolates . Indeed , over half of the Shigella genomes analysed carried a yhaJ pseudogene , an intriguing finding given that the differentiation between these two species is largely based on their pathogenicity and antigenicity rather than genetic distinction [32] . The ancestral nature of this locus and its high degree of conservation suggest an important role in E . coli . More specifically , in EHEC , the inability to grow on D-serine as a sole carbon source implies that YhaO and YhaJ cannot be simply involved in the metabolism of this amino acid but rather that they have been adapted for another as yet undefined function . Previous work has shown the importance of the dsdCXA locus for virulence gene expression in UPEC [22 , 24 , 33] . We therefore tested whether the yhaOMKJ genes affected expression of key virulence factors in EHEC . Non-polar deletion mutants for each of the four genes were generated and tested for effects on secretion of LEE-encoded effector proteins . SDS-PAGE analysis showed that yhaO and yhaJ were required for full activity of the LEE-encoded-T3SS , with a marked reduction in the secretion of associated proteins including Tir , EspD and EspA . Immunoblot analysis of secreted EspD confirmed the phenotypes of the ΔyhaO and ΔyhaJ mutants showing an ~3 . 2 and ~2 . 6 fold reduction in secreted EspD compared to the wild type . Immunoblot analysis of EspD from whole cell lysates also confirmed that not just secretion but also production of EspD was reduced in the ΔyhaO and ΔyhaJ mutant backgrounds . Deletion of yhaK or yhaM did not affect T3SS-associated protein production or secretion ( Fig 2A ) . To verify the phenotypes observed were the consequence of the specific deletions , complementation was achieved by transformation with a plasmid-borne copy of the appropriate gene , fully restoring the production and secretion of effector proteins ( Fig 2B ) . The mutants showed no change in growth rate in minimal media or any significant alterations in motility when inoculated onto soft agar plates ( S2 Fig ) . To examine the role of YhaO and YhaJ under LEE-inducing conditions we examined the global effects caused by deletion of yhaO and yhaJ using comparative RNA-sequencing analysis ( RNA-seq ) . This revealed 105 differentially expressed genes ( DEGs; defined as fold-change greater than 1 . 5 and an FDR corrected P-value of less than 0 . 05 ) between the wild type TUV93-0 and ΔyhaO mutant ( Fig 3A ) . Broad functional grouping according to the literature and gene ontology ( GO ) annotation revealed that more than half of the DEGs identified were involved directly in virulence ( Fig 3B ) . The entire LEE PAI was significantly downregulated , which is comprised of 41 ORFs and includes the master regulators ler and grlA . Twenty non-LEE encoded effectors ( NLEs ) , encoded across diverse elements of the EHEC genome , were also decreased as well as three putative adhesins ( Fig 3B; S3 Fig ) . For the 21 genes that were upregulated their functions were highly varied with roles in cellular metabolism , cell envelope biogenesis and bacteriophage-associated genes . Analysis of the ΔyhaJ mutant revealed 103 DEGs from the wild type , of which 77 were down-regulated and 29 up-regulated displaying diverse functions ( Fig 3B ) . Of the down-regulated genes , again over half were associated with the LEE ( 38 ORFs ) with a further 5 genes encoding NLE proteins . This pattern of expression was mirrored in the ΔyhaO mutant data set ( Fig 3C; S4 Fig ) . The transcriptomic profiles of ΔyhaO and ΔyhaJ showed very extensive overlap in virulence-related ORFs but also showed unique effects on global gene expression in either background ( Fig 3D ) . In both mutants , 45 genes were down-regulated including 38 LEE associated genes , 5 genes encoding NLE proteins and an LpxR homologue ( Z0955 ) suggested to play a role in pathogenesis by modulating lipid-A and , hence , cytokine responses [34] . The RNA-seq data were validated by qRT-PCR analysis for five genes ( espD , tir , ler , nleA and nleG ) identified as being differentially expressed by RNA-seq ( S5 Fig ) . These data identified YhaO and YhaJ as being part of very specific regulons primarily involved in LEE-associated pathogenesis however the differential regulation of a number of non-virulence associated genes in both backgrounds suggests that YhaO and YhaJ likely have other significant and independent roles depending on the conditions tested . RNA-Seq data are summarized in S2 Table . Given that deletion of yhaO or yhaJ selectively down-regulated the T3SS , we tested the ability of EHEC to bind to host cells and intimately attach via A/E lesions . EHEC use the LEE-encoded T3SS to translocate effector proteins into the host cell resulting in A/E pedestal formation and distinctive areas of condensed host-cell actin ( Fig 4A ) . Deletion of either yhaO or yhaJ resulted in significantly ( P ≤ 0 . 001 and P ≤ 0 . 01 respectively ) fewer infected host cells relative to the TUV93-0 control in which over 80% of host cells imaged were colonized . Complementation of either mutant ( pyhaO and pyhaJ ) restored host cell attachment to that of wild type levels ( Fig 4B ) . Moreover , for both mutants , the proportion of remaining attached bacteria formed significantly fewer pedestals ( P ≤ 0 . 01 and P ≤ 0 . 05 respectively ) than the wild type , which were identified by areas of actin condensation , a phenotype that is consistent with reduced effector protein production . This was in contrast with the WT EHEC strain , for which approximately 80% of attached bacteria formed pedestals . Similarly to the proportion of colonized host cells , complementation of either mutant resulted in pedestal formation comparable to the wild type ( Fig 4C ) . Having established that both YhaO and YhaJ play roles in modulating virulence gene expression we aimed to understand better their functions in order to offer mechanistic insight into this phenomenon . YhaO is predicted to be an inner membrane serine/threonine transporter . To examine if YhaO was capable of transporting serine , we used a UPEC ΔdsdXΔcycA mutant that has previously been reported to be unable to transport D-serine and consequently fails to grow on MOPS minimal agar plates containing this amino acid as a sole carbon source ( Fig 5A ) [23] . Growth could be restored by complementation with a plasmid over-expressing DsdX , the characterized D-serine transporter from UPEC CFT073 or by expression of YhaO from EDL933 , strongly supporting the notion that YhaO is capable of transporting D-serine . To further investigate this , radiolabeled D-[3H]-serine was then used to examine D-serine transport in the same genetic background . Uptake of D-[3H]-serine was measured over a range of concentrations from 0 . 01 μM to 200 μM and determined following 5 min incubation . Increasing the external D-[3H]-serine concentration from 0 . 01 μM to 100 μM resulted in a linear increase within the bacterial cells . Concentrations of D-[3H]-serine above 100 μM did not give any further accumulation ( Fig 5B ) . To confirm that the uptake of D-[3H]-serine is related to active transport rather than non-specific binding to the cell surface , uptake was measured in the absence and presence of 10 μM carbonyl cyanide m-chlorophenylhydrazone ( CCCP ) , used to uncouple the H+-gradient of the cell . The uptake was reduced by greater than 90% when CCCP was present , showing that the transport of D-serine is reliant on the H+-gradient ( Fig 5C ) . To determine the specificity of the transporter , competition experiments were performed in which increasing concentrations of unlabeled amino acids were pre-incubated in the uptake assay before D-[3H]-serine was added . L-threonine , a similar hydroxyl amino acid to D-serine affected uptake minimally ( less than 10% reduction compared to the control samples ) , even at concentrations of up to 100 μM , suggesting poor affinity for L-threonine . In contrast , addition of L-serine at 0 . 01 μM resulted in an 85% reduction of D-[3H]-serine uptake ( Fig 5D ) . Together , these results demonstrate that YhaO is capable of transporting D-serine but that it is not capable of discriminating between the two isomeric forms of this amino acid . These data are intriguing considering that the co-transcribed YhaM cannot restore growth to a UPEC ΔdsdA mutant or facilitate EHEC survival on D-serine as a carbon source , calling into question the functionality of YhaM as a serine deaminase ( S6 Fig ) . Examination of previous RNA-Seq data revealed that transcripts mapped to the co-transcribed yhaO and yhaM were increased ( ~1 . 5-fold ) in the presence of D-serine when compared to TUV93-0 alone in MEM-HEPES ( Fig 6A ) , whereas the transcription of yhaJ was not affected by addition of D-serine . To further explore the regulation of YhaO , a reporter plasmid containing the promoter region of yhaO fused to GFP in-frame ( pyhaO:GFP ) was generated and transformed into TUV93-0 . Expression of GFP was determined during growth in MEM-HEPES supplemented with 1 mM D-serine . Addition of D-serine resulted in a significant increase in GFP production during mid to late exponential phase of growth , with expression increasing over this growth phase from a 3 . 1-fold increase ( OD600 of 0 . 6 ) to a 3 . 5-fold increase above that of the wild type alone ( OD600 of 0 . 9 ) . In contrast , UPEC CFT073 transformed with the pyhaO:GFP reporter displayed similar level of yhaO expression in the absence of D-serine but no increase in GFP production when supplemented with 1 mM D-serine under these conditions , regardless of the growth phase ( Fig 6B ) . The expression of yhaJ and yhaO in EHEC is comparable to that of dsdC and dsdX in UPEC , in that D-serine does not affect transcription of the regulator dsdC but the transporter dsdX is significantly upregulated by its presence in the growth media . This was examined using CFT073 transformed with reporters containing the dsdC and dsdX promoters fused to GFP , revealing a 2-fold increase in dsdX expression when D-serine was present ( Fig 6C ) . Growth of EHEC under these conditions was not affected by the addition of D-serine ( doubling rates of 49 . 8 and 51 . 2 minutes respectively ) , despite an increase in its uptake from the environment ( Fig 6D ) . Contrastingly , wild type UPEC displayed a growth advantage in the presence of D-serine ( doubling rates of 150 . 2 and 103 . 2 minutes for without and with D-serine respectively; P-value 0 . 0023 ) but a ΔdsdA mutant was drastically impaired for growth in the presence of D-serine ( doubling rates of 142 . 5 and 221 . 4 minutes respectively; P-value 0 . 0127 ) ( Fig 6E ) . Collectively these results suggest that EHEC has an unusual tolerance for D-serine in the environment and are consistent with the notion that YhaO is an L/D-serine transporter but demonstrate that regulation of yhaO is responsive to the presence of environmental D-serine in an EHEC background only . Having explored the function of YhaO , we aimed to better understand the role of YhaJ . Given the protein has strong homology to known LTTRs , we investigated if YhaJ indeed functioned as a DNA-binding protein and how it contributed to the regulation of gene expression in EHEC . The gene encoding YhaJ from EDL933 was cloned into pET28b , over-expressed in E . coli BL21 ( DE3 ) cells and purified using a combination of immobilized nickel affinity chromatography and size exclusion chromatography . LTTRs typically form dimers in solution that can interact as dimer pairs to bind DNA specifically and regulate gene expression either positively or negatively [36] . Given the genetic location of yhaJ in respect to yhaO as described above we hypothesized that YhaJ may regulate yhaO expression by interacting with its upstream promoter region . Electrophoretic mobility shift assay ( EMSA ) analysis was carried out using a DIG-labeled DNA probe corresponding to an ~300 bp region upstream of the yhaO ATG start codon . Incubation of this probe with increasing concentrations of purified YhaJ ( 0 . 1 to 1 μM ) resulted in a shift of the free DNA indicative of a protein-DNA complex ( Fig 7A ) . In order to address the specificity of this reaction we employed three approaches . First , 1 μM YhaJ was incubated with the DIG-labeled yhaO probe and a 100-fold excess of unlabeled yhaO probe . The unlabeled probe outcompeted the DIG-labeled probe resulting in loss of band shift pattern . Second , YhaJ was tested for its ability to bind a fragment of the kan gene as a negative control . Incubation of increasing concentrations of YhaJ with DIG-labeled kan probe induced no band shift as seen for the yhaO probe . Third , a 100-fold excess of unlabeled kan probe used as a non-specific competitor for the DIG-labeled yhaO probe in a reaction with 1 μM YhaJ could not inhibit binding . These results collectively indicate that YhaJ can specifically bind the upstream regulatory region of yhaO ( Fig 7A ) . Having established this , we next investigated the role YhaJ plays on yhaO transcription . TUV93-0 and the ΔyhaJ mutant were transformed with pyhaO:GFP and were cultured in MEM-HEPES to promote expression of yhaO under LEE-inducing conditions . Activity of the yhaO reporter increased steadily into the late exponential phase in TUV93-0 , conditions that promote increased LEE expression , but was significantly ( P ≤ 0 . 05 ) impaired in ΔyhaJ ( Fig 7B ) . yhaO expression was reduced 1 . 5-fold from that of the wild type at OD600 of 0 . 6 but this increased to a >2-fold at OD600 0 . 9 . Together these data suggest that YhaJ plays a part in regulating yhaO expression directly under conditions that promote expression of the LEE . Given the importance of YhaJ for virulence , we hypothesized that this transcriptional regulator may also control the LEE directly . To address this , we utilized a set of previously described reporters that contain nested deletions of the LEE1 regulatory region fused to lacZ encoding the beta-galactosidase gene [37] . These reporters are designed to monitor activity of the LEE1 regulatory region from both its P1 ( distal ) and P2 ( proximal ) promoters , which have both been documented to play distinct roles in LEE1 activation [37–39] . A schematic of the reporter system is illustrated in Fig 8A and includes LEE10-568/LEE10-275 ( P1 and P2 containing ) , LEE10-155/LEE10-115 ( P1 containing ) and LEE20-568/LEE20-275 ( P2 containing ) . Monitoring the activity of this system in both TUV93-0 and ΔyhaJ under LEE-inducing conditions revealed that YhaJ regulated LEE1 transcription at the major P1 promoter ( Fig 8B ) . ΔyhaJ showed significantly ( P ≤ 0 . 05 ) reduced expression of LEE1 activity in LEE10-568/LEE10-275 and LEE20-568/LEE20-275 but not in the promoter P2-only LEE10-155/LEE10-115 constructs ( Fig 8B ) . Moreover , we used EMSA analysis to determine the binding capacity of YhaJ to the P1 and P2 promoter regions . In agreement with the transcriptional reporter data , increasing concentrations of YhaJ incubated with a DIG-labeled P1 probe induced a band shift that could be outcompeted by a 100-fold excess of unlabeled P1 probe . Conversely , YhaJ was not able to bind the P2 promoter region indicating specificity of YhaJ to the LEE1 P1 promoter region . As an additional control , a 100-fold excess of unlabeled kan probe was unable to reverse binding of YhaJ to the P1 promoter region ( Fig 8C ) . Interestingly , despite deletion of yhaJ being detrimental to NLE transcription as seen in the RNA-seq data , purified YhaJ showed no binding capacity to a selection of DIG-labeled probes corresponding to distinct NLE promoter regions ( S7 Fig ) . NLE regulation is less understood than that of the LEE and not all NLEs are not under the control of a universal regulatory system but have been shown to be influenced by LEE encoded regulators Ler and GrlA [28 , 40 , 41] . Taken together , these data strongly suggest that YhaJ plays an important role in directly activating LEE1 transcription and thus the entire LEE PAI via Ler . These results explain why deletion of yhaJ has detrimental effects on the virulence potential of TUV93-0 . Given our previous work investigating the ability of EHEC to respond to environmental D-serine by downregulating the LEE , these results also offer mechanistic reasoning behind the regulation of the D-serine transporter yhaO by YhaJ .
The ability of a pathogen to sense and respond to stimuli presented in the environment is of critical importance for niche adaptation . Intestinal pathogens must not only be able to identify their preferred site of colonization in terms of nutrient availability but also must compete with the resident microbiota for limited nutrients . Colonization within this complex ecosystem therefore requires effective sensing systems to ensure appropriate gene expression . There has been an emergence in the literature of a wide variety of important signals that EHEC can encounter in the intestinal tract and the complex molecular basis behind how these signals are interpreted allowing colonization of a particular niche within the host gastrointestinal tract is beginning to be unraveled in detail [9] . The precise signals that may contribute to determining niche selection extraintestinally are a less explored area . We recently described how the host metabolite D-serine selectively downregulated the LEE-encoded T3SS by modulating the expression of pre-existing transcriptional regulators [21] . D-serine is found in abundance at extraintestinal sites such as the brain and urinary tract but its concentrations along the intestine are below that required to inhibit LEE expression or growth of EHEC . Conversely , D-serine acts as a positive fitness trait and regulator of virulence gene expression in UPEC and the Gram-positive urinary tract pathogen Staphylococcus saprophyticus [22 , 24 , 42 , 43] . We also analysed the genome sequences of 1581 E . coli isolates and found that carriage of both the dsdCXA D-serine tolerance locus and the LEE PAI was a significantly rare event . By introducing a functional DsdA deaminase to EHEC the ability to use D-serine as a carbon source and eliminate intracellular accumulation was recovered however inhibition of the LEE was not abolished . This led us to propose that there was an ‘evolutionary incompatibility’ between the two loci thus assisting in the restriction of LEE-positive pathogens to the intestinal tract irrespective of whether they could catabolize D-serine or not [21] . This hypothesis offers one possible explanation as to why extraintestinal pathogens do not carry and adapt the LEE-encoded T3SS to their advantage , despite the LEE T3SS facilitating binding , at least in vitro , to a wide variety of cell types [41 , 44 , 45] . Acquisition of the LEE is also not determined by the phylogenetic relatedness of E . coli strains . Certain strains of intestinal pathogenic EPEC for instance are more closely related to ExPEC members of the B2 phylogroup yet have acquired the LEE , lost dsdCXA and consequently have evolved to be dedicated intestinal pathogens . Despite this exciting finding the underlining molecular mechanism used to mediate D-serine repression of the LEE remained a key question . Classically , bacteria utilise two-component sensors to respond to many changes in the environment and regulate gene expression . EHEC use the FusKR two-component system and quorum sensing systems respectively to respond to fucose concentrations appropriately at the epithelial surface and to integrate host and bacteria derived hormone-like signals [12 , 46] . Other signals such as ethanolamine via its sensing regulator EutR can be sensed directly within the cell to modulate the activity of virulence associated transcriptional regulators , [13 , 47] . For the latter , bacterial cells must be able to uptake the required signal in order to respond to it at the cytoplasmic level . While possessing DsdX as a pseudogene , EHEC accumulate D-serine intracellularly implying other uptake systems are at play . In this study we have identified YhaO , an inner membrane transporter that is capable of transporting D-serine in EHEC . This gene is part of a cluster that includes the co-transcribed YhaM ( a D-serine dehydratase ) and YhaJ ( a DNA-binding LTTR ) . Despite functionality of YhaO being confirmed , YhaM is clearly non-functional in EHEC and could not restore a UPEC dsdA mutant when supplied in trans . YhaJ was found to be responsible , at least in part , for regulating yhaO expression particularly at late exponential phase of growth . This is interesting as when EHEC is grown in MEM-HEPES , LEE expression is dramatically increased at this stage . Previous microarray data identified increased yhaO expression under these conditions also and recently an independent study reported yhaO to be part of the wider Ler regulon in EPEC but no role was specified [28 , 48] . Deletion of yhaO was detrimental for LEE expression and therefore A/E lesion formation . Together , these data imply an important role for YhaO in LEE regulation specifically under inducing conditions . Expression of yhaO was found to be responsive to exogenous D-serine in EHEC , increasing largely in its presence , but yhaJ did not express differentially . This is a similar scenario to that of the D-serine tolerance locus in UPEC in that dsdC transcription is not increased in response to D-serine but dsdX is significantly upregulated . This seems counter-productive considering the inhibitory effects of D-serine reported for E . coli [49] . Surprisingly , EHEC is able to tolerate mM concentrations of D-serine in MEM-HEPES without any growth defect , a trait that a UPEC ΔdsdA mutant does not have . We recently reported that wild type EHEC and UPEC ΔdsdA accumulate D-serine intracellularly and that this is due to the lack of a functional DsdA [21] . We also found the repressive effects of D-serine on LEE transcription to be a concentration-dependent process . In this respect , increasing D-serine uptake in EHEC would therefore increase the transcriptional response to this amino acid , all the while still allowing tolerance to intracellular accumulation . This provides a logical role for expression of YhaO under LEE-inducing conditions , to act as a safety net constantly monitoring the environment for inhibitory concentrations of D-serine . Further evidence for this is in the fact that YhaJ is expressed at a constant level providing continued input into the yhaO promoter . Constitutive expression of yhaJ also benefits expression of the LEE . We found YhaJ to be necessary for full expression of LEE operons 1 through 5 and formation of A/E lesions on host cells . Furthermore , YhaJ was found to be a direct regulator of the LEE1 P1 promoter in EHEC , which is considered the major activator of ler expression [37] . By feeding directly into the LEE master regulator and also regulating YhaO , YhaJ provides unique and subtle control over colonization in EHEC ( Fig 9 ) . Pathogen emergence is not solely influenced by the acquisition of virulence factors . Horizontally acquired elements such as the LEE must be integrated into the regulatory network of the cell in order to function in a timely and appropriate manner . Regulators of the LEE are often acquired horizontally on mobile genetic elements . For instance , the Pch regulators found on cryptic-prophage and the prophage-encoded Psr regulators that usurp the conserved glutamate dependent ( GAD ) acid stress response to regulate the LEE indirectly [50 , 51] . However , chromosomally encoded global regulators , such as nucleoid-associated proteins , are also important regulators of virulence [52–55] . Either way , the LEE is not a ubiquitous system and receives regulatory inputs from diverse sources . This demonstrates the high degree of adaptability in the E . coli genome . The same can be said of UPEC isolates . UPEC harbor a vast array of virulence determinants that can vary between isolates but no one virulence factor is responsible for colonization of the urinary tract . That being said it has been documented previously that certain UPEC isolates mutated for the dsdCXA D-serine tolerance locus have reacquired these genes horizontally presumably due to their importance for UPEC fitness and virulence in the urinary tract [56] . A recent study documenting host-specific induction of fitness genes during human urinary tract infection also highlighted the importance of typically non-virulence associated mechanisms in the pathogenesis of UPEC [57] . UPEC is very capable of surviving in the gastrointestinal tract in a highly competitive manner yet , despite carrying virulence factors that promote dissemination extraintestinally , UPEC is a very adapted pathogen tailoring the transcriptional profile of its core genome specifically to its current environment [58] . EHEC has the potential to at least come into contact with the urinary tract upon exit from the host via the rectum and in some rare cases has even been isolated from hospitalized patients suffering from urinary tract infection [59] . However , these variants are not clinically prevalent and this environment does not offer much advantage to the intestinally adapted EHEC . Intriguingly , Subashchandrabose et al . identified yhaOMKJ as being differentially expressed in a selection of UPEC isolates from human urinary tract infection when transcription in vivo was compared with growth in LB broth or human urine . This suggests an as yet unidentified role for these genes in UPEC during infection of the bladder , a D-serine rich environment [57] . This observation supports our model that YhaO and YhaJ play important roles in gene regulation during colonization and that they help shape the specialization process of pathogenic E . coli . Therefore , it is perfectly plausible that EHEC must possess a system to sense abundant signals including those from the urinary tract such as D-serine , thus informing the pathogen to restrict the expression of its key colonization factor when approaching a new , less favorable environment . Adaptation of existing core genes to ensure appropriate regulation of horizontally acquired elements is important for maximizing bacterial competitiveness . Recent work has shown that in the mouse pathogen Citrobacter rodentium , which also utilizes a LEE-encoded T3SS for virulence , an AraC-like regulator RegA responds to bicarbonate ions to regulate transcription globally , including the LEE . RegA homologues are found in E . coli species but do not play a role in LEE regulation , despite being of similar evolutionary origin , further demonstrating pathogen specific regulatory adaptations to common virulence factors [60–62] . The yhaOMKJ locus is similarly very conserved across the E . coli phylogenetic spectrum . With maintenance being intact among the vast majority of E . coli , this implies a role that is important for the fitness of both pathogens and non-pathogens in a range of different hosts and environments . RNA-seq data described here provide evidence for this , as YhaJ and YhaO seem to be involved in global gene regulation suggesting other roles besides control of the LEE . In contrast , the minority of E . coli that show attrition in this locus–particularly Shigella for yhaJ–are , presumably , undergoing a ‘use it or lose it’ approach to niche specification and genome minimalism [63] . Clearly in EHEC , YhaO and YhaJ are important for full expression of the LEE , a specialized colonization factor that is absent from non-pathogens . However , in over half of the Shigella genomes analysed , yhaJ was present as a pseudogene . As an invasive pathogen YhaJ may not be essential for other processes that it may regulate , including the control of specialized virulence factors . Additionally , it is possible that exposure to D-serine is a less common occurrence for Shigella , and therefore a role for YhaJ is less important resulting in attrition of the gene [64] . Certainly this observation is consistent with our previous findings suggesting that host metabolism can drive bacterial evolution by providing selective environments . Notably , Shigella carry a plasmid-encoded T3SS that is genetically related to the ETT2 ( E . coli type III secretion 2 ) system also carried by MNEC isolates [65] . Distinct from the LEE in both genetics and regulation , we predict the ETT2 would not be downregulated by addition of D-serine and we are currently testing this postulate . Overall , we have identified a highly conserved and widely distributed transporter and transcriptional regulator that act in concert to sense D-serine and control gene expression . Based on these findings , we propose to name YhaO as DlsT ( D/L-serine transport protein ) . The precise role of YhaJ in global gene regulation is not yet fully determined; hence we choose not to suggest a functional name as this time . We postulate this ubiquitous system is important as D-serine can act as either a carbon source or stress depending on the genetic background of the individual pathotype and modulate gene expression of unique virulence factors . Irrespective of its nutritional value , it appears that the ability to effectively monitor and respond to D-serine in the environment is critical for maximizing bacterial fitness and niche specification in certain pathotypes . This study demonstrates the adaptive power of the existing E . coli core genome to recycle and reuse present genes for a more specialized function .
The bacterial strains , plasmids and oligonucleotide primers used in this study along with relevant accompanying information are listed in S3 , S4 and S5 Tables , respectively . Single bacterial colonies were inoculated into 5 ml LB broth containing the appropriate antibiotics and cultured overnight at 37°C , 200 rpm . Overnight cultures were used to inoculate pre-warmed MEM-HEPES ( Sigma , St Louis , MO , USA; cat # m7278 ) and samples were cultured at 37°C , 200 rpm . D-serine was purchased from Sigma . Motility was assessed by inoculating the center of on 0 . 25% Tryptone agar plate with 5 μl of bacterial culture at OD600 0 . 6 and diameter of the population swim was measured after 8 hours at 31°C . Non-polar mutations of yhaO , yhaM , yhaK and yhaJ were generated in TUV93-0 . ΔyhaO was generated using Lambda red-mediated mutagenesis [66] . ΔyhaM , ΔyhaK and ΔyhaJ were generated using allelic exchange [67] . Complementation was achieved by cloning yhaJ and yhaO into low copy number pWSK vectors and transforming the plasmids into each deletion background . Strains of interest were transformed with pyhaO:GFP , pdsdC:GFP or pdsdX:GFP [68] and used to inoculate 10 ml MEM-HEPES as described above . Replicates were cultured at 37°C and 200 rpm with samples taken every hour for measurement of bacterial density ( OD600 ) and fluorescence . Population GFP expression was determined by transferring 200 μl aliquots to a black 96-well plate for GFP fluorescence measurement ( excitation at 485 nm; emission at 550 nm ) on a FLUOstar Optima Fluorescence Plate Reader ( BMG Labtech , UK ) . GraphPad Prism 5 . 0 ( San Diego , CA , USA ) software was used to generate a standard curve of OD600 versus fluorescence and obtain values at specific OD600 for comparison between samples . Background fluorescence was corrected for by subtracting values gained from cells carrying promoter-less reporter plasmids from a standard curve . Data presented are the mean ( ±SEM ) of at least three biological replicates . The nested deletion series of the LEE1 promoter region fused to lacZ were generated and described elsewhere [37] . These constructs were transformed into wild type TUV93-0 and ΔyhaJ . Promoter activity was measured as described previously [69] . Briefly , transformed strains were cultured in MEM-HEPES as described above to an OD600 of ~0 . 8 . 400 μl aliquots were diluted 1:1 in Z buffer and lysed with 0 . 1% SDS and chloroform then vortexed before incubating at 37°C for 1 minute . 200 μl of o-nitrophenyl-β-d-galactopyranoside ( 2 mg/ml ) was added to each reaction and incubated at 37°C before stopping the reaction with 500 μl of 1 M Na2CO3 when sufficient color change was observed . OD450 was measured and used to calculate the promoter activity in Miller units . Data presented are the mean ( ±SEM ) of at least three biological replicates . SDS-PAGE analysis of secreted proteins was carried out as described previously [51] . Strains of interest were cultured in 50 ml MEM-HEPES as above to an OD600 of ~0 . 8 and supernatants were obtained by centrifugation at 4000 rpm for 20 minutes . Whole cell pellets were lysed using BugBuster Protein Extraction buffer ( Merck , New Jersey , USA ) . For secreted proteins , cell culture supernatants were syringe filtered ( 0 . 45 μm ) and precipitated with 10% v/v TCA ( Sigma ) overnight at 4°C . Secreted proteins were harvested by centrifugation at 4000 rpm ( 4°C ) for 1 hour . Protein pellets were resuspended in Tris-HCl ( pH 8 . 0 ) and analyzed by SDS-PAGE using the Novex system ( Invitrogen , Carlsbad , CA , USA ) . Primary antibodies used for immunoblotting were EspD ( 1/6000 ) , Tir ( 1/2000 ) and GroEL ( 1/20000 ) . Antibodies were made up in PBST containing 1% skim milk powder . Comparison of protein levels from SDS PAGE and immunoblot experiments was carried out by densitometry using ImageJ . Experiments were performed on multiple occasions to confirm the results . Bacterial cultures were grown as above and mixed with two volumes of RNAprotect reagent ( Qiagen , Valencia , CA , USA ) , incubated for 5 minutes at room temperature and cell pellets harvested by centrifugation . Total RNA was extracted using an RNeasy kit ( Qiagen ) after which genomic DNA was removed using TURBO DNase ( Ambion , Carlsbad , CA , USA ) . Total RNA samples were enriched for mRNA using MICROBexpress mRNA enrichment kit ( Ambion ) . Samples for RNA-seq analysis were quality control tested for mRNA enrichment using an Agilent Bioanalyzer 2100 at the University of Glasgow , Polyomics Facility . cDNA synthesis and sequencing was performed at the University of Glasgow Polyomics Facility ( Illumina NextSeq 500 ) and the Edinburgh Genomics facility ( Illumina HiSeq 2500 ) for the ΔyhaJ and ΔyhaO mutants respectively obtaining 75 or 100 bp single end reads . Samples were sequenced in triplicate with TUV93-0 replicates sequenced in parallel on each platform . Raw reads were QC checked using FastQC ( Babraham Bioinformatics , Cambridge , UK ) and trimmed accordingly using CLC Genomics Workbench ( CLC Bio , Aarhus , Denmark ) . Trimmed reads were mapped to the EDL933 reference genome ( NCBI accession number: NC_002655 . 2 ) allowing for 3 mismatches per read and at least 5 reads per feature . Analysis of differential expression was performed using the Empirical analysis of DGE tool , which implements the EdgeR Bioconductor tool [70] . Differentially expressed genes were identified using a positive or negative absolute fold change of ≥1 . 5 and a corrected P-value of ≤ 0 . 05 ( false-discovery rate of 5% ) . GO functional grouping was summarized according to information available on Colibase and the RegulonDB [71 , 72] . Volcano plots were generated in CLC Genomics Workbench . Coverage plots used to visualize the pattern and abundance of RNA-seq read mapping to genomic loci were generated using EasyFig [35] . The sequence reads in this paper have been deposited in the European Nucleotide Archive under study PRJEB12065 . Validation of RNA-seq data was carried out by qRT-PCR using KAPA SYBR FAST Universal qRT-PCR master mix ( KAPA Biosystems , Woburn , MA , USA ) and M-MLV Reverse Transcriptase ( Promega , Madison , WI , USA ) . Total RNA was extracted as described above and was quantified on a NanoDrop 2000 ( Thermo-Scientific ) . Samples for comparison were normalized to a concentration of 50 ng/μl using TE buffer ( Ambion , Carlsbad , CA , USA ) . qRT-PCR analysis was performed using a one-step reaction; cDNA synthesis first followed by qRT-PCR according to the manufacturers specifications . Individual reactions were performed in technical triplicate and each gene to be analysed was performed in biological triplicate . The gapA gene was used to normalize the results . qRT-PCR reactions were carried out using the ECO Real-Time PCR System ( Illumina , San Diego , CA , USA ) according to the manufacturers specifications and the data were analysed according to the 2-ΔΔCT method [73] . Cell adhesion assays were performed essentially as described previously [21] . Coverslips were seeded with 4x104 human epithelial tissue culture cells ( HeLa cells; Thermo-Scientific , Waltham , MA , USA ) in multi-well plates and incubated overnight in MEM-HEPES at 37°C with 5% CO2 . TUV93-0 , ΔyhaJ and ΔyhaO were transformed with an RFP-expressing plasmid ( pRFP ) and subsequently used for adhesion assays . Cultures for cell infection were grown in MEM-HEPES at 37°C until at an OD600 of ~0 . 7 . HeLa cells were washed with fresh MEM-HEPES and infected with 100 μl bacterial culture ( OD600 of 0 . 1 ) in 500 μl fresh pre-warmed MEM-HEPES . Multi-well plates were centrifuged at 400 rpm for 3 minutes and incubated at 37°C with 5% CO2 for 2 hours , after which coverslips were washed with fresh media to remove unbound bacteria and incubated for a further 3 hours . Coverslips were washed 3 times with sterile PBS before fixing for 20 minutes with 250 μl PFA ( 2% ) . Coverslips were washed a further 3 times with PBS . 250 μl of Triton X-100 ( 0 . 5% ) was added and wells were incubated for 5 minutes before further washing . Host cell actin was stained with Phalloidin-488 ( Invitrogen ) for 1 hour and coverslips were washed again . Mutants carrying complementation plasmids were stained at this stage with anti-O157 primary ( 1/500 ) and Alexa-Fluor 555 secondary ( Invitrogen ) as an alternative to expression of pRFP . Finally , coverslips were wicked dry and mounted on glass microscope slides using fluorescent mounting medium ( Dako , Cambridge , UK ) . Slides were dried in the dark overnight before imaging . Imaging was performed on a Zeiss M1 Axioimager microscope and data was acquired and deconvoluted using the Zen Pro software ( Zeiss , Jena , Germany ) . For quantification of adhesion at least twenty-five random fields of view were obtained per replicate and A/E lesions were counted as areas of intense actin condensation beneath bacterial cells . Data presented are the mean ( ±SEM ) of at least three biological replicates . Assessment of the ability to grow using D-serine as a sole carbon source was carried out as described previously using MOPS minimal media agar plates supplemented with D-serine [23] . Strains of interest were streaked and grown over a 36-hour period at 37°C on MOPS plates . Experiments were performed multiple times to confirm the results . The coding sequence for yhaJ from EDL933 was amplified from TUV93-0 genomic DNA by PCR using primers with BamHI ( forward ) and HindIII ( reverse ) in-frame flanks and cloned into pET-28b ( N-terminal 6xHistidine tag ) before being transformed into E . coli BL21 DE3 cells for over expression . Overnight cultures were used to inoculate LB and cultures were grown at 37°C and 200 rpm until OD600 of 0 . 6 , at which point cells were induced with 1 mM IPTG and overexpressed at 15°C overnight . Cells were harvested by centrifugation , resuspended in wash buffer ( 200 mM NaCl , 50 mM Tris , 40 mM Imidazole , 10% glycerol ) and lysed using a French press . The supernatant was then used for immobilized metal affinity ion chromatography ( IMAC ) using an AKTA-prime according to the manufacturers specifications . Further purification of desired elution samples was carried out using size-exclusion chromatography ( SEC ) . Elution fractions from the IMAC stage were dialyzed overnight in SEC buffer before being re-purified according to size using an AKTA-prime and a Superdex S200 column . Elution fractions corresponding to the size of YhaJ were retained . Concentration of purified YhaJ was determined using a Nanodrop 2000 . In order to examine the ability of YhaO to transport D-serine we used an established CFT073 deletion mutant for known D-serine transporters , ΔdsdXΔcycA [23] . By transforming this strain with an inducible expression vector containing YhaO ( pyhaO-ind ) from EDL933 we could recover the wild-type feature and be certain that all transport of D-serine occurs through YhaO . Cultures of ΔdsdXΔcycA + pyhaO-ind were grown in LB media overnight and used to inoculate MOPS media containing 3% glycerol at an OD600 of 0 . 1 . The cultures were grown until an OD600 of 0 . 4 at which point 0 . 4 mM IPTG was added to initiate expression of pyhaO-ind . The cells were incubated for one hour at 37°C after induction and then harvested by centrifugation at 3500 g for 20 min . The cells were washed twice in PBS and resuspended in 500 μl PBS . The protein concentration of the sample was measured by QUBIT ( Thermo-Scientific ) . Cells were split into 20 μl aliquots and kept on ice . The transport of D-[3H]-serine was characterized by incubating cell suspensions with a range of concentrations of the radiolabelled ligand ( 0 . 1 μM , 1 μM and 10 μM ) for 15 minutes . The cells were diluted in 5 ml MOPS-Tris buffer and then applied onto a membrane filter ( 0 . 2 μM ) . The liquid was moved through using a vacuum pump and the filters were washed in 5 ml MOPS-Tris buffer before the membranes were allowed to dry and placed in scintillation vials in 3 ml Biosafe counting cocktail ( RPI Corp , Mount Prospect , IL , USA ) . The samples were measured in a scintillation counter . Time dependency of the D-serine uptake was measured by incubating samples with 1 μM D-[3H]-serine and diluting the samples into 5 ml MOPS-Tris at various time points ( 1 min to 20 min ) . Dependency of the transporter upon the membrane potential of the cell was confirmed by pretreatment of cell suspensions with 10 μM carbonyl cyanide m-chlorophenylhydrazone ( CCCP ) for three minutes . Competition assays were performed by pre-incubating the cell suspensions with a range of concentrations of L-serine or L-Threonine for three minutes before the incubation of 1 μM D-[3H]-serine for 3 minutes . Disintegrations-per-minute values determined by Scintillation counter . Data were normalized to the activity of D-[3H]-serine and to the overall protein concentration of the cell suspension using GraphPad Prism 5 . 0 ( San Diego , CA , USA ) . EMSA assays were performed using the DIG Gel Shift Kit , 2nd Generation and the DIG Wash and Block buffer set ( Roche , Mannheim , Germany ) according the manufacturers specifications with minor alterations . DNA probes were amplified by PCR using primers specific to the regions of interest . DNA fragments were labeled with ddUTP-11-DIG and diluted to a concentration of 0 . 4 ng/μl for use in binding reactions . Binding reactions were carried out for 30 minutes at 30°C using increasing concentrations of recombinant YhaJ ( 0 to 1 μM ) . Competition assays used a 100-fold excess of unlabeled specific or non-specific probe . A fragment of the kan gene was used as a non-specific control probe . Binding reactions were separated on 6% DNA retardation gels ( Invitrogen ) and transferred to positively charged nylon membrane ( Roche ) using the NOVEX system ( Invitrogen ) . EMSA assays were then developed using AP conjugated anti-DIG antibody ( Roche ) according to the manufacturers specifications . EMSAs were repeated multiple times to confirm the results . The nucleotide sequences for 159 E . coli core-genes were elaborated as described by previously [21 , 74] . At each iteration , the core gene set ( initialised as the nucleotide sequence for genes present in strain MG1655 ) was aligned to the next E . coli genome sequence using blastn [75] . Genes aligning at > 70% identity and > 80% of the length of the coding sequence were retained in the core gene set for use in the next iteration . This analysis produced 159 genes , the nucleotide sequences of which were extracted from the E . coli genomes using blastn , aligned by Muscle [76] and concatenated . A maximum likelihood tree was constructed using PhyML under the GTR + g model of nucleotide substitution [77] . Dendrograms were visualized using the APE package [78] implemented in R [79] . The amino acid sequences for genes yhaO , yhaM , yhaK and yhaJ were collected from the EDL933 genome ( NCBI accession number: NC_002655 . 2 ) , and amino acid sequences for the genes dsdX , dsdC and dsdA were collected from the CFT073 genome ( NCBI accession number: NC_004431 . 1 ) . These sequences were used as the query sequence in tblastn searches against the E . coli genome sequences . In order to try to assemble hits which may be split over contigs , high scoring pairs ( HSPs ) aligning at greater than 70% amino acid similarity over greater than 30% of the coding sequence of the query protein were collected and assembled against the query sequence . The percent similarity ( of the assembled hit to the query sequence ) and coverage ( of the assembled hit over the query sequence ) was then calculated from these assembled hits and a total percent similarity between the hit and query sequence calculated by the formulae ( percent similarity * coverage ) / 100 . The assembled hit sequences were saved for further pseudogene analysis . A gene was called as present within a genome if the assembled hit aligned to the query sequence at greater than 80% total similarity . The distribution of the genes across the E . coli core-genome dendrogram was visualized using the Diversitree package [80] implemented in R [79] . For the identification of pseudogenes , the recovered assembled hit sequences were investigated by both manual inspection and calculation of the length of the sequence until a stop codon was encountered . Obviously foreshortened or truncated proteins , those where a stop codon was encountered which shortened the protein by greater than 5% of the length of the query sequence , were assigned as pseudogenes .
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The host intestinal tract is a challenging environment for any foreign organisms not usually found within the microbiota . Intruding pathogens must survive physical barriers and readily compete with the local micro flora for limited nutrients within their preferred niche . In order to do this , intestinal pathogens have adapted many methods of sensing the environment for numerous chemical signals that may be encountered , and thus translate these signals to the relevant transcriptional networks that promote colonization . However , intestinal pathogens will also encounter a vast variety of signals both prior to entry into the intestinal tract and post fecal shedding . Therefore sensing specific signals from these environments is key to limiting the colonization of unfavorable environments . In this work we have elaborated on previous findings that the host metabolite D-serine , found in abundance at extraintestinal sites , can repress colonization of enterohaemorrhagic Escherichia coli ( EHEC ) , by demonstrating a mechanism used to sample D-serine from the environment . Responding appropriately to host-relevant signals is critically important for niche recognition and also reveals the adaptive power of bacterial pathogens . Knowledge of such signals reveals the detailed mechanisms about niche adaptation , how colonization is regulated and could potentially be used for the design of novel intervention strategies to limit intestinal pathogenesis .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2016
|
A Highly Conserved Bacterial D-Serine Uptake System Links Host Metabolism and Virulence
|
Dengue infection spread in naive populations occurs in an explosive and widespread fashion primarily due to the absence of population herd immunity , the population dynamics and dispersal of Ae . aegypti , and the movement of individuals within the urban space . Knowledge on the relative contribution of such factors to the spatial dimension of dengue virus spread has been limited . In the present study we analyzed the spatio-temporal pattern of a large dengue virus-2 ( DENV-2 ) outbreak that affected the Australian city of Cairns ( north Queensland ) in 2003 , quantified the relationship between dengue transmission and distance to the epidemic's index case ( IC ) , evaluated the effects of indoor residual spraying ( IRS ) on the odds of dengue infection , and generated recommendations for city-wide dengue surveillance and control . We retrospectively analyzed data from 383 DENV-2 confirmed cases and 1 , 163 IRS applications performed during the 25-week epidemic period . Spatial ( local k-function , angular wavelets ) and space-time ( Knox test ) analyses quantified the intensity and directionality of clustering of dengue cases , whereas a semi-parametric Bayesian space-time regression assessed the impact of IRS and spatial autocorrelation in the odds of weekly dengue infection . About 63% of the cases clustered up to 800 m around the IC's house . Most cases were distributed in the NW-SE axis as a consequence of the spatial arrangement of blocks within the city and , possibly , the prevailing winds . Space-time analysis showed that DENV-2 infection spread rapidly , generating 18 clusters ( comprising 65% of all cases ) , and that these clusters varied in extent as a function of their distance to the IC's residence . IRS applications had a significant protective effect in the further occurrence of dengue cases , but only when they reached coverage of 60% or more of the neighboring premises of a house . By applying sound statistical analysis to a very detailed dataset from one of the largest outbreaks that affected the city of Cairns in recent times , we not only described the spread of dengue virus with high detail but also quantified the spatio-temporal dimension of dengue virus transmission within this complex urban environment . In areas susceptible to non-periodic dengue epidemics , effective disease prevention and control would depend on the prompt response to introduced cases . We foresee that some of the results and recommendations derived from our study may also be applicable to other areas currently affected or potentially subject to dengue epidemics .
Dengue is a mosquito-borne infection that has re-emerged as a major international public health concern over the last four decades [1] , [2] , [3] . Caused by four closely related yet antigenically distinct single-stranded RNA viruses ( genus Flavivirus , family Flaviridae ) , dengue viruses persist in a horizontal Aedes aegypti-human transmission cycle [4] . Transmission and spread of dengue infection are determined by the interplay of multiple factors including the level of herd immunity in the human population; virulence characteristics of the circulating viral strain; temperature and rainfall; survival , abundance , dispersal and blood feeding behavior of female Ae . aegypti; and human density , age structure , and behavior [5] , [6] . As a consequence , contact rates between humans and mosquitoes are not random , but highly clustered in space and time [7] . The increasing trends in human population growth and urban redistribution that occurred over the past 40 years , coupled with the expansion of commercial trade and the rapid movement of humans ( by air travel ) , have reshaped the global map of dengue transmission risk [8] , [9] . Currently , about 70 to 100 million cases of classic dengue infection are reported every year , with an estimated 2 . 1 million cases of life-threatening disease in the form of Dengue Hemorrhagic Fever ( DHF ) /Dengue Shock Syndrome ( DSS ) [10] . Furthermore , the number of dengue fever epidemics has increased dramatically , and an expansion of the dengue endemic and hyperendemic areas is indisputable [2] , [8] , [9] . Under current socio-epidemiological scenarios , continued geographic expansion of epidemic dengue is expected to continue ( as observed in north and central Argentina , where dengue transmission was registered for the first time in 2009 [11] ) , and severe dengue and DHF outbreaks are expected to follow once mixing of multiple serotypes occurs . Dengue epidemics in such areas are commonly originated by viremic travelers from endemic regions [9] , and can cover large areas leading to a large number of cases as a consequence of the limited ( or null ) population exposure to dengue viruses , the prevailing high vector abundances and the challenges faced by local vector control programs on dealing with massive outbreaks . Consistent with global trends , outbreaks of dengue have become more frequent and severe in Australia , occurring exclusively in north Queensland ( NQ ) [12] , [13] , [14] , [15] , [16] , [17] . Originated by viral introduction via infected travelers from endemic regions , dengue outbreaks in this region are characterized by a rapid spread both in time and space , as a result of the prevailing high Ae . aegypti populations [18] and the movement of residents and tourists within and between urban centers [15] . The recent occurrence of two major and widespread epidemics in 2003 and 2008–2009 has challenged local health authorities with the question of whether NQ will join the growing list of dengue endemic regions . In Queensland , the Tropical Population Health Unit ( TPHU ) dependent of Queensland Health is the institution responsible for regular vector and viral surveillance , vector control , outbreak response , public education , and operational research [12] , [19] . In late February 2003 , TPHU was notified of three locally acquired dengue fever cases in a small industrial area in the city of Cairns [15] . Mosquito-control measures were implemented immediately and local doctors were alerted . These cases were quickly confirmed as dengue virus serotype 2 ( DENV-2 ) [15] . Vector-control measures began in the affected Cairns neighborhoods following the Dengue Fever Management Plan for north Queensland ( Supporting Information S1 ) , and extended until the outbreak was declared over , five-and-a-half months and 459 cases ( 383 of which occurred in the city of Cairns ) after the primary introduction [15] . In following up these cases , it was learned that a PNG national introduced the virus into Cairns in late January soon after arriving from PNG into a neighborhood heavily infested by Ae . aegypti [18] . In support of such case as the epidemic's putative index case are the following: a ) dengue is not endemic in Cairns , indeed , there was no confirmed dengue activity in urban Cairns before the IC arrival into Cairns from PNG; b ) once transmission was confirmed in the area , the sera of the putative case ( originally misdiagnosed as malaria ) was retrospectively confirmed by PCR as DENV-2 positive , 49 days after its arrival from PNG [15]; c ) the DENV-2 from 2003 had 99 . 8% homology with an import from PNG into the nearby city of Townsville in April 2003 [15] , indicating PNG as the most likely origin of the DENV-2 introduction; d ) most of the early cases occurred around the putative index case's residence . Dengue infection spread in naive populations occurs in an explosive and widespread fashion [5] , [20] , [21] , [22] , [23] as a consequence of the combination of the lack of herd immunity , the population dynamics and dispersal of Ae . aegypti and the movement of individuals within the urban space [15] , [24] . Knowledge on the relative contribution of such factors to the pattern of virus propagation during epidemic events has been limited . As a consequence , the spatial dimension of dengue virus spread within complex urban environments is unknown . Although a few studies had quantified the spatial pattern of dengue epidemic transmission in urban environments [20] , [22] , [23] , [25] , [26] , difficulties in assessing where the virus has been first introduced had limited their description of the pattern of dengue infection spread . In the present study we analyzed the pattern of spread of the DENV-2 outbreak that affected the city of Cairns ( NQ ) in early 2003 , quantified the relationship between dengue spread and the location of the epidemic's index case ( IC ) , derived a dispersal kernel for virus spread , assessed the effects of vector control in the containment of the infection , and generated recommendations for city-wide improvement of dengue surveillance and control .
The city of Cairns ( total 2006 population: 140 , 347 ) is located in the wet tropics of northeastern Queensland , Australia ( 16 . 9° S; 145 . 8° E ) . Cairns has a tropical monsoonal climate , with respective mean daily low and high temperatures of 18°C and 26°C in winter and 24°C and 31°C in summer , and most of the rainfall ( ca . 82% of the annual 1 , 992 mm ) falling during January–April ( Australian Bureau of Meteorology ) . Residential areas consist of a mixed housing type , with relative small 1–3 story apartment blocks interspersed with single family houses . Housing ranges from modern brick , concrete block and stucco structures to wooden houses that are 50–100 years old . These old wooden ‘Queenslander’ houses are elevated on wooden or concrete poles and typically feature unscreened windows to maximize air flow . Older suburbs of Cairns ( i . e . , Parramatta Park , Manuda , Cairns North , Edge Hill ) contain mostly ‘Queenslander’ houses , and often are surrounded by dense tropical vegetation . Cairns also is surrounded by a series of small isolated ‘beach communities’ that abut the Coral Sea . The present study focused on dengue transmission dynamics in urban Cairns; beach communities and satellite towns were excluded because of their low ( or absence of ) dengue transmission [17] . De-identified data with age , sex , date of onset of infection , and geographic position of the most likely place of dengue infection for each of the 383 laboratory-confirmed human dengue cases that occurred within urban Cairns in 2003 were provided by TPHU . Additional information given by TPHU included: location and timing of each indoor residual spray ( IRS ) performed by the Dengue Action Response Team ( DART ) , GIS layers with information on the road network and each one of the 32 , 716 premises censused in urban Cairns in the year 2003 , and a 2004 orthorectified high-resolution satellite image ( Ikonos , GeoEye , Dulles , VA ) of the city of Cairns . All geographic layers were processed in a Geographic Information System ( ArcGIS 9 . 3 , ESRI , Redlands , CA ) in order to hide their absolute location while preserving the relative distance between them ( to protect each patient's identity ) . Dengue is a notifiable diseae in Australia [19] , [30] . Upon suspicion of a dengue case , medical practitioners from private clinics and the Cairns hospital are required to contact TPHU to provide details about each case ( name , address , phone numbers and specific symptoms; see Figure S1 in Supporting Information S1 for a sample notification form ) . Also , all pathology laboratories in Queensland are required to promptly notify public health authorities of any laboratory result indicative of a recent dengue infection ( i . e . , positive dengue IGM titers or virus detection by PCR ) . Within 24 hours of receipt of a notification of a suspicious or a laboratory confirmed case highly trained TPHU public health nurses perform contact tracing telephonic interviews to determine a patient's travel history and to identify the origin of infection ( i . e . , imported or locally acquired dengue ) , the date of onset of infection ( i . e . , date of onset of symptoms minus the intrinsic incubation period of 4–7 days [5] ) , the locations a patient visited while viremic and , ultimately , the most likely place where infection has occurred [30] . Refer to Figure S2 in Supporting Information S1 for a sample dengue case report form used by TPHU nurses to obtain information on each case and to infer the most likely place of infection . The most likely place of infection of each case was determined by epi-linking the places visited during the 4–7 days before the onset of illness . The locations were based upon a ) home address , b ) work address , or c ) places and people who they have visited during the exposure period ( Figure S2 in Supporting Information S1 ) . Patients were asked for addresses where they had been bitten by mosquitoes during the exposure period . Any addresses with recent ( ∼2–4 weeks ) dengue activity were considered a likely place of infection . The selection of the most likely place of infection for cases epi-linked to more than one premise was based on the amount of daytime spent by a person on each location ( i . e . , the premise in which a patient spent most of his/her daytime was selected as the exposure site ) . The information of the most likely place of infection for cases without any epidemiological link to transmission areas ( based on the phone interviews ) was updated if new information , such as the confirmation of previously unknown dengue cases within 2 weeks of the onset of symptoms of the initial case , was obtained . Interviews were also performed with the persons each patient identified as potential primary or secondary contacts ( e . g . , work mates , relatives , friends ) to pre-empt the detection of further secondary infections . Based on estimates of a recent ( 2008–2009 ) epidemic , TPHU nurses generally interview approximately 3 potential cases per every confirmed case ( D . Brookes , Queensland Health , personal communication ) . Given that TPHU only kept digital records of the most likely places of dengue infection for each case ( after the change from paper to digital records , TPHU discarded all phone interview paper records ) in this study we were unable to analyze the accuracy of nurses in identifying them . While we acknowledge that some of the dengue acquisition addresses may have been incorrectly identified during the interviewing process ( due to patients' recall bias ) , we believe that most are accurate and that the general spatial nature of the outbreak is not radically perturbed by the misidentification of a small number of acquisition addresses . Upon confirmation of an address where a patient spent time while viremic , TPHU initiated vector control activities as described in Supporting Information S1 . The date and address for every IRS/source-reduction intervention were recorded in a geodatabase linked to the Cairns GIS . In the present study we only analyzed data on indoor residual spraying ( IRS ) because , when properly applied , it represents an effective method to supress Ae . aegypti indoor populations [31] . We estimated the age-adjusted incidence of infection for the 2003 epidemic by applying the direct method [32] . This method adjusts the amount that each age group contributes to the overall rate of transmission , so that the overall rates are based on the same age structure [32] . Such adjustment was calculated by first multiplying the age-specific disease rates by age-specific weights ( i . e . , the proportion of the standard 2000 Queensland population within each age group ) and then summing the weighted rates across all age groups to give the overall age-adjusted dengue incidence rate for the 2003 epidemic . In this way , we eliminated possible interferences in the estimates due to heterogeneous demographic structure of the studied population . Classic , spatial , and Bayesian statistical analyses were performed to describe and quantify the spread of dengue in the 2003 Cairns epidemic . A maximum likelihood logistic regression [32] was employed to assess the impact of IRS on the odds of secondary dengue infections at the house level . Particular attention was paid to the timing of spray versus the occurrence of cases in a house , since variation in the incubation period of dengue ( ∼7 days when accounting for intrinsic incubation period ) can affect the predicted relationship between spraying and dengue cases ( by having cases infected before the spraying but showing symptoms after the spraying ) . Cross-correlation time series analysis [33] between the weekly number of cases and the weekly number of IRS applications , weekly precipitation and average temperature were performed to assess the relationships between the temporal progression of the epidemic and selected environmental factors . Meteorological data for Cairns was obtained from the Australian Bureau of Meteorology ( source station: Cairns International Airport , located <4 km from the introduced case's residence ) . Spatial analyses were performed to quantify the intensity ( Local K-function ) and directionality ( angular wavelet analysis ) of the spatial clustering of dengue cases around the introduced case ( IC ) , and space-time analysis ( Knox test ) were applied to identify independent space-time clusters of dengue transmission during the 25 weeks of the outbreak . The Local K-Function ( Li ( d ) ) developed by Getis and Frankling [34] was applied to determine the overall distance up to which cases clustered around the IC . In our focal analysis of Li ( d ) , i is represented by the location of the IC . Statistical inference of Li ( d ) is performed by comparing the observed Li ( d ) with the expected Li ( d ) generated by 999 Monte Carlo realizations under the hypothesis of Complete Spatial Randomness [34] . A focal spatial correlogram of Li over d was used to assess the distance up to which clustering of dengue cases around the IC was maximized ( dmax ) . Briefly , dmax represents the distance at which the value of Li is maximum . dmax is interpreted as the distance beyond which the inclusion of further cases does not increase the probability that the distribution of events differ from random [34] . To determine if the distribution of cases around the IC occurred predominantly in a given cardinal direction ( i . e . , anisotropic distribution ) we divided the space around the IC's house into one degree sectors , and counted the number of cases that fell within each sector . These counts were then analyzed by angular wavelet analysis [35] . A wavelet function g ( x ) is a scalable windowing function . In our study we used the French Top Hat [35] as a wavelet function . The main metric derived from fitting the wavelet function to the data is the wavelet positional variance . Peaks in this variance indicate directions where most of the cases fell relative to the IC . In order to separate true patterns from random fluctuations , the significance of the wavelet analysis was determined by comparing the observed variance with the one obtained from 999 Monte Carlo simulations [35] . The analysis was performed for both the location of cases and the location of Cairns houses to determine if any anisotropic pattern in the distribution of cases could have been an artifact of the spatial arrangement of houses within the city . Visualization of spatial anisotropy in the occurrence of cases was performed by estimating spatial standard-deviation ellipses in ArcGIS 9 . 3 ( ESRI ) . The Knox method [36] was applied to quantify the space-time interaction of individual confirmed dengue cases reported during the outbreak . This method tests for possible interaction between the distance and time separating cases , based on the number of case pairs found in a particular time-space window ( e . g . , case pairs separated by less than M meters and T days ) [36] . When interaction is present , distances between pairs of cases will be small , and the test statistic will be large . In our study we chose the values of M and T as 100 m and 20 days , respectively , to account for mosquito dispersal distance ( i . e . , Ae . aegypti seldom disperses beyond 100 m [37] , [38] ) and virus incubation periods ( i . e . , maximum sum of intrinsic and extrinsic incubation periods ) . The expected values of the test under the null hypothesis of random case occurrence ( in space and time ) were estimated by performing 999 Monte Carlo simulations . A semiparametric Bayesian space-time structured additive regression model ( STAR ) [27] , [39] was applied to assess the effects of IRS , rain and spatial autocorrelation in the odds of weekly dengue infection over the first 15 weeks of the epidemic . Since our analysis focused on weekly data we selected a discrete-time duration STAR model [27] . Such model allows a unified treatment of time scales , linear and non-linear effects of covariates and spatially correlated random effects within a Bayesian framework [27] . Briefly ( refer to [27] for a detailed description ) , a space-time geoaditive STAR model has the following predictor structure: ( 1 ) where u′itγ are the usual linear predictors ( fixed effects ) for covariate vector u , f1 . . k are possibly non-linear functions of the covariates , ftime is a possibly non-linear time trend and fspat is a spatially correlated ( random ) effect of the location sit an observation pertains to [27] . In a Bayesian approach , all non-linear functions fj and parameters γi are considered as random variables and ( 1 ) is therefore conditional upon these random variables , having to be supplemented with appropriate prior distributions . Fixed effects were modeled by independent diffuse priors ( p ( γj ) ∼const , j = 1 , … , r ) , whereas the priors for unknown functions ( fj ) were dependent on the type of covariate and on the prior knowledge about smoothness . The fixed effects ( f1 . . k ) and the time function ( ftime ) were modeled via Bayesian penalized splines ( P-splines ) , whereas Markov random field priors were chosen as priors for the spatial effects ( fspat ) [27] . Posterior means together with confidence intervals and other parameters are obtained by drawing samples from the posterior by Markov chain Monte Carlo ( MCMC ) techniques [27] . Variance parameters ( τj2 ) can be estimated by assigning additional hyperpriors to them . The most common assumption is that τj2 are independently inverse gamma distributed , i . e . , τj2∼IG ( aj , bj ) , with hyperparameters aj and bj a priori set as aj = bj = 0 . 001 . For updating the parameters in a MCMC sampler , a Metropolis-Hastings algorithm based on iteratively weighted least squares was applied [27] . We performed a sensitivity analysis of the best fitted model by varying the values of aj and bj between 1 and 0 . 0001 as described in [39] . Our STAR model evaluated the effect of rain , the cumulative proportion of sprays performed around a premise ( cum_spr ) and the spatial arrangement of premises ( spat ) on the odds of weekly dengue virus infection ( binomial variable , 0 = no infection , 1 = infection ) at the house level from weeks 0 to 15 post introduction . Analysis focused in the neighborhoods surrounding the IC's house ( Parramatta Park , Manuda and Cairns North ) , where most of the cases and IRS applications occurred . Thyssen polygons from the centroids of all the premises within the analyzed area were generated to allow contiguity weighting schemes for the spatial random effects . Our analysis matrices had a dimension of 1 , 490 premises by 15 weeks ( or 22 , 350 repeated measurements ) , and the structure of the evaluated models was as follows: ( 2 ) and ( 3 ) We compared both models in their Deviance Information Criterion ( DIC , the AIC equivalent for Bayesian models [27] ) after 100 , 000 MCMC randomizations , and only reported the results of the model with the lowest DIC . Spatial and spatio-temporal analysis were performed with ClusterSeer 2 . 0 ( Terraseer , Ann Arbor , MI ) , R 2 . 10 . 1 ( http://www . r-project . org/ ) and ArcGIS 9 . 3 ( ESRI ) software , whereas Bayesian STARS were performed with BayesX software ( http://www . stat . uni-muenchen . de/~bayesx ) and model outputs visualized with R package BayesX ( http://cran . r-project . org/web/packages/BayesX/ ) . The protocols for storing , analyzing and reporting results on the 2003 Cairns dengue epidemic data were approved by Queensland Health's Human Research Ethics Committee ( protocol HREC/09/QCH/52-590 ) .
Local transmission of dengue in Parramatta Park began 18 days after the onset of symptoms in the imported case ( 21 January ) . However , the TPHU was not notified of dengue activity in the area until 5 March ( ∼43 days post-introduction ) and initiated mosquito control measures the next day . It took ∼49 days to retrospectively confirm that the traveler from PNG ( initially misdiagnosed with malaria ) was indeed the epidemic's IC . A total of 383 laboratory-confirmed symptomatic cases were registered within urban Cairns over the 25-week epidemic period that followed the initial introduction . All infections were confirmed as mild ( only 5% of all cases were hospitalized ) DENV-2 derived from the initial introduction; no dengue-related deaths or DHF manifestations were reported . The index case ( week 0 ) and subsequent first wave of local transmission ( weeks 2–3 ) are clearly distinguished by the epidemic curve ( Figure 1A ) . The weekly number of confirmed dengue cases then showed an exponential growth from one to 56 cases from weeks 4 to 7 post introduction ( PI ) , followed by a stable period ranging from 44 to 47 cases during weeks 8–10 PI , and a final exponential decay thereafter ( Figure 1A ) . The weekly pattern of IRS applications followed the pattern of human cases , totaling 1 , 163 applications over a 19 week period ( Figure 1A ) . The overall age-adjusted incidence rate of the 2003 Cairns epidemic was 1 , 148 cases per 100 , 000 ( Table 1 ) . The highest incidence rates were observed in males 30–39 year old . Overall , young adults ( 30–39 years old ) presented the highest incidence rates ( average [SD] , 258 . 5 [27 . 9] and 193 . 6 [16 . 9] cases per 100 , 000 for men and woman , respectively ) , but not in the younger or older ages ( Table 1 ) . The weekly number of cases was strongly and positively correlated ( Cross-correlation coefficient , r>0 . 6 ) with the number of IRS applications up to a time lag of 2 weeks ( Figure S3 in Supporting Information S1 ) . Such positive correlation was consequence of the strong and active response of TPHU to the DENV-2 epidemic once DENV-2 transmission was confirmed ( Figure 1A ) . The weekly variation in temperature ( mean , minimum and maximum ) and total precipitation during the 25-week period of the outbreak ( Figure 1B ) did not show any strong correlation ( r<0 . 5 ) with the weekly number of cases ( Figure S3 in Supporting Information S1 ) . However , the lack of rain during weeks 8–11 ( Figure 1B ) coupled with the high intensity of IRS applications during that period could have acted synergistically against local Ae . aegypti populations and help explain the sharp reduction and further interruption of dengue transmission after week 11 PI ( Figure 1A ) . Figure 2 ( and Video S1 ) depicts the spatio-temporal pattern of dengue spread in Cairns during the 25-week transmission period . Up to week 5 PI , most transmission was contained around the IC ( all but one confirmed case occurred within 100 m of the IC ) . Within the first 3 weeks PI , two additional cases occurred in the same house of the IC . Between weeks 6 and 10 PI , transmission continued propagating around the IC , but also expanded to other neighborhoods located further than 100 m of the IC . An increase in the distance of new cases to the IC together with a reduction in the number of confirmed cases were evident by week 15 PI . Between weeks 15 and 25 PI only a few isolated cases occurred , most of them located in the periphery of urban Cairns . The last case was contracted on week 25 , and the epidemic was formally declared over three months later . Focal clustering of DENV-2 cases was maximized at a distance of 800 m from the IC ( Li ( dmax ) = 1 , 742 . 3; P<0 . 05; Figure S4A in Supporting Information S1 ) . A total of 240 cases ( 63% ) were located within dmax , mainly in the neighborhoods Parramatta Park ( PP ) and Cairns North ( CN ) ( Figure S4B in Supporting Information S1 ) . The spatial wavelet directionality analysis performed within dmax showed a significant peak ( Spatial Variance >1 . 96; P<0 . 05 ) in the orientation of cases around the IC towards the NW-SE direction ( Figure 3A , B ) . A significant peak in the distribution of houses around the IC towards the same NW-SE direction ( Figure 3C ) points to the orientation of the built environment ( blocks were aligned NW to SE and elongated at a ratio of ca . 3× longer than wide ) as the most likely cause of the anisotropic distribution of cases around the IC . The dominant wind direction during the first 2 months from the initial epidemic spread from the index case ( Feb . –March ) was from the SE quadrant ( ie . , 60–180°; Figure 3D ) , with 80% and 44% of winds at 9 AM and 3 PM from such quadrant , respectively . Such prevailing early morning and late afternoon winds could have affected dispersal of infected Ae . aegypti females , also contributing to the SE/NW oriented anisotropic distribution of dengue infections around the IC ( Figure 3B ) . The space-time Knox test statistic identified a total of 18 independent significant space-time clusters involving 250 ( 65 . 3% ) cases ( Figure 4 ) . The remaining 133 ( 34 . 7% ) cases did not show any spatio-temporal association among them or with members of the space-time clusters . Table 2 summarizes the characteristics of each identified space-time cluster , together with the average distance of each case to the original IC and the putative index case ( PIdC ) of each cluster , and Figure S5 in Supporting Information S1 shows the weekly distribution of the proportion of cases within each space-time cluster . The earliest and largest cluster ( cluster 1 ) occurred around the IC , and included 129 cases ( including the IC ) extending over 440 m during a 13-week period ( Figure 4 , Table 2 ) . The second cluster was initiated 37 days after the onset of symptoms of the IC , and was located at an average distance of 679 m from the IC ( Figure 4 , Table 2 ) . The average distance between every cluster's case and the case that first showed symptoms ( i . e . , the cluster's putative index case , PIdC ) was 75 m ( SD: 51 . 2 m ) whereas the average distance between cases within a cluster was 73 . 2 m ( SD , 59 . 9 m ) ( Table 2 ) . The spraying response ( measured in days since the onset of symptoms of a cluster's first reported case ) in each cluster averaged 15 . 3 days ( range , 0–40 days ) whereas the spraying coverage averaged 36 . 8% ( range , 0–100% ) for all the premises with cases and 23% ( range , 0–47 . 1% ) for all the premises found within 100 m of a premise with a confirmed case ( Table 2 ) . For each space-time cluster we identified its first confirmed case and estimated the spatial and time distances from each secondary case in the cluster to this PIdC . PIdC can be interpreted one of the most likely origins of a space-time cluster . We then considered each cluster as a replicate to assess the relationship between distance and time since the onset of symptoms of a PIdC . The distance up to which most of the secondary cases were found increased with the time since the onset of symptoms of a PIdC from 50 m to 200 m and 325 m for weeks 1–3 , 4–6 and 7–8 , respectively ( Figure 5A ) . Most of the cases whose onset of symptoms was within 3 weeks of the onset of symptoms of a PIdC were found within 50 m of it ( Figure 5A ) . The mean distance from a secondary case to a PIdC increased linearly with the time after onset of symptoms of the PIdC , at a rate of 14 . 4 m ( SD , 16 . 2 m ) per week during weeks 1–3 and 32 . 9 m ( SD , 13 . 2 m ) per week from weeks 4–8 post onset of symptoms of the PIdC ( Figure 5B ) . About 95% ( 2 SD ) of all the cases found within the first week of onset of symptoms of the PIdC occurred 125 m around it ( Figure 5B ) . This distance increased to 200 m by week 3 . Figure 5B can be interpreted as a kernel of dengue diffusion from a PIdC after filtering out the effect of long distance human movement . The odds of a secondary dengue infection at premises with confirmed dengue cases was significantly higher at unsprayed premises than at a sprayed premises ( OR = 2 . 8; 95% CI = 1 . 1–6 . 9; P = 0 . 03 ) . From the 151 unsprayed premises with confirmed dengue cases , 36 ( 23 . 8% ) reported subsequent dengue cases at an average of 7 days ( SD = 10 . 6 days; Max = 50 days ) of the onset of symptoms of the first case in the premise . Whereas from the 97 sprayed premises with confirmed dengue cases , 13 ( 13 . 4% ) reported subsequent dengue cases after the onset of symptoms of the first case in the premise . From such estimate are excluded 20 confirmed cases exposed to infective bites in sprayed premises within 7 days of an insecticide spray , and most likely infected before IRS applications . The main causes of lack of IRS applications were residents' refusal to grant access to the DART team due to personal matters or to aversion to pesticides , residents' absence at the time of DART visitation , and occurrence of locked entrance gates or dangerous dogs at a given premise . Bioassays using WHO cones on lambda-cyhalothrin-treated wood ( SA Ritchie , unpublished data ) together with an observed 90% reduction of gravid female collections in sticky ovitraps within a month of IRS applications in Parramatta Park [18] support the lack of resistance to lambda-cyhalothrin in local Ae aegypti populations . DIC values for STAR models ( 2 ) and ( 3 ) were 2 , 036 and 2 , 025 , respectively . Hence , a model without rain as a fixed effect ( 3 ) was selected as the best descriptor of the weekly spatial pattern of dengue infection . All variables in the model had an acceptance rate of 65% or more ( not shown ) . The posterior mean ( with 80% credibility intervals ) of the effect of week on the odds of dengue infection is shown in Figure 6A . The odds of infection was negative from weeks 0–4 ( the “silent” period before the epidemic was identified ) , positive from weeks 5–13 ( the period of “active” transmission ) and negative onwards ( the period of effective control ) ( Figure 6A ) , resembling the shape of the epidemic curve ( Figure 1A ) . The effect of the spatial occurrence of cases followed the observed space-time clustering of cases , with the highest posterior mean values ( dark red in Figure 6B ) found around the IC's residence and the remaining areas of medium positive ( orange in Figure 6B ) effect found in the periphery . The cumulative proportion of sprays around a premise had a non-linear relationship with the posterior odds of dengue infection ( Figure 6C ) . When spraying coverage around a premise was less than 40–60% , the odds of dengue infection was positive ( IRS did not prevent further cases around a premise ) . Only when 60% or more of the premises around a house were sprayed with insecticides the odds of infection was significantly reduced to levels below 0 , and IRS applications had a protective effect in the further occurrence of dengue cases ( Figure 6C ) . The spatial occurrence of IRS applications ( Figure 6D ) was similar to the distribution of cases ( Figure 6B ) , with most of the applications in the vicinity of the IC's residence and less applications in the periphery of the introduction point . The sensitivity analysis performed by changing the hyperpriors ( a and b ) did not show any deviation from the basic model with default values ( Figure S6 in Supporting Information S1 ) .
Dengue vector control failures are partly due to our deficiencies in understanding relationships among available interventions , virus transmission dynamics , and human behavior [40] . In areas sporadically affected by epidemic dengue , such as northern Queensland , control interventions are generally implemented in response of the occurrence of local transmission , generally when it is too late to rapidly contain virus propagation [21] , [22] , [23] , [25] , [41] . By applying sound statistical analysis to a very detailed dataset from one of the largest outbreaks that affected the city of Cairns in recent times , we not only described the spread of DENV-2 with high detail but also derived important knowledge that will contribute to the understanding of how dengue virus infection propagates epidemically within complex urban environments . Current patterns of human movement by air travel have increased the probability of introduction of dengue into Ae . aegypti infested areas [9] . However , it is recognized that only a handful of such introductions will have the potential of becoming IC's of a dengue epidemic . Therefore , the likelihood of a successful dengue introduction will depend on the juxtaposition of various events , such as the time a person remains viremic in the destination area ( tv ) , the number of sites he or she visited while viremic ( lv ) , and the number of Ae . aegypti bites he or she received across lv during tv [41] . Lastly , the likelihood of secondary transmission in the same area will be dependent on the exposure of local residents to infective bites from the Ae . aegypti females found across lv ( after accounting for extrinsic incubation period and vector dispersal ) . All such events are significantly modulated by the impacts of vector control interventions and the build-up of population herd immunity to DENV infection occurring both in space and time . Hence , the complex pattern of dengue introduction , establishment and further propagation relies on a complex repertoire of events that , altogether , determine the spatial dimension of virus epidemic spread . Sequential transmission ( i . e . , the progressive occurrence of human cases in neighboring houses ) , likely attributable to mosquito-driven spread and/or short-distance mobility of viremic humans , as well as long distance propagation of infection ( likely generated by human mobility ) have been documented in many urban dengue epidemics [21] , [22] , [42] . Neff et al [21] elegantly showed how , after the introduction of dengue in a Puerto Rican village , subsequent cases occurred “sequentially” within the same block and also in distant parts of the village . Similarly , phylogenetic analysis of a DENV-3 epidemic affecting the city of Sao Paulo ( Brazil ) allowed Mondini et al . [25] to estimate the most likely route of viral dispersal , showing that a same lineage was “dispersed” within the city both at short and long distances compatible with mosquito- and human-mediated virus spread , respectively . Our detailed analysis differentiated with great detail the contribution of short and long distance propagation of dengue virus infection within Cairns . We identified the location of 18 transmission clusters within the city that , given their space-time separation , were most likely originated by the movement of viremic humans within the city . Such clusters , although different in their extent and duration of dengue infection presence , shared a similar pattern of virus propagation from their PIdC . Outdoor sticky ovitrap collections performed in PP during the initial weeks of the epidemic evidenced high dengue virus infection rates in Ae . aegypti ( up to 116 per 1 , 000 ) , validating the occurrence of vector-mediated virus propagation within clusters . Furthermore , as most human DENV-2 infections were mild , visitation of viremic patients to their near neighbors can also help explain the rapid propagation of dengue infection within each cluster . Build-up of immunity in the human population ( a . k . a . herd immunity effect ) has been postulated as an important driver in the dynamics of dengue virus infection , mainly by modulating human-mosquito infective contacts [5] , [6] . In our study we were unable to quantitatively assess the contribution of herd effect on the local dynamics of dengue transmission ( no information on human population numbers per house were available ) . However , given the impact and extent of the epidemic , we hypothesize that the local propagation around the IC and not the overall termination of the dengue outbreak were affected by the herd immunity effect . We base this assumption on the following observations: a ) given the small and sporadic introductions of dengue , previous immunity to DENV-2 can be considered negligible , and a high population susceptibility assumed; b ) a significant proportion of cases occurred in close proximity to the IC , and the ratio of infected to susceptible individuals could be high enough in such area to have a detrimental effect in the local transmission of dengue; and c ) city-wide transmission was not severely impacted due to the low ratio of infected individuals to the population at risk ( ∼383/140 , 300 ) ; even assuming a 1∶10 symptomatic to asymptomatic ratio such proportion would have been lower than 5% . The 2003 Cairns epidemic had its epicenter in the neighborhood of Parramatta Park ( PP ) and then progressed to the neighborhoods of Cairns North ( CN ) and eastern Manuda ( MN ) . Such pattern of introduction and spread was consistent with descriptions of previous Cairns epidemics [13] , [14] , [17] , and may be the product of the combination of demographic , environmental and entomologic characteristics unique to such areas . The high density of elevated old ‘Queenslander’ houses found in PP and CN , together with the presence of abundant tropical vegetation around them , provides optimal conditions for Ae . aegypti development and dispersal [18] , [37] . As a consequence , such neighborhoods generally have the highest Ae . aegypti populations in Cairns [13] , [18] . Given that most ‘Queenslander’ houses have unscreened windows , endophagy by Ae . aegypti can increase vector abundance but also vector-mediated virus propagation to neighboring premises ( as observed in the 2003 epidemic with the propagation of infection from the IC's house –a typical ‘Queenslander’ house – to neighboring houses ) . Moreover , the high number of backpacker hostels found in such neighborhoods ( particularly CN ) increases the possibility of a dengue introduction by a viremic traveler in those areas ( as observed in the 1997 Cairns epidemic that originated from a backpacker guesthouse located in CN [14] , [17] ) . Hence , the patterns of introduction and further spread of dengue in Cairns appear to follow a consistent spatial pattern irradiating from a few key neighborhoods with particular conditions . Case detection , vector surveillance and disease management could be highly improved if such spatial heterogeneity in the likelihood of dengue introduction and spread is accounted in their design , particularly in the early stages of an outbreak . A classic approach to reduce the propagation of infected vectors and suppress dengue transmission during the early stages of an epidemic ( i . e . , after the detection of active transmission ) consists of the targeted implementation of vector control actions within a buffer distance ( e . g . , 50–100 m ) of a confirmed case [43] . Such approach may be insufficient if virus human or vector propagation of dengue virus occurs beyond 100 m . Mark-release-recapture ( MRR ) studies have shown that urban Ae . aegypti females seldom disperse beyond 100 m [38] , [44] , [45] , [46] . However , given that most mosquitoes are recaptured within 3 weeks of release , MRR studies tend to collect very limited data on the dispersal ability of older females . Thus , the contribution of older , potentially viremic , females to the tail of the dispersal distribution is highly underrepresented . By using robust space-time clustering tests we were able to use human dengue infection as a marker of virus propagation and later estimate the spatial and temporal dimensions of dengue virus spread from a putative index case ( PIdC ) . We acknowledge that human movement may also contribute to the spread of dengue virus beyond the dispersal kernel . Nonetheless , our study showed that most ( 95% ) of the cases associated with a PIdC were within a 200 m radius of it , and that the average spread of dengue infection varied from 14 to 32 m per week . If validated with data from other epidemics and settings , such information could have significant impacts in the design and implementation of case detection and vector control activities , particularly in areas affected by epidemic dengue . A spatio-temporal unit for case detection and control actions could help determine the area around a PIdC that would need to be screened for additional cases or controlled with insecticides or source-reduction in order to halt the propagation of dengue virus infection . Rapid ( and effective ) response constitutes a key operational premise in such settings [47] . Larval control and source reduction represent two of the most effective and widely used strategies to control Ae . aegypti populations [31] , [48] . However , in areas sporadically affected by dengue epidemics preventive actions are generally rare , and most vector control activities occur upon the identification of an introduced case or the detection of active local transmission . In such circumstances , adulticiding ( i . e . , targeted control of adult Ae . aegypti by IRS or space spraying ) represents an effective control action to rapidly suppress dengue transmission [48] . Additionally , where dengue hits sporadically it is common that vector control agencies are understaffed , making the response to a dengue outbreak a daunting challenge . For instance , during the 2003 epidemic Cairns Dengue Action Response Team ( DART ) was composed by only 4 staff members who had to be supplemented by ‘volunteers’ from other health agencies once it was evident that the number of cases exceeded the capacity of these officers to respond . Under such circumstances , our analysis shows that although IRS had a significant effect in controlling Ae . aegypti and reducing the odds of dengue infection , the spraying coverage around an infected premise had to be maintained at 60% or more in order to prevent subsequent infections . This finding points to the need for a coordinated effort in the design of control interventions , since partial insecticide spraying ( <40% coverage ) can yield to a low control effectiveness , and a higher chance of virus spread . In Cairns , lack of personnel , the occurrence of closed or conflictive premises or of property owners refusing any control activities in their houses were the main causes of the reduced insecticide coverage found in the vicinity of many dengue-positive premises . The incorporation of database and mapping technologies to track the delivery of control actions and monitor the levels of spraying coverage would prove essential to rapidly and effectively respond to a dengue epidemic [49] . Preventive control in high risk areas , capacity building ( particularly in GIS/mapping and spatial analysis ) , incorporation of trained field technicians from other public health agencies , and integration of scientifically-based and context-sensitive control actions represent key vector control components of an integrated program geared to effectively contain dengue epidemics . Underreporting and asymptomatic infections can represent an important proportion of the total number of dengue cases affecting a city during an epidemic [5] , [6] . One of the main limitations of our study has been the lack of knowledge of the relative contribution of such “silent” infections to the total pool of cases . Dengue infection detection and notification in northern Queensland are high ( due to the quality of the health system and the history of dengue introductions ) [19] , [24] . Hence , underreporting rates are considered low compared to the ones found in other urban centers . Nonetheless , since we analyzed data on laboratory-confirmed cases we can assume them to be the tip of the iceberg in the overall pattern of dengue spread , and that the distribution of under-reported cases will follow the one of laboratory-confirmed cases . On the other hand , the actual contribution of asymptomatic cases to the local spread of dengue is unknown , in part due to the uncertainty about their potential to infect Ae . aegypti mosquitoes while viremic [4] . A serologic survey or an active surveillance system could have helped assess the size of infected population ( and consequently the effect of herd immunity buildup ) as well as the actual attack rate and epidemic potential of dengue virus in the 2003 epidemic . In Cairns ( as in many other settings where dengue transmission is sporadic ) the age-adjusted incidence was higher in young adults . Given that this age group is also one of the most mobile segments of the population their infection could have been the product of their movement ( and exposure ) in transmission “hot spots” . In our study we used the most likely place of transmission ( instead of the case's residence ) as the positional mark of a case . Such choice allowed us to more accurately analyze the propagation of dengue virus infection , since our approach included the potential exposure locations rather than merely the residential address of a case . Although TPHU nurses are highly trained and skilled in contact tracing ( some of them have been performing case detection for more than 10 years ) , the reliability of their assessment is not perfect . However , the lack of original records of all the locations reported by a patient ( due to disposal of paper records when THPU migrated to digital records ) prevented us to analyze the relationship between dengue infection and the type and number of exposure locations reported and , ultimately , the accuracy of TPHU nurses in identifying transmission locations . The integration into a GIS-based decision support system of all the locations a patient has visited during the previous week to the onset of symptoms will help TPHU nurses improve their assessment . Rapid mapping of all the locations identified by the field nurses not only will allow detect where a patient may have gotten infected , but also assess which locations he or she may have visited while viremic . Such information could improve outbreak response and control of dengue epidemics . In summary , the 2003 Cairns outbreak exhibited a pattern common to most dengue epidemic areas: virus introduction by a viremic traveler , delayed case identification and confirmation , abundant Ae . aegypti populations , limited ( or absent ) preventive control measures , delayed initiation of vector control activities once transmission was confirmed , and limited personnel/infrastructure to control a spreading epidemic . All those factors acted together to generate one of the largest outbreaks Cairns has had in recent times [13] , and challenged health authorities to develop a plan to prevent epidemic spread following a point introduction . From our detailed analysis we generated a series of recommendations for TPHU that may help contain future dengue outbreaks in Cairns: a ) upon suspicion of a dengue introduction , treat each potential case as dengue and perform containment activities covering all the premises found within a distance pre-spcified according to the time elapsed since the suspected introduction ( as outlined in Figure 5B ) ; b ) target surveillance and preventive control in the neighborhoods dominated by older , unscreened housing such as PP and CN , that are most likely to initiate epidemic transmission; c ) perform insecticide resistance tests periodically; and d ) incorporate GIS and space-time analysis ( by training local public health specialists ) as the key tools of a decision support system for dengue management in northern Queensland . We foresee that some of the analytical procedures and derived recommendations may also be applicable to other areas currently affected or potentially subject to epidemic dengue .
|
Global trends in population growth and human redistribution and movement have reshaped the map of dengue transmission risk , exposing a significant proportion of the world's population to the threat of dengue epidemics . Knowledge on the relative contribution of vector and human movement to the widespread and explosive nature of dengue epidemic spread within an urban environment is limited . By analyzing a very detailed dataset of a dengue epidemic that affected the Australian city of Cairns we performed a comprehensive quantification of the spatio-temporal dimensions of dengue virus epidemic transmission and propagation within a complex urban environment . Space and space-time analysis and models allowed derivation of detailed information on the pattern of introduction and epidemic spread of dengue infection within the urban space . We foresee that some of the results and recommendations derived from our study may also be applicable to many other areas currently affected or potentially subject to dengue epidemics .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
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"public",
"health",
"and",
"epidemiology/epidemiology",
"infectious",
"diseases/viral",
"infections",
"ecology/spatial",
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2010
|
Quantifying the Spatial Dimension of Dengue Virus Epidemic Spread within a Tropical Urban Environment
|
Reproductive proteins are among the fastest evolving in the proteome , often due to the consequences of positive selection , and their rapid evolution is frequently attributed to a coevolutionary process between interacting female and male proteins . Such a process could leave characteristic signatures at coevolving genes . One signature of coevolution , predicted by sexual selection theory , is an association of alleles between the two genes . Another predicted signature is a correlation of evolutionary rates during divergence due to compensatory evolution . We studied female–male coevolution in the abalone by resequencing sperm lysin and its interacting egg coat protein , VERL , in populations of two species . As predicted , we found intergenic linkage disequilibrium between lysin and VERL , despite our demonstration that they are not physically linked . This finding supports a central prediction of sexual selection using actual genotypes , that of an association between a male trait and its female preference locus . We also created a novel likelihood method to show that lysin and VERL have experienced correlated rates of evolution . These two signatures of coevolution can provide statistical rigor to hypotheses of coevolution and could be exploited for identifying coevolving proteins a priori . We also present polymorphism-based evidence for positive selection and implicate recent selective events at the specific structural regions of lysin and VERL responsible for their species-specific interaction . Finally , we observed deep subdivision between VERL alleles in one species , which matches a theoretical prediction of sexual conflict . Thus , abalone fertilization proteins illustrate how coevolution can lead to reproductive barriers and potentially drive speciation .
Given the importance of reproduction for evolutionary fitness , one might predict that reproductive proteins would be highly conserved , especially those required for interaction between sperm and egg . The requirement of molecular recognition between interacting proteins should result in sequence conservation , and indeed , there is proteome-wide evidence that interaction interfaces are more highly conserved than other surface residues [1] . Yet many key reproductive proteins evolve rapidly and are driven to do so by positive selection [2] . Furthermore , several fertilization proteins are driven to change at the specific regions mediating sperm-egg recognition . This observation stands in stark contrast to the general conservation of interaction interfaces . The driving force behind the initial divergence of fertilization proteins is unknown and is a subject of active investigation . Some proposed hypotheses are sexual selection , the creation of reproductive barriers between hybridizing populations ( reinforcement ) , and a sexual conflict over the fertilization rate [2] . Regardless of which force drives their initial divergence , the interaction between sperm and egg should be maintained through coevolution , in which one or both proteins adaptively compensate for changes in the other . Such female-male coevolution has often been proposed to contribute to the rapid evolution of reproductive proteins [3]–[6] , but specific tests of this hypothesis have not been performed . The process of coevolution could leave characteristic signatures on interacting fertilization genes . In populations with multiple alleles , sperm-egg pairs expressing compatible alleles would have fertilization rates exceeding those of relatively incompatible pairs , especially in the presence of sperm competition . This difference in rates would create an association of compatible alleles within zygotes . Hence , one predicted signature , apparent in populations , is a genetic association of alleles between the two interacting genes . Such an association could be observed as intergenic linkage disequilibrium ( LD ) . This prediction has also been made in terms of sexual selection , in which a genetic association develops between a male trait and female preference for that trait [7] , [8] . Another potential signature of coevolution is found in gene phylogenies in which coevolution could create a long-term correlation of evolutionary rates between the two genes [9] , [10] . During coevolution , acceleration in the rate of change of one protein would cause its cognate to compensate in order to maintain their interaction . Hence , rates of evolution would correlate between corresponding branches of their phylogenetic trees . This prediction has been supported by multiple studies which found correlations of branch lengths between interacting proteins [9]–[14] . Such a signature could also be used to test for long-term coevolution between interacting fertilization proteins . Interacting sperm-egg protein pairs are currently known in only two taxonomic groups , abalone and sea urchins [15] , [16] . Abalone are marine mollusks that release eggs and sperm into the water column so that recognition proteins on gamete surfaces are largely responsible for species-specificity . Abalone fertilization is partially controlled by the proteins lysin and VERL ( vitelline envelope receptor for lysin ) . The large glycoprotein VERL ( 3 , 761 amino acids ) contains 22 tandem repeat units which are thought to bind each other to create structural fibers of the egg vitelline envelope , a major barrier to sperm [15] . Sperm release lysin ( ∼150 amino acids ) onto the vitelline envelope where it non-enzymatically unravels VERL fibers , opening a hole for sperm entry [17] . It is hypothesized that lysin disrupts the self-interaction of VERL repeat units by competing for hydrogen bonds [15] . The interaction between vitelline envelopes and lysin is highly species-specific , contributing to reproductive isolation between species [15] , [18] . For example , fertilization efficiency is low in a hybrid cross of Haliotis rufescens eggs and H . fulgens sperm ( ∼10% ) . Yet by adding purified H . rufescens lysin , fertilization by H . fulgens sperm reaches 90% , significantly rescuing the efficiency of heterospecific sperm [19] . This biochemical rescue experiment is analogous to genetic rescue experiments and demonstrates the species-specificity of the lysin-egg interaction . Lysin and VERL show robust signs of positive selection in their divergence between species . Likelihood methods infer both of them to have a class of codons experiencing a significant excess of amino acid substitutions compared to silent substitutions [20] , [21] . Positive selection on lysin was mapped to codons in the structural regions that are important for species-specific dissolution of vitelline envelopes [18] , [22] . Positive selection on VERL was found at repeats 1 and 2 , but not in the remainder of its repeat array [21] . It has been proposed that repeats 1 and 2 are responsible for the species-specificity of the lysin-VERL interaction because the first 2 repeats evolve independently , having diverged from the rest of the array and from each other [23] . The remaining repeats 3 through 22 are highly homogenized by gene conversion or unequal crossing-over and share greater than 95% nucleotide identity . In summary , divergence at lysin and VERL indicates recurrent bouts of positive selection driving amino acid substitutions at the specific structural regions responsible for their interaction . This observation suggests the presence of a coevolutionary process to maintain species-specific sperm-egg recognition . We used the well-characterized interaction between lysin and VERL to test predictions about adaptive coevolution and found support for both hypothesized signatures . We also present polymorphism-based evidence that positive selection acts on VERL and lysin , providing independent support to conclusions from divergence studies . Finally , we discovered an agreement between observed allele frequencies at these genes and predictions made by mathematical models of sexual conflict . Overall , studying both the female and male proteins revealed a more complete picture of reproductive protein evolution and allowed us to address general questions about coevolution .
To examine intraspecific patterns of fertilization protein evolution , we sequenced lysin , VERL , and non-reproductive genes in populations of two abalone species: Haliotis corrugata , the pink abalone , and H . fulgens , the green abalone . For brevity , we will refer to each species by its common name , pink or green . These two species are distributed along the Pacific coast of North America from Point Conception , California , USA to Baja California , Mexico [24] . Population samples of 28 pink and 16 green individuals were collected via non-destructive tentacle clips off Point Loma , San Diego , California . In addition to lysin and VERL , we sequenced genes with no known reproductive function to estimate baseline levels of polymorphism in these populations and to control for population demographic effects on tests of neutrality . Mitochondrial cytochrome oxidase I ( COI ) was sequenced in all individuals of both species . Three additional non-reproductive loci were sequenced in pink abalone . These loci were introns of three nuclear genes encoding slowly evolving , non-reproductive proteins ( rib , eef , and rtp: see Methods ) . Two non-reproductive loci were sequenced in green abalone . One was the intron of a nuclear gene ( rib ) , and the other included intron and exon sequence from the gene encoding cellulase ( cel: see Methods ) . VERL consists of a non-repetitive N-terminal region , an array of 22 large repeats ( each ∼153 amino acids ) , and a non-repetitive C-terminal region [23] . VERL is too repetitive to sequence in its entirety , so we analyzed the regions accessible by PCR: the first two repeats , the last repeat ( representing the 20 repeats which are homogenized by concerted evolution ) , and the unique C-terminal sequence , each of which was sequenced in individuals of both populations . Patterns of intraspecific polymorphism at VERL are very different between pink and green abalone . In green abalone , VERL has only a single polymorphism in all 1 , 470 aligned base pairs ( Table 1 ) . Hence , polymorphism ( θW ) in green VERL is close to zero ( Table 1 ) . The single SNP is non-synonymous and is present at a moderate frequency ( derived allele 16% ) . In the pink abalone , nucleotide diversity at VERL is much higher and even differs significantly between gene regions ( Table 2 ) . Alleles of repeats 1 and 2 are closely related and coalesce in the recent past ( Figure 1 ) , although there are multiple coding differences between them . They contain 13 non-synonymous polymorphisms and a coding insertion-deletion ( indel ) positioned between repeats 1 and 2 . This indel variation is at a small repeat of 11 amino acids present in 1 to 4 copies in the population . In contrast , the last repeat of VERL in pinks ( representing repeats 3–22 ) is the most polymorphic region that we sequenced . Compared with repeats 1 and 2 , there is a significant excess of polymorphism in the last repeat ( Hudson-Kreitman-Aguade test ( HKA ) , P = 0 . 0097 ) [25] . This difference is remarkable because repeats 1 and 2 directly adjoin repeats 3–22 without intervening introns . The high level of polymorphism within the last repeat is evident in its repeat unit phylogeny ( Figure 1 ) . The last repeat also contains a polymorphic indel of 11 amino acids . This indel does not show homology to the N-terminal indel mentioned above , nor is it in linkage disequilibrium with it . All five exons of lysin were sequenced in both species , except for a portion encoding part of the secretion signal . For pink abalone , most of the intron sequence was also obtained , yielding an alignment of almost 6 kilobase pairs ( kb ) of the lysin gene region . In green abalone , a subset of lysin introns was sequenced , yielding more than 2 kb aligned in total . Notably , neither abalone species contained non-synonymous polymorphisms in lysin; however , there were synonymous and intronic polymorphisms . Levels of polymorphism in lysin were lower than at non-reproductive , nuclear loci for both species ( Pink: θW ( lysin ) = 0 . 0014 , θW ( non-rep ) = 0 . 0046; Green: θW ( lysin ) = 0 . 0007 , θW ( non-rep ) = 0 . 0081; Table 1 and Table 2 ) . The non-reproductive theta estimates above were made from a concatenation of the nuclear , non-reproductive loci . The low levels of polymorphism at lysin suggest recent positive selective sweeps , which we will explore in a later section . We first asked whether lysin and VERL were physically linked . We used a mapping family of Haliotis discus , a species closely related to both study populations . The wild-caught male parent was mated to a female from a cultivated strain as previously described [26] . The male parent contained polymorphisms in both lysin and VERL allowing us to score recombination in the progeny . Of 20 genotyped progeny , we observed 11 of the parental male genotype versus 9 recombinants . By examining the log odds ratio ( LOD ) for linkage given the progeny genotypes , we can confidently reject linkage between lysin and VERL at distances of 17 centiMorgans ( cM ) or less ( LOD threshold of −2 . 0 ) ( Section 11 . 3 of Strachan and Read [27] ) . Therefore , there is a great deal of recombination between them and we should not expect linkage disequilibrium simply due to physical linkage . In fact , the progeny genotypes are consistent with independent assortment between lysin and VERL . We studied patterns of linkage disequilibrium ( LD ) between lysin and VERL to test for a genetic association between them , which could result from strong selection for compatible alleles . We studied the pink abalone population because it contained sufficient polymorphisms in lysin , VERL , and non-reproductive genes . The green abalone could not be studied because it contained only one polymorphism in VERL . The strength of LD between any pair of genes was judged by the proportion of single nucleotide polymorphism ( SNP ) comparisons showing statistically significant LD ( α = 0 . 05 ) . Because several polymorphisms within each gene were in LD due to physical proximity we chose a single “tag SNP” to represent each block of associated SNPs [28] . By analyzing tag SNPs , intragenic LD was reduced and single tests between intergenic SNPs became more independent . For example , the average r2 between all lysin SNPs is 0 . 228 , and after choosing tag SNPs it was reduced to 0 . 105 . LD between any pair of tag SNPs was assessed by a test for genotype data , and significance was determined by comparison to a distribution of random permutations [29] . To improve power , we excluded rare SNPs with minor allele frequencies less than 5% [30] . As expected , many intragenic comparisons showed significant LD due to physical linkage ( Figure 2 ) . In contrast , we do not normally expect LD between unlinked genes . Comparisons between non-interacting genes served as a control against genome-wide LD , which could result from cryptic population structure or migration . Only 3 of the 231 comparisons ( 1 . 3% ) between non-interacting genes were significant; however , 16 of the 152 comparisons ( 10 . 5% ) between lysin and VERL were significant ( Figure 2 ) . This proportion between lysin and VERL exceeds the nominal rate of the test ( α = 5% ) . Because comparisons between tag SNPs are more independent , we can use the binomial distribution to show that this proportion was not likely to occur by chance ( P = 0 . 0041 , 16 or more successes in 152 trials ) . We performed these tests again comparing only those SNPs with similar allele frequencies because the comparison of frequency-matched SNPs can be a more sensitive measure of LD [30] . The results were similar: 9 of 110 lysin-VERL comparisons ( 8 . 2% ) and 2 of 183 non-interacting comparisons ( 1 . 1% ) were significant . Although the tag SNPs reduced intragenic LD , the tests were still not completely independent , and remaining LD could lead to correlated results and departures from the nominal rate of the test . Generally , tag SNPs are chosen using a threshold level of r2 to group associated SNPs . As this threshold is dropped , groups will become larger , the number of tag SNPs will decrease , and intragenic LD will decrease . For example , using a threshold of 0 . 1 , average r2 within lysin drops from 0 . 228 to 0 . 048 . To study the robustness of the lysin-VERL association to varying levels of intragenic LD we repeated our tag SNP analysis at a series of lower thresholds starting from the initial level of 0 . 64 , and decreasing to thresholds of 0 . 4 , 0 . 3 , and 0 . 1 . As the threshold dropped , the proportion of significant comparisons between lysin and VERL always significantly exceeded the nominal rate , and actually increased as intragenic LD decreased ( Table 3 ) . In contrast , the proportion of significant non-interacting comparisons remained between 1 and 2% across all thresholds . Because we showed above that lysin and VERL are not closely physically linked , the observed LD between lysin and VERL is consistent with strong selection for compatible alleles . We first tested for positive selection using both divergence and polymorphism data with the McDonald-Kreitman test ( MK ) , which compares the abundances of non-synonymous and synonymous substitutions to non-synonymous and synonymous polymorphisms [31] . The MK test indicated a significant excess of non-synonymous divergence in the first two repeats between pink abalone and an outgroup species , H . discus . ( P = 0 . 012 ) . This constitutes evidence for long-term positive selection for amino acid substitutions in the first two repeats and corroborates the inference of recurrent positive selection in these repeats previously made using only divergence data [21] . In contrast , the last repeat in pink abalone did not show a significant excess of non-synonymous divergence . In the green population , the MK test could not be performed for VERL because only 1 polymorphism was observed . While the divergence-based tests above reflect long-term patterns of evolution , polymorphism data can shed light on recent , population-specific evolutionary events . We first present results for VERL in the pink population . We analyzed the N- and C-terminal portions of VERL separately because they had very different levels of polymorphism and they are separated by more than 8 kb . The N-terminal portion consisted of the first 2 repeats in the repeat array , while the C-terminus consisted of the last repeat and some non-repetitive C-terminal sequence . We first studied the polymorphism frequency spectrum at these regions to test for departures from neutral evolution ( Table 2 ) . In the first 2 repeats , the statistics Tajima's D , Fu & Li's D , and Fay & Wu's H were not significantly different from the neutral expectation [32]–[34] . However , the last repeat of VERL in the pink abalone showed a significantly positive Fu and Li's D statistic , due to an excess of substitutions on internal branches ( Table 2 ) ( P = 0 . 021 ) . This result is consistent with balancing selection favoring the maintenance of divergent lineages in the population . We can see the potential effects of such selection in the relationship of the observed alleles ( Figure S1 ) . For example , alleles of the last repeat are deeply subdivided into two clades separated by an average of 3 . 9 and a maximum of 10 amino acid substitutions and by an indel of 11 amino acids ( Figure 3A ) . The amount of polymorphism between these alleles exceeds divergence between some pairs of abalone species ( Figure 1 ) , because there were only 3 fixed substitutions between pinks and H . cracherodii and 6 to H . discus . Generally , the last repeat contains more polymorphism than all of the non-reproductive loci ( Table 2 ) , although not significantly more ( HKA test , P = 0 . 057 ) . Tajima's D also deviates in the direction expected for balancing selection , although its deviation was not significant ( D = 1 . 06 , P = 0 . 111 ) . Population history , such as structure or growth , can affect patterns of polymorphism and hence influence these statistical tests of neutrality; however , such demographic events would have a general effect on all loci in the genome . We applied the frequency spectrum tests used above to the three nuclear , non-reproductive genes in pinks and confirmed that VERL's deviation from neutrality was locus-specific ( Table 2 ) . An alternative explanation for the observed deep divergence is that concerted evolution brought a rare interior repeat to the last repeat , since interior repeat units could harbor divergent copies . However , the array is thought to be homogenized by concerted evolution , which involves unequal crossing over and/or gene conversion [35] . We looked deeper into the array to get a better picture of this process in pink VERL . We performed a Southern blot to examine 2 pink individuals for sequence divergence among the interior repeat units . First , we excised the VERL repeat array from genomic DNA with restriction enzymes that cut in the second repeat and downstream of the last repeat . We then performed a partial digest in the repeats to determine the repeat types found in the interior . Because we saw two divergent clades of last repeats , we chose a restriction enzyme , Bpu10I , which distinguishes between the two clades . Specifically , Bpu10I cuts in the 33 bp insertion that separates the clades . After performing a partial digest with Bpu10I we probed the non-repetitive C-terminal end of the resulting fragments . If the interior repeats were of the clade containing the insertion , the partial digest should produce a ladder at specific fragment sizes . If instead the array contains different internal repeats we should only see two bands , one at low molecular weight and another at high molecular weight ( uncut by Bpu10I ) . We also searched for sequence divergence with a BsmI partial digest , which should cut at a site in both clades . We performed the partial digests on 2 individuals: one a homozygote at the last repeat for the insertion clade , the other was heterozygous for the two clades . Our sample contained no individuals homozygous for the deletion clade . Individual pink35 produced a ladder of 5 visible bands at the predicted molecular weights for Bpu10I lanes 2&3 ( Figure S2 ) . The 5 fragments were the exact sizes predicted for a single cut in each repeat unit upstream of the last repeat . While the ladder of repeats should continue up to about 20 , we did not expect to see the full ladder because each fragment's abundance decreases with its distance from the probe . The 5 visible bands show that the insertion clade repeat is also found in the 4 immediately upstream repeats . Individual pink36 showed similar bands except the second band ( Figure S2: “d” ) was missing . This indicates either a different repeat clade or a nucleotide substitution in the restriction site . For both individuals the BsmI lanes showed ladders as expected and did not show any evidence for interior repeat divergence . Notably , lane 4 resolved a very large repeat ladder with no evidence for divergence . Overall , the partial digests show that the insertion repeat clade is found in the interior of the array as well as at the last repeat , and that there is some evidence for sequence divergence in pink36 . Also of note , these individuals showed different full repeat array sizes , which are apparent in the non-partially digested lanes ( “1” ) . The band for pink35 is just above the 10 kb marker , which corresponds to a slightly truncated array of approximately 20 units , while individual pink36 is at 11 . 1 kb and approximately 22 units . Such polymorphism in array lengths is expected if unequal crossing-over is occurring . VERL in the green population showed only 1 polymorphism in 1 , 470 aligned basepairs . HKA tests showed that such low polymorphism is not consistent with the expected neutral level of polymorphism . These HKA tests compared both N- and C- terminal VERL regions with each of 3 non-reproductive loci ( rib , cellulase , and COI ) . All comparisons indicated a significant deficiency of polymorphism in VERL: VERL N-terminus vs . rib , cellulase , and COI: P = 0 . 018 , P = 3 . 0×10−5 , and P = 5 . 3×10−8 , respectively; VERL C-terminus: P = 0 . 039 , P = 0 . 0016 , and P = 4 . 1×10−5 , respectively . The 2 HKA tests above which compared VERL to mitochondrial COI were appropriately corrected for the haploid , maternal inheritance of the mitochondrion . This strong reduction suggests a recent selective sweep affecting both termini of green VERL , but unfortunately the lack of polymorphisms also precludes the application of further tests . Using both divergence and polymorphism data , we observed an excess of non-synonymous divergence in lysin for both pink and green populations ( MK tests: P = 0 . 006 and P = 0 . 00044 , respectively ) . This result indicates recurrent positive selection for amino acid changes over long time periods , and is consistent with past divergence studies . We tested the hypothesis of a recent selective sweep at lysin using polymorphism-based methods . Lysin in both populations is characterized by the presence of a single coding allele and by abnormally low levels of silent polymorphism . HKA tests compared polymorphism and divergence between lysin and non-reproductive loci in both species and suggested that these reductions in polymorphism are non-neutral . In pink abalone , 2 nuclear loci indicated a significant reduction at lysin ( lysin vs . rib , P = 0 . 025 , lysin vs . rtp , P = 0 . 0074 ) , while 1 small nuclear locus , eef , did not . The mitochondrial locus COI has roughly the same level of polymorphism as lysin; however , it is more reasonable to compare lysin ( θW = 0 . 0014 ) with COI synonymous site polymorphism ( θWsyn = 0 . 0042 ) because most of lysin's sequenced region is non-coding . In green abalone , polymorphism at lysin is significantly lower than all non-reproductive loci examined ( lysin vs . rib , P = 0 . 0065; lysin vs . cellulase , P = 2 . 2×10−9; lysin vs . COI , P = 5 . 8×10−12 ) . The departure from neutrality between lysin and the non-reproductive loci could be due to either a deficiency of polymorphism at lysin or an excess of divergence in lysin's introns . Estimates of divergence are similar for introns of lysin and the non-reproductive loci ( Table 1 and Table 2 , KJC ) , and there is no reason to expect divergent selection in lysin's introns . Therefore , polymorphism was likely reduced in the lysin gene region by a non-neutral process , such as a recent selective sweep . Overall , green lysin showed a strong reduction in polymorphism and is consistent with a sweep across the entire region . Pink lysin showed a more moderate reduction across the whole gene , but sliding window analysis shows a strong local reduction around exon 1 ( Figure 4B ) . Summary statistics of the polymorphism frequency spectrum ( Tajima's D , Fu & Li's D , and Fay & Wu's H ) were not significantly different from the neutral expectation in either species when calculated over the entire gene region ( Table 1 and Table 2 ) ; however , in pink lysin a sliding window analysis of Fay & Wu's H statistic rejects neutrality from 2 kb downstream of exon 1 until the end of the sequenced region ( Figure 4B ) . Following a sweep , genetic hitchhiking is predicted to form an excess of high frequency derived polymorphisms ( indicated by a low value of H ) flanking a region of strongly reduced polymorphism [34] , [36] . Interestingly , this is what we observed at pink lysin . Frequency-based tests did not reveal evidence for selection at green lysin; however , this does not exclude its possibility because these statistics typically demonstrate low power and detect departures only within specific time periods after a sweep [37]–[39] . A composite likelihood test that takes advantage of our nearly 6 kb of contiguous sequence in pink abalone revealed further evidence of a recent selective sweep . ( This test was not performed in greens because that population only contained 6 SNPs in lysin . ) The composite likelihood method evaluates local patterns of polymorphism for consistency with a selective sweep model by considering the locations and allele frequencies of the observed polymorphisms [40] . We followed the published composite likelihood procedure by Kim and Stephan for testing a particular region using their software . The likelihood ratio statistic , LR1 , which reflects the fit of the data to a selective sweep model , was first computed for the pink lysin data . The statistical significance of this LR1 value was determined by comparison to those of 1 , 000 data sets simulated without a selective sweep but under population parameters inferred from the observed data . We used experimental data to estimate the recombination rate ( 4Ner = 6 . 02×10−3; see Methods ) and baseline polymorphism level ( θW = 0 . 0046; pooled nuclear , non-reproductive loci ) . The inference of a selective sweep at pink lysin was highly significant ( P<0 . 001 ) as no simulated dataset had an LR1 value more extreme than that of the observed data . To test the robustness of this inference to population demographics , we performed a goodness-of-fit test ( GOF ) to a selective sweep model using the method of Jensen et al . [41] . This is an important control because population demographics , such as structure , can create signatures that resemble a selective sweep . A goodness-of-fit statistic ( GOF1 ) evaluated the fit of our lysin data to a selective sweep model when compared with an alternative , parameter-rich model . We then compared the observed GOF1 value to 1 , 000 data sets simulated under a selective sweep with parameters matching those inferred from the data . The GOF test does not reject a selective sweep model for an alternative , parameter-rich model ( P = 0 . 790 ) , which suggests that the selective sweep signature is not due to population demographics . Finally , we used a sliding window profile of the LR1 statistic to infer the genic regions containing the selected mutation . This is inferred where the statistic crosses a significance threshold of ( P = 0 . 01 ) . The profile indicated that the sweep was likely due to a selected mutation at or near exon 1 ( Figure 4A ) . Indeed , nucleotide polymorphism is near zero at exon 1 and steadily increases downstream , consistent with polymorphisms recombining onto the selected haplotype during a sweep ( Figure 4B ) [36] . We inferred the amino acid substitutions leading from a recent ancestor to the extant pink lysin sequence , and 5 of the 10 total substitutions were within exon 1 , any of which could have been responsible for the inferred selective sweep . Notably , previous divergence studies also indicated several codons in exon 1 as frequent targets of positive selection [22] , [42] . We evaluated coevolution between lysin and VERL over long timescales by testing for a correlation of evolutionary rates during the divergence between species . Our expectation was that rates of amino acid evolution for lysin and VERL would co-vary due to compensatory evolution and shared selective pressures . Hence , dN/dS , a measure of evolutionary rate , would correlate between corresponding branches of VERL and lysin phylogenies . We took advantage of 8 closely related species from the north Pacific , including the pink and green species , for which confident sequence alignments could be made and which represent levels of divergence appropriate for the use of codon models ( Haliotis corrugata , H . cracherodii , H . discus , H . fulgens , H . kamtschatkana , H . rufescens , H . sorenseni , and H . walallensis ) . Importantly , synonymous sites are not saturated between these species; for example , the estimated divergence at synonymous sites ( dS ) over the longest branch is 0 . 11 . We determined a phylogenic tree for these species using the coding sequence of lysin and the first 3 repeats of VERL . Using a Bayesian method , one tree topology had a posterior probability greater than 99% and was used to represent the species phylogeny over which the proteins would coevolve ( Figure 5A ) . We tested for a correlation of dN/dS values using several methods . As a first , simple approach we made dN/dS estimates for each branch using the branch model of codeml [22] and analyzed them with linear regression models . Because some short branches had no synonymous changes in lysin , their dN/dS ratios are undefined but codeml assigns an arbitrary value of 999 . These branches were a challenge to using conventional regression models , and to lessen their effect on the regression , we set their dN/dS values equal to 6 , the nearest integer above the largest estimated value . The linear regression of lysin on VERL dN/dS point estimates yielded the predicted positive relationship ( r2 = 0 . 35 ) ( Figure 5B: dotted line ‘r’ ) and was statistically significant ( F1 , 11 = 5 . 83 , P = 0 . 034 ) . Because the extreme dN/dS values on short branches could have a strong influence on this correlation , we also performed the regression after removing those branches with fewer than 5 total substitutions in lysin . The correlation became stronger ( r2 = 0 . 51 ) and remained statistically significant ( F1 , 8 = 8 . 477 , P = 0 . 020 ) . Also , to better account for the uncertainty in each dN/dS estimate we performed a weighted linear regression with the relative amount of divergence on each branch as a weighting factor . The weighted regression was also positive and significant ( r2 = 0 . 40 , F1 , 11 = 7 . 34 , P = 0 . 020 ) ( Figure 5B: dashed line ‘w’ ) . Although these initial results were encouraging , we found them unsatisfactory because the strength of the correlation depended on which corrections were implemented and which value was chosen to limit the extreme dN/dS estimates . Ideally , we wanted a method that would evaluate the correlation while using a model of sequence evolution to account for uncertainty in dN/dS . To this end , we developed a novel method to test the correlation entirely within the phylogenetic model , instead of using point estimates . We created likelihood models in which the evolutionary parameters for both proteins were jointly estimated using the program HyPhy [43] . Our most general model , ‘free’ , allows each branch of both genes trees to have its own dN/dS value . The ‘free’ model is analogous to two branch models of codeml , one for each gene . Next , the ‘correlated’ model constrains dN/dS values to fall on a line of correlation for corresponding branches of lysin and VERL . This line is described by 2 global parameters representing its slope and y-intercept . When optimized , the ‘correlated’ model's likelihood reflects the strength of correlation . The ‘null’ model also models dN/dS values on a line , but its line is constrained to have a slope of zero , representing an uncorrelated relationship between lysin and VERL . A likelihood ratio test between the ‘correlated’ and ‘null’ models tests whether the slope of the correlation line is significantly different from zero . The optimized results for these models are shown in Figure 5 . The ‘correlated’ model described a line closely fitting the dN/dS values of the longer , more informative branches , because the weighting of these branches was inherently higher in the evolutionary model ( Figure 5B: solid line ‘L’ ) . Similarly , the effect of the extreme , undefined values was much less . The ‘correlated’ model fits the data significantly better than the ‘null’ model ( LRT = 4 . 2 , P = 0 . 040; Figure 5C ) . Also , we found that the ‘correlated’ model described the data well because the ‘free’ model was not significantly better ( P = 0 . 94; Figure 5C ) . Since the assumed species tree could influence the outcome of these tests , we explored alternative topologies , including the lysin gene tree , a tree containing polytomies where lysin and VERL trees disagree , and the consensus tree using a maximum likelihood method . ( The VERL tree topology did not differ from the Bayesian-determined topology used initially . ) All of these topologies were largely in agreement , and the few differences were between 4 closely related species ( the bottom 4 leaves in Figure 5A ) . For each of these alternative topologies the ‘correlated’ model rejected the ‘null’ model ( P = 0 . 021 , 0 . 021 , 0 . 048 , respectively ) . In summary , multiple approaches indicated a positive and significant dependency between lysin and VERL dN/dS values during the divergence of these 8 species , reflecting long-term coevolution . To test the robustness of these results , we performed the likelihood test on simulated sequences and between non-interacting abalone proteins . We first simulated “pseudo-VERL” sequences by shuffling its dN/dS values among branches and then simulating along the species tree . We could not perform the same shuffled simulation for lysin because of its undefined dN/dS estimates . We also simulated VERL and lysin sequences by pulling random branch dN/dS values from a gamma distribution while maintaining all other parameters from the observed data . These 3 sets of simulated sequences were then tested for correlated evolution as described above . The shuffled VERL datasets only showed coevolution with lysin that met or exceeded the real data in 1 of 1 , 000 simulations . Similarly , the gamma-distributed VERL datasets exceeded the observed statistic in only 2 of 1 , 000 simulated sets . The simulated lysin sequences showed coevolution with VERL that matched or exceeded the observed data in 148 of 1 , 000 sets . These bootstrap analyses suggest the following p-values for the observed correlation: 0 . 002 , 0 . 003 , and 0 . 148 , respectively . We then sequenced two control genes , cellulase and haemocyanin , in all eight species and tested their correlation with lysin and VERL and with each other . We did not expect correlated rates for these five non-interacting comparisons . None of them were statistically significant , and their LRT statistics were 1 . 52 , 2 . 78 , 1 . 34 , 2 . 08 , and 0 . 40 , compared with 4 . 20 between lysin and VERL .
We used the well-characterized interaction between lysin and VERL to investigate two potential signatures of coevolution . The first signature is the prediction that compatible alleles of lysin and VERL would be associated within individuals . We saw significant signs of association between lysin and VERL but not between non-interacting genes . Such tests between genes require measures to reduce intragenic linkage disequilibrium ( LD ) so that individual SNP comparisons will be more independent . This is a significant challenge as intragenic LD can never be completely removed . However , it can be reduced to low levels by using a tag SNP to represent each block of associated SNPs . We chose multiple sets of tag SNPs to yield lower and lower levels of residual intragenic LD . We found that the proportion of significant comparisons between lysin and VERL remained high and statistically significant for all of these sets ( Table 3 ) . This observation supports an association between a sexually selected trait and preference for that trait , in which the gene controlling preference ( VERL ) would select compatible alleles of the male trait ( lysin ) . This type of selection is a required step in the coevolution of the two genes . An alternative explanation for the association is that lysin and VERL are physically linked; however , to create the observed association via physical linkage , theory predicts that they would need to be very closely linked , at a genetic distance of approximately 0 . 005 cM . Given the results of our progeny array , the LOD score for this distance is less than −33 , and linkage at distances up to 17 cM are ruled out using a LOD threshold of −2 . Hence , physical linkage is not at all likely to be the cause of the observed association between lysin and VERL alleles . Finally , it seems that the observed association between lysin and VERL alleles formed prior to the latest selective sweep in lysin since it currently contains no amino acid polymorphisms . According to this hypothesis we observed the residual LD between lysin SNPs that recombined onto the swept polymorphism . Indeed , the SNPs in LD with VERL are in the downstream portion of the lysin gene , away from the location of the putative selective sweep . The second potential signature of coevolution is a correlation in the rate of amino acid substitution ( dN/dS ) along phylogenetic branches . A correlation is predicted because as one protein experiences an increase in its evolutionary rate , perhaps due to an adaptive episode , the rate of compensatory evolution in its coevolving partner would also increase . In addition , evolutionary pressures acting on both proteins could create a correlation , such as a change in the strength of functional constraint . We considered multiple approaches to test correlated evolution between lysin and VERL: a linear regression of dN/dS point estimates , a weighted regression of point estimates , and a novel set of likelihood models . Each of these approaches showed a positive and significant correlation between lysin and VERL dN/dS values; however , we consider the results of the likelihood method to be the most compelling for several reasons . The likelihood method uses an evolutionary model , so it weighs each branch proportionally to the certainty in its dN/dS value . Second , the branches of lysin without synonymous substitutions and the arbitrarily chosen limit to dN/dS had strong effects on the linear regressions . These various approaches all showed a positive and significant correlation between lysin and VERL evolutionary rates . We also performed several control comparisons to test whether the observed level of correlation between lysin and VERL was unique . Our VERL simulations showed that a correlation of the strength observed between lysin and VERL was rarely observed using random dN/dS values or shuffling of observed values; however , the simulated lysin sequences showed correlations with VERL in about 15% of cases . The cause for this discrepancy between simulated loci is not clear , but it could be an effect of lysin's small size . The lysin simulations cause us to recommend some caution to the conclusion of phylogenetic coevolution . The five comparisons between non-interacting abalone proteins did not show any significant correlations and were not comparable to that between lysin and VERL , so there does not seem to be a genome-wide correlation between proteins in these species . Such a genome-wide correlation could be expected if there were large changes in effective population size along branches . These results support the uniqueness of lysin-VERL coevolution . In general , we found a significant and positive relationship between lysin and VERL evolutionary rates , as predicted under coevolution . In the future it will be interesting to test for such a correlation within other species and between other interacting fertilization proteins . Although general studies of protein networks have revealed correlated rates of evolution for interacting proteins [9] , [10] , [44] , there is debate over how much of the correlation can be attributed to coevolution at the interaction interface or , instead , to shared selective pressures [45] . In the case of lysin and VERL , their divergence is driven predominantly at their sites of interaction , which are the N- and C- termini of lysin and the repeat units of VERL . Therefore , the correlation between lysin and VERL is more likely due to coevolution between their interacting regions . The ‘correlated’ likelihood model can tell us about the relative rates of evolution between the two proteins . Coevolution could proceed through relatively equal numbers of changes to each protein . Alternatively , multiple compensatory substitutions could occur in one protein for each single change in the other . The ‘correlated’ model suggests that the latter relationship exists between lysin and VERL . The slope of the correlation line was approximately 10 , reflecting a greater number of amino acid changes in lysin for each change to VERL . However , this value is also expected to be influenced by the strength of negative selection ( conservation ) on each protein , and so should not be interpreted as the sole effect of compensatory changes . This difference of evolutionary rates suggests that in order to maintain optimal binding , several changes in lysin are required for each change in VERL , a possibility also discussed by Nei and Zhang [46] . Previous studies used divergence between species to infer positive selection on lysin and VERL and to specify the individual codon sites where it acted [21] , [22] , [47] . Our polymorphism data independently support the inference of positive selection on both proteins and even indicate its action at the same structural regions . Polymorphism at lysin was reduced in both pink and green populations , consistent with recent selective sweeps . Selective sweeps at lysin could be very frequent , because in all four species in which a population has been studied , levels of polymorphism are seriously reduced and not a single amino acid polymorphism has been found: Haliotis corrugata and H . fulgens ( this study ) , H . tuberculata [48] , and H . rufescens [47] . The lack of amino acid polymorphism is remarkable considering lysin's extreme rate of divergence [47] . In this study , the composite likelihood method inferred a selective sweep encompassing the first exon of pink lysin , in agreement with the codons frequently inferred under selection using divergence data [22] and consistent with experimentally determined species-specific domains discovered through site-directed mutagenesis [18] . This agreement is a nice example of functional data correlating with evolutionary analyses . Similar to lysin , VERL in green abalone may have undergone a recent selective sweep because there was only 1 polymorphism among 32 chromosomes , and such a severe reduction in polymorphism over 1 , 470 bp was inconsistent with neutral evolution . VERL in the pink abalone was more complex . When we looked at divergence and polymorphism together using the McDonald-Kreitman test , we saw a significant excess of non-synonymous divergence at repeats 1 and 2 . This result corroborates dN/dS analyses in which recurrent positive selection was inferred within the first 2 repeats but not in the remainder of VERL [21] . Polymorphism-based evidence alone sheds light on recent , population-specific evolution at pink VERL . While the first 2 repeats showed no polymorphism-based evidence of recent selection , the last repeat of pink VERL showed a signature different from all other analyzed regions . It had a high level of polymorphism , and alleles were divided into 2 clades , each separated by multiple amino acid changes and an 11-amino acid indel ( Figure 3A ) . Such high diversity could be created as a result of frequency-dependent or balancing selection , as is suggested by the frequency spectrum tests . An alternative explanation could be that the array contains divergent internal repeats , one of which moved to the last repeat by gene conversion . We also consider this a plausible alternative; however , three experimental results lead us to prefer selection . The question is whether the rate of array homogenization via concerted evolution is great enough to suppress deep divergence among internal repeats . One allele of VERL in H . rufescens has been completely sequenced . All of its repeats 3 through 22 showed at least 95% nucleotide identity , and hence did not contain divergent interior repeats [23] . Another study randomly cloned interior repeats from several species , and the repeat units were closely related [35] . Finally , our Southern blot did not reveal great divergence in the interior repeats . It will take additional in-depth studies of VERL alleles to better distinguish between these two hypotheses . While previous divergence studies did not infer positive selection in repeats 3 through 22 [21] , our observations in pink and green abalone suggest more complex evolution , possibly involving selective episodes . Several hypotheses are offered to explain the rapid divergence of fertilization proteins [2] . One such hypothesis , sexual conflict , describes a scenario in which the adaptive optimum of a trait differs between males and females [49] . When the conflict is mediated by different genes in males and females ( interlocus sexual conflict ) , a continuous , adaptive struggle between male and female characters results . Indeed , experimental evolution in Drosophila has demonstrated that such antagonistic evolution between the sexes can occur as predicted [50] . For fertilization , there is a predicted sexual conflict over the fertilization rate and its effect on polyspermy . Polyspermy is the fertilization of an egg by multiple sperm , which in many species halts development . The optimum fertilization rate for a male is fast in order to outcompete sperm from other males [51] , while the optimum for females is a moderate rate to control sperm entry and minimize the number of her eggs killed by polyspermy . Polyspermy increases when the rate of fertilization is too high because eggs cannot activate their defensive blocks before additional sperm fuse . There is evidence that the fertilization rate is not optimal for female abalone because their eggs suffer from polyspermy under natural sperm concentrations [52] . In addition , abalone have been observed in nature to spawn in aggregated groups and even in stacks of multiple individuals which would produce high local concentrations of sperm [53] , [54] . Generally , polyspermy rates can be high in natural populations of free-spawning organisms , even under sperm-limited conditions [55] , [56] , and so the potential for conflict is great . Polyspermy is directly related to fitness because it strongly affects the number of viable offspring , and hence a sexual conflict over fertilization rate would be strong . In theory , as the rate increases over generations due to sperm competition , the egg would counter-adapt to slow and regulate sperm entry . There is evidence that amino acid changes in lysin and VERL affect the fertilization rate in such a way . Lysin dissolves egg vitelline envelopes in a species-specific manner [15] , and introducing lysin segments from one species into another has the corresponding effect on specificity [18] . While this experimental evidence shows the potential for lysin and VERL to control fertilization rate , and hence to mediate sexual conflict , theoretical predictions also corroborate a sexual conflict between lysin and VERL . Mathematical models have predicted genetic outcomes within populations experiencing a sexual conflict [57] . The most common observation is a coevolutionary chase between female and male genes , involving recurrent adaptive evolution in both . An alternative outcome is also observed in which the female gene temporarily wins the conflict by diversifying and hence trapping the male gene at an intermediate position [58] , [59] . In this situation , the female alleles form 2 distinct clades , and the male gene possesses a single allele that is equally adapted to each clade , yet suboptimal for either individually ( Figure 3B ) . We found close resemblance between this stalemate outcome and alleles in the pink abalone; VERL last repeat alleles formed divergent clades separated by several protein differences ( Figure 3A ) , and lysin showed only one coding allele . This stalemate outcome could also explain our hypothesis of balancing selection at VERL , because frequency-dependent selection would effectively maintain the two divergent clades . Notably , if we had studied only the male protein this pattern would have been missed . Generally , such a conflict over fertilization rate could be operating in diverse taxonomic groups because positive selection is widely observed at fertilization genes [60] . If conflict is widespread , it has great potential to drive the divergence of fertilization proteins and lead to reproductive isolation and speciation between allopatric populations . In theory , a sexual conflict could even drive speciation in a freely-mating ( sympatric ) population , because models show that the male gene could counter-diversify in response to the stalemate outcome , resulting in assortative mating [58] .
Haliotis corrugata ( pink ) and H . fulgens ( green ) abalone DNA samples were isolated from non-destructive tentacle clips of individuals off Point Loma , San Diego , California , USA . Total DNA was isolated using the PUREGENE DNA purification kit ( Gentra Systems , Inc , Minneapolis , Minnesota , United States ) . Genotypes were determined for VERL , lysin , and non-reproductive loci by PCR amplification from total genomic DNA followed by direct sequencing . We also sequenced these loci from Haliotis discus for use as an outgroup for H . corrugata , except for the first 2 repeats of VERL which were available in GenBank entry AF490763 . PCR primers were designed from published transcripts of the lysin and VERL genes ( Genbank M34389 , M98875 , AF490764 , AF490763 ) . We determined most of the lysin gene in pink abalone , including introns 1 , 2 , and 4 . We also sequenced part of intron 3 . The length of the unsequenced portion of intron 3 was estimated from a long-range PCR product spanning the region . Resequencing yielded almost 6 kb in each of 25 individuals for the pink lysin gene . In green abalone individuals , all exon and some flanking intron sequence of lysin was determined . Due to VERL's large repeat units ( ∼453 bp ) , only exterior repeats are accessible by PCR . Repeats 1 , 2 , and the C-terminal repeat were amplified by placing a primer outside the repeat array . Sequence coverage in pink and green abalone VERL was identical . For each pink individual , the number of 11-amino acid repeats between the larger repeats 1 and 2 was determined from the lengths of PCR products spanning this mini-repeat array . Introns of non-reproductive genes were amplified in pink abalone using PCR primers based on transcribed sequences from a H . corrugata ovary cDNA library [61] . Transcripts encoding highly conserved proteins were chosen to avoid loci potentially under positive selection . The intron-exon structure of these conserved genes was assumed identical to vertebrate homologs , and primers were placed within the boundaries of conserved exons . This resulted in successful PCR amplification of over half of attempted introns . The nuclear introns chosen for genotyping were from an abalone homolog of the oyster Ribosomal Protein L5 ( rib ) , a homolog of Elongation Factor-2 ( eef ) , and a homolog of Receptor Protein Tyrosine Phosphatase Delta ( rtp ) . A mitochondrial locus , cytochrome oxidase I ( COI ) , was amplified using published primers [47] . Four H . fulgens ( green ) COI sequences were retrieved from GenBank ( AY679078-81 ) . Our PCR primers are listed in the Supplementary Text S1 , and PCR conditions are available from the authors upon request . Single band PCR products were sequenced on an ABI 3100 using Big Dye v . 3 . 1 ( Applied Biosystems , Foster City , California , United States ) . Sequence reads were called , aligned , and analyzed using phred , phrap , and consed [62] , [63] . Polymorphisms were flagged by polyphred and visually confirmed [64] . Genotypes at each polymorphic site were verified manually , checked for Hardy-Weinberg equilibrium , and then transferred by Perl scripts to a phase-determining program , PHASE [65] . Control coding sequences for the phylogenetic coevolution method were sequenced from 8 species . Cellulase primers were designed from GenBank entry AB125892 which was also the source for the H . discus sequence . Hemocyanin coding sequences incorporated some of that produced by Streit et al . [66] , and we performed additional sequencing using primers designed from GenBank entries AJ749644 , AJ749646 , AJ749647 , AJ749648 , AJ884595 , AJ884596 , and AJ252741 . Gene regions newly sequenced in this study are available in GenBank entries FJ940228-FJ940677 . The sequences for all 32 chromosomes at the C-terminal region of VERL in H . fulgens ( greens ) were identical to GenBank entry DQ453752 from nucleotide 85 to 774 , and so they were not submitted . We chose a set of representative tag SNPs for each gene using the program ldSelect under the default parameters [28] . Gametic phase is unknown when testing for linkage disequilibrium ( LD ) between unlinked genes . To test LD in this situation we used a likelihood ratio test for genotype data implemented in Arlequin [67] . LD is tested for each pair of SNPs using a likelihood-ratio test which is compared to an empirical distribution generated by a permutation procedure [29] . This test assumes Hardy-Weinberg equilibrium , so sites that violated this assumption at the α = 0 . 01 level were removed from analysis . This LD test on genotypes performs well when the number of alleles is low; in our dataset , all SNP loci had only 2 alleles . We excluded rare variants below a minor allele frequency of 5% . In one test , frequency-matched SNPs were compared to improve power [30] . SNPs were considered frequency-matched if their minor allele frequencies were not more than 10% different , as recommended by Eberle et al . [30] . Summary statistics and sliding windows of polymorphism were calculated in DnaSP [68] . P-values for tests of selection were generated in DnaSP using coalescent simulations under the conservative assumption of no recombination . Hudson-Kreitman-Aguade ( HKA ) tests and McDonald-Kreitman tests were also performed in DnaSP . HKA tests comparing nuclear to mitochondrial loci in the green abalone used the appropriate correction for the haploid , maternal inheritance of the mitochondrion . Phylogenies of VERL segments in Figure 1 were determined and plotted using dnaml and drawgram of the PHYLIP package [69] . Haplotype networks in Figure 3 were created by TCS [70] . Lysin's haplotype network was based on the largest region without evidence of recombination between SNP markers ( ∼1 kb ) , and the network for the last repeat of VERL included our entire 306-basepair sequence of that region . We isolated genomic DNA from 2 individuals , one a homozygote for the last repeat type and the other a heterozygote . We first used two restriction enzymes to excise the VERL repeat array . These cut in the second repeat ( BclI ) and 1 . 6 kb downstream of the last repeat ( BsaI ) , and were allowed to cut to completion for 3 hours at 50°C . Partial digests were carried out for 2 different durations . We performed partial digests with Bpu10I at 37°C for 30 seconds and for 2 minutes . Partial digests with BsmI were performed for 15 and 45 seconds at 65°C . All enzymes were obtained from New England Biolabs ( Ipswich , Massachusetts , USA ) . Reactions were performed in 30 µl volumes with 2 µg genomic DNA each . We loaded 10 units ( U ) of each restriction enzyme except for BsmI for which we used 3 U . Seven such reactions were run for each condition so that we digested 14 µg of genomic DNA for each lane . Reactions for each condition were pooled and the DNA was ethanol precipitated , which recovered about 8 µg for each lane . All recovered DNA was loaded into a 0 . 8% agarose gel and run for 15 hours at 40V in re-circulated TAE . DNA was blotted onto a nylon membrane using capillary action with ammonium acetate buffer as described in chapter 5 . 2 of Molecular Genetic Analysis of Populations [71] . Twenty-five ng of a 500 basepair PCR product of the C-terminal unique region of VERL was labelled with 32P by nick translation with a NEBlot kit ( New England Biolabs , Ipswich , Massachusetts , USA ) . Hybridization was carried out at 65°C overnight followed by washes in standard saline citrate . We performed a composite likelihood test for selective sweeps according to the procedure outline by the developers [40] . Selective sweep parameters and a composite likelihood statistic were inferred from the pink lysin data , and 1 , 000 neutral simulations were performed under parameter values estimated from the data . The values of the composite likelihood statistic from these simulations formed a null distribution against which to test a selective sweep in the data . Polymorphisms were polarized to ancestral and derived alleles using an outgroup sequence from H . discus . The average recombination rate in pink abalone was estimated from the sex-average genetic map length for a close relative , H . discus ( 2 , 320 . 1 cM ) [72] and the measured genome size of pink abalone , H . corrugata ( C-value = 2 . 00 pg: ∼1 , 956 Mb ) [73] . These values yield a sex-average estimate of 1 . 19 cM/Mb across the pink abalone genome . Using the same method , our estimate for the human genome ( 1 . 02 cM/Mb ) is near the generally agreed upon value ( 1 . 30 cM/Mb ) [74] . We estimated the effective population size ( Ne ) of pink abalone using the formula: Ne = θ/4μ . Polymorphism was estimated from the 3 nuclear , neutral loci ( θW = 0 . 0046 ) , and the nucleotide mutation rate per generation was taken from an experimental measurement in C . elegans ( μ = 9 . 1×10−9 ) [75] . Hence our estimate of the recombination rate ( 4Ner ) was 6 . 02×10−3 in pink abalone . The goodness of fit procedure for testing the robustness of an inferred selective sweep to population demographics was performed as prescribed [41] . The goodness of fit statistic ( GOF1 ) for the sweep in pink lysin was compared to 1 , 000 simulations under parameter estimates for the inferred sweep . We tested the relationship between VERL and lysin dN/dS ratios using linear regressions on point estimates and using novel likelihood models . Both approaches used multiple alignments of VERL and lysin from 8 species . The VERL alignment consisted of repeats 1 , 2 , and 3 as presented in Galindo et al . [21] . Lysin coding sequences for the same 8 species were retrieved from GenBank . A tree topology for these 8 species was determined by MrBayes using a concatenation of lysin and VERL and using the general reversible nucleotide model with rate variation modeled by the gamma function with a proportion of invariable sites [76] , [77] . Linear regressions were performed using the ‘R’ program ( http://www . r-project . org/ ) on branch dN/dS values estimated by the codeml program of the PAML package [78] . Three joint likelihood models were created to evaluate the strength of correlation of branch-specific dN/dS values of lysin and VERL . We constructed and maximized these models using a custom script written for HyPhy version 0 . 9920060106beta for Macintosh OSX [43] . The ‘free’ model is parameter-rich and has a separate dN/dS value for each branch of each gene . The ‘free’ model will fit the data relatively well compared to the subsequent models . The ‘free’ model was created by partitioning the data into lysin and VERL and assigning a codon model and the tree topology determined above . Values of dN and dS were estimated using the Goldman and Yang codon model ( GY94 ) [79] . The ‘correlated’ model was created to judge how well a correlated relationship explains the variation in branch dN/dS values . It was created by placing the following constraint on each phylogenetic branch , i:Slope and y-intercept are global parameters defining the correlation line ( Figure 5B: solid line ‘L’ ) . We optimized the ‘correlated’ model starting from 6 different initial values of the slope parameter to ensure convergence . The ‘null’ model was created to test if the correlation in the ‘correlated’ model is statistically significant . The ‘null’ model is defined by constraining the slope parameter to zero . Both VERL and lysin were analyzed as the dependent variable in the ‘null’ model and the maximum likelihood of the two was used . This step was necessary because both cases are uncorrelated and yet their maximum likelihoods are different . Finally , comparing the nested ‘correlated’ and ‘null’ models tests whether the slope parameter is significantly non-zero . A P-value for the rejection of the ‘null’ model in favor of the alternative ‘correlated’ model was obtained using a likelihood ratio test in which the twofold difference in their maximum log likelihoods is assumed to follow a χ2-distribution with degrees of freedom equal to the difference in the number of parameters . There is one degree of freedom between the ‘correlated’ and ‘null’ models . Model optimizations began with tree distances as initial parameter values and used a precision of 1×10−5 .
|
When a sperm meets an egg , it must display the correct recognition proteins to achieve fertilization . Given the importance of fertilization one would think these proteins are perfected and do not change over time; however , recent studies show that they do change and quite rapidly . Thus , the sperm and egg must change together in harmony , through a process called coevolution , so the species can successfully reproduce . We followed the sperm–egg coevolutionary process at the level of genes: one that makes the protective egg coat and a sperm gene which opens that coat for fertilization . By examining their DNA sequences in two abalone species , we revealed two coevolutionary signatures . In one case , we discovered an association of variants between the egg and sperm genes , the origin of which could be strong preference for compatible variants . In the second case , we demonstrated that both genes changed at correlated rates over millions of years of evolution . Whenever one gene had accelerated in one species , the other showed a parallel acceleration in that same species . These unique signatures help us to understand coevolution by revealing its strength within natural populations and by showing that it has acted consistently over long time periods .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biochemistry/molecular",
"evolution",
"evolutionary",
"biology/evolutionary",
"and",
"comparative",
"genetics",
"evolutionary",
"biology/sexual",
"behavior",
"molecular",
"biology/molecular",
"evolution",
"evolutionary",
"biology",
"genetics",
"and",
"genomics",
"genetics",
"and",
"genomics/population",
"genetics"
] |
2009
|
Coevolution of Interacting Fertilization Proteins
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Epstein-Barr virus ( EBV ) is linked to a broad spectrum of B-cell malignancies . EBV nuclear antigen 3C ( EBNA3C ) is an encoded latent antigen required for growth transformation of primary human B-lymphocytes . Interferon regulatory factor 4 ( IRF4 ) and 8 ( IRF8 ) are transcription factors of the IRF family that regulate diverse functions in B cell development . IRF4 is an oncoprotein with anti-apoptotic properties and IRF8 functions as a regulator of apoptosis and tumor suppressor in many hematopoietic malignancies . We now demonstrate that EBNA3C can contribute to B-cell transformation by modulating the molecular interplay between cellular IRF4 and IRF8 . We show that EBNA3C physically interacts with IRF4 and IRF8 with its N-terminal domain in vitro and forms a molecular complex in cells . We identified the Spi-1/B motif of IRF4 as critical for EBNA3C interaction . We also demonstrated that EBNA3C can stabilize IRF4 , which leads to downregulation of IRF8 by enhancing its proteasome-mediated degradation . Further , si-RNA mediated knock-down of endogenous IRF4 results in a substantial reduction in proliferation of EBV-transformed lymphoblastoid cell lines ( LCLs ) , as well as augmentation of DNA damage-induced apoptosis . IRF4 knockdown also showed reduced expression of its targeted downstream signalling proteins which include CDK6 , Cyclin B1 and c-Myc all critical for cell proliferation . These studies provide novel insights into the contribution of EBNA3C to EBV-mediated B-cell transformation through regulation of IRF4 and IRF8 and add another molecular link to the mechanisms by which EBV dysregulates cellular activities , increasing the potential for therapeutic intervention against EBV-associated cancers .
Tumor viruses have evolved multiple strategies for modulating the expression of an array of cellular genes to enhance persistence , latency and survival of infected cells . Studies into these strategies have provided several lines of evidence as to the mechanisms of differential gene expression and their deregulation during oncogenesis . Particularly , EBV is responsible for the development of lympho-proliferative diseases manifested in immuno-compromised AIDS patients [1] , and is also linked to Burkitt's lymphoma , Hodgkin's lymphoma , B and T cell lymphomas , anaplastic nasopharyngeal carcinoma , and also some forms of gastric carcinomas [2] . Human primary B lymphocytes are the principal target for EBV infection , although the virus has the potential to infect other lymphocytes and epithelial cells [3] . EBV infection transforms primary human B-cells into continuously growing lymphoblastoid cell lines ( LCLs ) with the establishment of viral latency [4] . Three major types of viral latency have been elucidated with each having their own specific viral gene expression pattern , although other patterns have been described [5] . EBV latency proteins are comprised of EBV nuclear antigens , such as EBNA1 , EBNA2 , EBNA3A/3 , EBNA3B/4 , EBNA3C/6 and three latent membrane proteins LMP1 , LMP2A and LMP2B [6] , [7] . These proteins are all expressed in type III latency , also referred as the growth programme [8] . Six of the EBV encoded latent proteins including , LMP1 , EBNA-LP , EBNA1 , EBNA2 , EBNA3A and EBNA3C were found to be important or critical for B-cell immortalization in vitro [9] . EBNA3C , as demonstrated by genetic analysis using recombinant virus strategies is necessary not only for proficient immortalization of primary human B-cells in vitro [10] , but also for the purpose of cell-cycle progression and growth maintenance of EBV-positive lymphoblastoid cells [1] . Interestingly , EBNA3C has the ability to perform both functions as a transcriptional activator and repressor [11] , and can interact with a wide range of transcriptional modulators , like PU . 1 , Spi-B , HDAC1 , CtBP , DP103 , p300 , prothymosin-α , Nm23-H1 , SUMO1 and SUMO3 [12] . EBNA3C also plays a critical role in deregulation of mammalian cell-cycle by targeting different cellular onco-proteins and tumor suppressors [13] . Recently , we demonstrated that EBNA3C negatively regulates p53 functions by interacting with ING4 and ING5 [14] . The mammalian interferon regulatory factor ( IRF ) family of transcription factors were categorized as transcriptional regulators of type I interferon ( IFN ) and IFN-inducible genes [15] . However , recent studies have revealed that this protein family also plays a vital role in regulation of host defence beyond its function in the IFN-system [16] . The IRF family is comprised of nine members , which include IRF1 , IRF2 , IRF3 , IRF4 , IRF5 , IRF6 , IRF7 , IRF8/ICSBP , and IRF9/ISGF3 [17] . IRFs have also been linked to viral induced transformation as EBV-encoded LMP-1 can induce the expression level of IRF7 and its activation through receptor-interacting protein ( RIP ) -1 and TRAF6 [18] . IRF7 promotes anchorage-independent growth of NIH-3T3 cells , and with LMP-1 , it shows an additive effect on the growth of these cells [19] . IRF4 , also known as LSIRF , ICSAT , Pip , and Mum1 , was cloned independently as the homologous member of the IRF gene family and as an interacting partner of PU . 1 [20] . IRF4 is expressed at all developmental stages of B-cell , in mature T-cells , and also in macrophages [21] , and the analysis of IRF4 knockout mice revealed that IRF4 is vital for the function and homeostasis of both mature B and T-lymphocytes [22] . IRF4 also has an essential role in T-cell immune responses [23] . In macrophages , IRF4 is essential for TLR signalling [24] and is essential for the expression of surface major histocompatibility complex class II ( MHCII ) molecule in dendritic cells for antigen presentation [25] . There are some reports which suggest that IRF4 also plays an important role in receptor editing [26] . More recently studies have indicated that IRF4 , when overexpressed , functions as an oncoprotein [27] . On the contrary , IRF4 was found down-regulated in some myeloid and early B-lymphoid malignancies [28] , and so IRF4 may have different functions in the context of different cell types [29] . IRF4 deficiency facilitates the progression of BCR/ABL-induced B-ALL , while forced expression of IRF4 potently supresses the pathogenesis of BCR/ABL-induced B-ALL [28] . These findings demonstrated that IRF4 can also functions as a tumor suppressor in the myeloid lineage and in early stages of B-cell development . IRF4 is linked to human T-cell Leukemia virus-induced transformation [30] , has oncogenic potential in vitro and can inhibit apoptosis [31] . Recently , it was demonstrated that IRF4 indirectly regulates miR-155 , an evolutionarily conserved miRNA , via B-cell integration cluster ( BIC ) [32] . IRF4 is also important in the pathogenesis of multiple myeloma [33] , and is involved in EBV mediated growth transformation of B-lymphocytes [34] . Furthermore , IRF4 is also known to be involved in regulation of EBV-mediated cell growth by down-regulating the expression level of IRF5 , another pro-apoptotic member of interferon regulatory factors [35] . This report now shows that IRF4 can play a crucial role in modulating the activities of other critical IRF transcription factors in EBV transformed cells . Interferon regulatory factor 8 ( also known as IFN consensus sequence-binding protein/IRF8 ) is another potent transcription factor belonging to the IRF family [36] . Expression of IRF8 is generally seen in hematopoietic cells , including monocytes , macrophages and the subsets of lymphocytes [37] . In case of late myeloid differentiation , IRF8 plays an important role in the commitment to macrophage differentiation and is essential for the function of mature macrophages [38] . In contrast , IRF8-null mice show noticeable clonal expansion of undifferentiated granulocytes and macrophages , which often progress to a chronic myelogenous leukemia ( CML ) like syndrome in these animals [39] , [40] . Notably , IRF8 expression was found dramatically decreased in patients with CML and acute myeloid leukemia ( AML ) [41] . These studies suggested that IRF8 plays a crucial role in regulation of leukemogenesis and functions as a tumor suppressor of certain myeloid malignancies . The molecular mechanism involved in the control of leukemogenesis by IRF8 is yet to be delineated . However , IRF8 deficiency in hematopoietic cells leads to declined spontaneous apoptosis and enhanced resistance to the extrinsic apoptotic induction [42] . These results provide clues as to another potential branch in regulation of critical cellular regulatory components by EBNA3C . In this current study , we now provide the first evidence linking EBNA3C to differential regulation of IRF4 and IRF8 and show that they can contribute to B cell transformation . Interestingly , our work demonstrated a molecular interplay between IRF4/IRF8 and EBNA3C . Detailed mapping revealed that 29 residues within the N-terminal domain of EBNA3C interact with IRF4 and IRF8 and this interaction led to stabilization of IRF4 by inhibiting its Ub-proteasome-mediated degradation and enhancing the degradation of IRF8 . We also found that a Spi-1/B-like motif within the C-terminal domain of IRF4 plays a critical role in binding to EBNA3C . Additionally , RNA interference based strategy to knock-down endogenous IRF4 showed a significant reduction in EBV transformed cell proliferation , as well as increased sensitivity to etoposide-induced apoptosis . We also demonstrated significant down-modulation of IRF4 targeted proteins such as , c-Myc , Cyclin B1 and Cyclin-dependent kinase 6 ( CDK6 ) upon EBNA3C or IRF4 knockdown in lymphoblastoid cells . These results imply that EBNA3C mediated activation of IRF4 and its downstream signalling may deregulate important cellular functions which include proliferation , apoptosis , and cell-cycle which favour the development of B-cell lymphomas . These findings provide important clues to yet another fundamental role of EBNA3C in contributing to EBV-mediated B-cell oncogenesis via differential regulation of IRF4 and IRF8 .
IRFs are important contributors to pathogenesis associated with human malignancies [15] . IRF4 is associated with enhanced pathogenesis of EBV-mediated growth transformation of B-lymphocytes , and has been shown to play a primary role in cell proliferation of multiple myeloma [43] , [44] . IRF8 has been characterized as a major transcription factor in the IRF family of proteins [45] , and its levels are dramatically decreased in CML and myeloid leukemia cells [46] . Here we examined whether IRF4 and IRF8 are potentially involved in EBV mediated B cell transformation as proteomic analysis of EBNA3C complexes isolated from LCLs identified IRF4 and IRF8 . To determine the status of IRF4 and IRF8 levels after EBV infection , 10 million human peripheral blood mononuclear cells ( PBMC ) were infected with BAC-GFP EBV and the cells were harvested at different time points . Western blot analysis showed up-regulation of IRF4 but no observed change in IRF8 protein level after 0 , 2 , 4 , 7 and 15 days of post-infection ( Fig . 1A ) . Western blot analysis of IRF4 and IRF8 levels were also performed in EBV transformed LCL1 , LCL2 cells compared to EBV negative BJAB , DG75 and Ramos cell lines . The results showed a significant upregulation of IRF4 levels , but similarly IRF8 levels remained relatively unchanged ( Fig . 1B ) . To further investigate this phenomenon , we analyzed the Burkitt's lymphoma cell line , EBV negative BL41 with and without the wild type EBV strain B95 . 8 . Here again , BL41/B95 . 8 cells showed an increased level of IRF4 protein in this isogenic background which was not seen for IRF8 . To determine if these differential protein expressions were related to expression of a specific EBV latent antigen expressed during latency type III , we analyzed the results from the Burkitt's lymphoma cell lines Mutu III ( latency III ) compared with Mutu I ( latency I ) [47] . Interestingly , a similar level of elevated IRF4 protein expression pattern was seen in Mutu III but again little or no detectable change seen in case of IRF8 ( Fig . 1C ) . To verify whether EBV infection was responsible for the change in Irf4 compared to Irf8 mRNA expression level as suggested by the above results , human peripheral blood mononuclear cells ( PBMC ) were infected with BAC-GFP EBV as previously described [48] . 0 , 2 , 4 , 7 and 15 days post-infected samples were harvested for mRNA isolation and Real-time PCR analysis . Importantly , the result showed no detectable change in Irf4 and Irf8 mRNA levels ( Supplementary Fig . S1A ) . Additionally , our real-time PCR analysis with EBV transformed LCL1 and LCL2 cells in comparison with EBV negative BJAB indicated no significant change in Irf4 and Irf8 mRNA expression levels ( Supplementary Fig . S1B ) . To determine what effect EBNA3C may have on IRF4 and IRF8 , EBV negative Burkitt's lymphoma cell line BJAB and BJAB7 , BJAB10 ( EBNA3C stably expressed in BJAB ) cells were subjected to real-time PCR analysis . The data showed a similar mRNA expression pattern for Irf4 and Irf8 as before with no significant change ( Supplementary Fig . S1C ) . Besides , we also compared the transcript level of EBNA3C in DG75 , BJAB with LCL1 , and LCL2 . The result indicated that as expected the EBNA3C levels were substantially expressed in LCLs ( Supplementary Fig . S1D ) . Therefore , these results confirm that regulation of IRF4 and IRF8 in EBV infected cells is most likely through post-translational modification of the polypeptides . Previous reports showed that the EBV latent membrane protein 1 ( LMP1 ) induced IRF4 expression [43] . To examine whether EBNA3C can directly regulate the expression of IRF4 , we performed Western Blot analysis on P3HR1 and Jijoye cell lines , two isogenic Burkitt's Lymphoma lines [49] . Both cell lines are EBV positive and express EBNA3C , whereas P3HR1 lacks EBNA2 and a portion of EBNA-LP gene [50] . Consequently , due to that deletion , P3HR1 cells express negligible levels of LMP1 [51] . Our results clearly indicated that the expression levels of IRF4 are similar in these two cell lines ( Supplementary Fig . S2 ) . To explore the effect of EBNA3C on IRF4 and IRF8 , EBV negative BJAB and BJAB7 , BJAB10 cells were analyzed by Western blot . The results demonstrated a significant increase in IRF4 protein expression level and a substantial reduction of IRF8 expression ( Fig . 1D ) . Therefore , these results further support a direct role for EBNA3C in regulation of IRF4 and IRF8 independent of other EBNAs or LMP1 . We next investigated the protein expression levels of IRF4 and IRF8 with a dose-dependent increase of EBNA3C in EBV negative DG75 B-cell line . Our results showed that the IRF4 protein level steadily increased , but the detected IRF8 protein level decreased with increasing amounts of EBNA3C ( Fig . 1E ) . To further elucidate the role of EBNA3C in modulating the levels of IRF4 and IRF8 , we performed Western blot analyses on LCLs which were stably knocked-down for EBNA3C with specific EBNA3C short hairpin RNA ( Sh-E3C ) . We observed that the IRF4 protein expression levels were significantly decreased as compared to the sh-control ( Sh-Ctrl ) LCLs . However , the protein expression level of IRF8 was found higher in EBNA3C knocked-down cells , when compared with the sh-control vector stably transfected LCL1 ( Fig . 1F ) . We further examined whether IRF4 and IRF8 can directly associate with EBNA3C . First , we performed in vivo co-immunoprecipitation assays in EBV positive cells . In addition , HEK-293 cells were co-transfected with expression constructs for Myc-tagged EBNA3C and IRF4 , IRF8 tagged with the Flag epitope . Immunoprecipitation analysis as shown in Fig . 2A , clearly demonstrated a strong association of EBNA3C with IRF4 and IRF8 in cells . Further , we checked the interactions using GST pull-down experiments , with cell lysates prepared from two transformed EBV-positive lymphoblastoid cell lines-LCL1 and LCL2 , EBV negative BJAB and EBNA3C expressing BJAB7 and BJAB10 . The results demonstrated that EBNA3C strongly interacted with the GST-IRF4 and GST-IRF8 fusion proteins but not with the GST control ( Fig . 2B ) . The amount of control GST and GST-IRF4 , GST-IRF8 fusion proteins used in this GST-pulldown experiment was shown in a parallel gel with Coomassie Blue staining ( Fig . 2C ) . To further support this association as on endogenous complex , EBNA3C , IRF4 or IRF8 were immunoprecipitated from BJAB , EBV transformed LCL1 and LCL2 cells , as well as BJAB7 and BJAB10 ( Fig . 2D , E ) . Data analyzed from the ectopic expression as well as LCLs endogenously expressing IRF4 , IRF8 and EBNA3C confirmed a substantial association of IRF4 and IRF8 with EBNA3C in a molecular complex in EBV-infected cells . In order to determine the specific domain of EBNA3C that interacts with IRF4 and IRF8 , HEK-293 cells were co-transfected with expression constructs for Flag-IRF4 , Flag-IRF8 , Myc-tagged full length EBNA3C ( residues 1–992 ) or different truncated mutant of EBNA3C ( residues 1–365 , 366–620 or 621–992 ) and co-immunoprecipitation experiment was performed with anti-Myc antibody . The result illustrated that only the full length or N-terminal truncated EBNA3C co-immunoprecipitates with IRF4 and IRF8 . On the other hand , no co-immunoprecipitation was observed with other truncated mutants of EBNA3C ( Fig . 3A , B ) . To further corroborate the association results , we performed in-vitro GST-pulldown assays using in-vitro translated full length and truncated EBNA3C mutant fragments followed by the co-incubation with bacterially expressed and purified GST-IRF4 and GST-IRF8 proteins . The result indicated that the N-terminal EBNA3C directly interacted with both IRF4 and IRF8 ( Fig . 3C ) . Next , we extended our in-vitro GST-pulldown experiment to determine the specific residues within the N-terminal domain of EBNA3C , important for the IRF4 and IRF8 interactions . We further found with in-vitro precipitation assays using a series of N-terminal truncated mutants of EBNA3C that the N-terminal amino acid residues 130–190 bound to IRF4 and IRF8 ( Supplementary Fig . S3A ) , however , amino acid 130–159 residues showed the highest binding affinity ( Fig . 3D , E ) . To determine the importance of specific amino acid residues mediating these interactions , we observed some functionally conserved residues from an alignment result of EBNA3C 130–159 with EBNA3A and EBNA3B ( Supplementary Fig . S3B ) . To address the critical role of individual amino acid residues , single or double point mutation were introduced in conserved EBNA3C 130–159 residues as indicated by boxes in Fig . 3G . Interestingly , Phenylalanine 144 ( F144A ) dramatically reduced the interaction with IRF4 and IRF8 . In addition , a double mutation of arginine-149 and arginine-151 also significantly reduced IRF4 and IRF8 binding activity ( Fig . 3F ) . To define the specific domain of IRF4 and IRF8 responsible for interacting with EBNA3C , we performed co-immunoprecipitation experiments using Flag-tagged full length ( resides 1–451 ) and different truncated mutants of IRF4 ( residues 1–135 , 136–245 , 246–451 ) or IRF8 ( residues 1–426 , 1–135 , 136–278 , 279–426 ) with Myc-tagged full length EBNA3C . The results indicated that the C-terminal domain of IRF4 and IRF8 bound to EBNA3C ( Fig . 4A , B , C ) . Previously , it was reported that the amino terminal domain of EBNA3C associates with Spi-1 and Spi-B proteins [52] . It is also known that IRF4 directly associates with Spi-1 and Spi-B [53] , [54] . So , it was possible that IRF4 interacts with EBNA3C through a Spi-1 or Spi-B motif . To further examine if IRF4 interacts with EBNA3C through its Spi-1/B motif , we first aligned the sequence of Spi-1 , Spi-B and IRF4 proteins . Alignment data analysis showed that IRF4 contains a Spi-1/B motif based on hydrophobic homology of amino acid sequences and that the consensus Spi-1/B motif lies within residues 250–295 ( Fig . 4D ) . To further confirm the association of IRF4 and EBNA3C through Spi-1/B motif , co-immunoprecipitation assays were performed with Myc-tagged full length EBNA3C , full length Flag-IRF4 and Flag-Spi-1/B deletion mutant of IRF4 . The result clearly demonstrated that the interaction with EBNA3C and IRF4 is significantly less with the Spi-1/B motif deletion mutant suggesting that this motif is important for its interaction ( Fig . 4E ) . The above studies showed a complex with EBNA3C , IRF4 and IRF8 . Furthermore , previous experiments suggested that there was a dramatic upregulation of IRF4 in the presence of EBNA3C . Therefore , we examined the sub-cellular localization of IRF4 and EBNA3C . Immunofluorescence analysis was performed in transiently transfected as well as EBV transformed cells . We ectopically expressed Flag-tagged IRF4 with the GFP-tagged EBNA3C in HEK-293 cells . The results clearly demonstrated that IRF4 co-localized with EBNA3C in nuclear compartments with the exclusion of the nucleoli as indicated by yellow fluorescence signals ( Fig . 5A ) . To further validate our finding and to also support the association between IRF4 and EBNA3C under relevant physiological conditions , we used BJAB10 stably expressing EBNA3C and LCL1 cells . Here , BJAB cells represent EBV negative cells which do not express EBNA3C . Using specific antibodies against EBNA3C and IRF4 , our immunofluorescence studies clearly indicated that EBNA3C signals were predominantly co-localized with IRF4 to similar nuclear compartments . ( Fig . 5B ) . A similar result was obtained with IRF8 although the signals were much weaker and is likely due to the reduced levels of IRF8 ( data not shown ) . Interestingly , some IRF4 signals were also diffused in the nucleus although a large portion of those clearly co-localized with the punctate signals of EBNA3C ( Fig . 5A and 5B ) . Additionally , the co-localization study was extended with different truncated regions of EBNA3C and the result shown here , demonstrated that IRF4 co-localized with the N-terminal domain of EBNA3C ( residues 1–365 ) whereas , the middle domain ( residues 366–620 ) and C-terminal domain ( residues 621–992 ) showed negligible co-localization pattern ( Fig . 5C ) . From the studies above it was clear that EBNA3C can play a major role or is a major contributor to IRF4 protein levels . To determine whether EBNA3C can modulate the stabilization of IRF4 , we co-transfected HEK-293 cells with Flag-tagged IRF4 , and either the control vector or the Myc-tagged EBNA3C and then treated the transfected cells with the proteasome inhibitor MG132 . Interestingly , the results indicated a significant accumulation of IRF4 protein in comparison with mock treated or control vector transfected cells ( Fig . 6A ) . Next , HEK-293 cells were transfected with control vector , Flag-IRF4 , full length , N-terminal ( residues 1–365 ) and N-terminal deleted mutant ( residues 366–992 ) of Myc-tagged EBNA3C expression constructs . Thirty-six hours post-transfected cells were treated with the protein synthesis inhibitor , cyclohexamide and monitored for protein levels at 0 , 6 and 12 hours by Western blot analysis . As expected , the results demonstrated that the stability of IRF4 protein was significantly increased in the presence of EBNA3C ( Fig . 6B ) . However , in the absence of EBNA3C or using the specific N-terminal deleted EBNA3C , the IRF4 protein levels were gradually degraded within 6 to 12 hours of cyclohexamide treatment ( Fig . 6B ) . This result therefore provided evidence as to the stability of both EBNA3C and IRF4 proteins when the protein synthesis inhibitor cyclohexamide was used in the assay and also demonstrated a critical role for N-terminal domain of EBNA3C in enhancing IRF4 stability ( Fig . 6B ) . We also performed a similar protein stability assay for BJAB , BJAB10 and LCL1 cells treated with cyclohexamide . Our results reconfirmed that in the EBNA3C expressing BJAB10 cell line , as well as in LCLs expressing other latent proteins the IRF4 levels were greatly enhanced ( Fig . 6C ) . Therefore , EBNA3C contributes to stabilization of IRF4 in EBV infected and transformed cells . Our previous studies showed that EBNA3C targets the SCFSkp2 E3 ubiquitin ( Ub ) ligase complex thereby destabilizing various key cell-cycle proteins including retinoblastoma ( Rb ) and p27 KIP [55] . Recent experimental evidence also suggested that EBNA3C can enhance the intrinsic ubiquitin ligase activity of Mdm2 towards P53 , which in turn aided degradation of p53 by ubiquitination [56] . Thus , by modulating cellular ubiquitination activities , EBNA3C can provide a favourable environment for malignant transformation and proliferation of EBV-infected cells . The above-mentioned results demonstrated stabilization of IRF4 particularly in the presence of EBNA3C . We further assessed the possible contribution of EBNA3C to modulation of the poly-ubiquitination status of IRF4 and IRF8 . To further corroborate our hypothesis , we performed ubiquitination assays using HEK-293 cells . Here , we transiently co-transfected different expression constructs for HA-Ub , Flag-IRF4 and Myc-EBNA3C . Furthermore , immunoprecipitation followed by Western blot analysis clearly showed a reduction in the level of IRF4 poly-ubiquitination in EBNA3C expressing cells ( Fig . 7A ) . Next , we extended this experiment using the catalytic domain mutant of EBNA3C Myc-C143N and N-terminal deleted mutant Myc-EBNA3C ( residues 366–992 ) . The results showed enhanced ubiquitination of IRF4 when transfected with these expressions constructs ( Fig . 7B , C ) . Additionally , we performed ubiquitination assays with different truncated mutants of EBNA3C in HEK-293 cells . The results also confirmed a critical role for the N-terminal domain of EBNA3C in regulation of IRF4 poly-ubiquitination ( Fig . 7D ) . Additionally , we performed immuno-precipitation assays using specific antibodies against IRF4 in EBV negative BJAB , and BJAB7 , BJAB10 cells , as well as EBV transformed LCL1 , LCL2 cells . The complexes showed high molecular weight species of IRF4 ( Fig . 7D ) . These high molecular weight species migrated at a slower rate in EBV-negative BJAB cells . However , in BJAB7 and BJAB10 or in LCL1 and LCL2 there were significantly less compared to the EBV negative BJAB cells . Western blot analysis using Ubiquitin-specific antibody showed a similar pattern ( Fig . 7E ) . We also evaluated IRF4 ubiquitination using a sh-control vector and a Sh-E3C stably transfected LCL1 cell lines . The resulting poly-ubiquitination of IRF4 was shown to be significantly higher in EBNA3C knockdown . However , the poly-ubiquitinated status of IRF8 was found to be much reduced in the same cell lines ( Fig . 7F and 7G ) . These results strongly indicate that EBNA3C differentially modulates ubiquitination of IRF4 and IRF8 , and so their stability in EBV transformed cells . To explore the potential mechanism of EBNA3C-mediated IRF4 induction and degradation of IRF8 , we transiently transfected EBV negative DG75 cell line with control vector , with or without EBNA3C tagged with the Myc epitope ( Myc-EBNA3C ) , and an increasing dose of IRF4 tagged with the Flag epitope ( Flag-IRF4 ) . We monitored the expression of IRF8 protein by Western Blot analysis . Surprisingly , we observed no significant change of IRF8 protein levels in EBNA3C untransfected control , but a significant down-regulation of IRF8 was seen in the presence of EBNA3C ( Fig . 8A ) . We then performed Western blot analysis by transfecting DG75 cells with or without Myc-EBNA3C and an increasing dose of Flag-IRF8 to monitor IRF4 protein levels . Our results demonstrated that even with the gradual increase of IRF8 expression , the IRF4 protein expression level was relatively unchanged as determined by Western blot in the presence or absence of EBNA3C ( Fig . 8B ) . To investigate whether IRF4 is playing a vital role in IRF8 degradation in the presence of EBNA3C , we performed poly-ubiquitination assays by co-transfecting Flag-IRF4 , IRF8 , Myc-tagged EBNA3C and the Myc-tagged catalytic domain mutant of EBNA3C in HEK-293 cells . Interestingly , in the presence of wild-type EBNA3C we found higher ubiquitination of IRF8 with IRF4 as compared to EBNA3C-C143N ( Fig . 8C ) . These results further corroborated the above data showing the negative regulation of IRF8 by IRF4 in the presence of EBNA3C . To explore the effect of the modulation of IRF4 on IRF8 protein levels in the context of EBV-mediated B-cell transformation , we stably transduced LCL1 cells with lentivirus which express a short hairpin RNA to knock-down IRF4 ( Sh-IRF4 ) . In parallel , we used stable Sh-Ctrl LCL1 cells as a control cell line . We also verified that the cells were stably transduced by checking the GFP expression and the protein expression level of IRF4 knock-down cells by Western blot analysis ( Supplementary Fig . S4A , B ) . Previously , we observed a decrease in poly-ubiquitination of IRF8 in EBNA3C knockdown LCL1 cells ( Fig . 7F ) , whereas there was enhanced ubiquitination of IRF4 as seen by an increased pattern of the slower migratory bands . Here , we further investigated the polyubiquitination status of IRF8 in stable IRF4 knockdown LCL1 cells compared with Sh-Ctrl LCL1 cells . Surprisingly , we found a reduction in the IRF8 poly-ubiquitination level and also a substantial upregulation of IRF8 upon IRF4 knockdown ( Fig . 8D ) . This strongly suggests that IRF4 is a major player in EBNA3C-mediated IRF8 destabilization and degradation by the Ubiquitin-proteasome system . Previous studies suggested that the oncogenic transcription factor c-Myc has a crucial role in cell growth , metabolism and proliferation [57] , Cyclin dependent kinase 6 ( CDK6 ) overexpression was implicated in the pathogenesis of B-cell malignancies [58] , and also aberrant expression of the cell cycle regulatory protein Cyclin B1 has been detected in different lymphomas and EBV-immortalized cells [59] , [60] . Earlier studies also demonstrated that these molecules are direct targets of IRF4 [44] , [61] . To determine , if EBNA3C has some regulatory effect on the IRF4 downstream signaling molecules , we checked the status of the protein levels of these molecules in IRF4 and EBNA3C stable knockdown LCL1 cells . The results showed down regulation of those proteins upon IRF4 or EBNA3C knockdown ( Fig . 8E ) . To validate this data , the IRF4 stable knockdown LCL1 cells were transiently transfected with either control vector or Flag-tagged IRF4 plasmid vectors . 48 hrs after transfections the cells were harvested and Western blot analysis was performed ( Fig . 8E ) . The results clearly indicated that rescue of IRF4 expression in IRF4 stable knockdown LCL1 cells had similar results compared to wild-type for expression levels of c-Myc , Cyclin-dependent kinase 6 and Cyclin B1 which were substantially increased compared to the control vector cells . Dysregulation of these downstream signaling molecules may play a major role in a range of cellular process , such as aberrant cell proliferation , apoptosis and cell-cycle regulation . In order to examine the effect of EBNA3C on IRF4 mediated cell proliferation , HEK-293 cells were transfected with control vector , Myc-tagged EBNA3C , Flag-tagged IRF4 expression plasmids , Myc-tagged EBNA3C and Flag-tagged IRF4 , Myc-tagged N-terminal domain deleted mutant EBNA3C ( residues 366–992 ) and Flag-IRF4 as designated in the figure ( Fig . 9A–C ) . In addition , cells were also transfected with GFP expression vector . Transfected cells were selected with G418 for 2 weeks for colony formation assays . Here , we observed a significant increase in colony numbers when EBNA3C and IRF4 proteins were co-transfected in comparison to the set transfected with only IRF4 . Interestingly , co-expression with the N-terminal domain deleted mutant of EBNA3C and IRF4 showed a significant reduction in colony numbers which also confirmed the importance of N-terminal EBNA3C domain in IRF4 mediated cellular proliferation ( Fig . 9A and 9C ) . We further extended these studies by performing cell proliferation assays as determined by cell counting for 6 days ( Fig . 9B ) . By using Trypan Blue dye staining , dead cells were excluded . To determine the expression levels of the transfected constructs , Western blot analysis was performed with G418 selected stable cells ( Fig . 9D ) . Recently , it was reported that inhibition of IRF4 is deleterious to myeloma cell lines suggesting that IRF4 silencing can be a potentially new target to be exploited therapeutically [62] . To corroborate these studies that IRF4 has oncogenic potential and can prevent cellular apoptosis , we performed Flow-cytometric analysis of etoposide treated Sh-Ctrl , Sh-IRF4 LCL1 cells to examine the cell-cycle distribution profiles . Our result showed an increased percentage of sub-G0/G1 phase cells in IRF4 knockdown cells with etoposide treatments ( Fig . 9E ) . Moreover , the results showed that IRF4 knockdown LCLs were more prone to chemo-therapeutic drug induced cell death and clearly demonstrated that the level of apoptosis was much higher for Sh-IRF4 LCL1 cells compared to Sh-Ctrl LCL1 cells ( Fig . 9G ) . To assess the cellular proliferation in context of IRF4 knock-down , a proliferation assay was performed at different time points by treating cells with etoposide . Interestingly , the result indicated that the proliferation rate of IRF4 knock-down LCL1 cells was lower compared to the Sh-Ctrl LCL1 ( Fig . 9F ) . We also performed cell proliferation assays with two different EBV negative cell lines DG75 and BJAB , EBV transformed cell lines LCL1 and LCL2 , and EBNA3C expressing BJAB7 and BJAB10 cells , along with Sh-Ctrl and Sh-E3C transfected stable LCL1 cell lines . These results clearly suggested that EBV positive cells specifically expressing EBNA3C were not susceptible to etoposide induced cell death . However , in EBNA3C knockdown cells , significant reduction of cell proliferation was observed ( Supplementary Fig . S5 ) . To further confirm whether IRF4 silencing had some effect on etoposide induced apoptosis of EBV positive lymphoblastoid cells , Western blot analysis was performed to examine the level of Poly ( ADP-ribose ) polymerase 1 ( PARP-1 ) cleavage . Sh-Ctrl and Sh-IRF4 LCL1 cells were treated with different concentrations of etoposide and were examined to detect the 89 kDa active form of PARP-1 by Western blot analysis . The results clearly demonstrated that EBV transformed cells with IRF4 knock-down showed an increased sensitivity to etoposide induced apoptosis ( Fig . 9H ) . Additionally , we performed an assay to detect apoptotic cells with ethidium bromide and acridine orange staining as well as DNA fragmentation assay . The results also indicated that IRF4 knockdown enhanced the level of apoptosis in EBV transformed LCL1 cells ( Supplementary Fig . S6 and S7 ) . To determine the crucial role of EBNA3C and IRF4 on the growth inhibitory property of IRF8 , we transfected Ctrl-vector , Myc-EBNA3C , Flag-IRF8 , Flag-IRF4 and GFP expression plasmids into HEK-293 cells . Transfected cells were selected by G418 for 2 weeks and cell proliferation rate was determined at different time points . The results demonstrated that the growth inhibitory property of IRF8 was reduced by IRF4 with an additive effect when EBNA3C was included ( Fig . 10A ) . Western blot analysis was performed with those stable transfected cells to monitor the expression levels of both proteins . The results indicated that IRF8 protein expression levels were reduced in the presence of EBNA3C and IRF4 ( Fig . 10B ) . GAPDH Western blot was shown as internal loading control and GFP protein blot were used to demonstrate equal amount of protein lysates from stable transfected cells . We further performed colony formation assays with the same transfected stable cells above . Interestingly , we saw a significant increase in colony numbers when EBNA3C and IRF4 proteins were co-expressed with IRF8 protein in comparison to the set transfected with only IRF8 ( Fig . 10C and 10D ) . These results support our previous results above suggesting that EBNA3C can suppress the growth inhibitory effect of IRF8 in association with IRF4 . To further explore the significance of IRF4 expression in EBNA3C-mediated inhibition of IRF8 function , we generated IRF4 knockdown stable Ramos cell lines , which is EBV negative . Lentivirus-mediated transduction was further confirmed by GFP expression ( Fig . 10F ) , and the expression level of knockdown IRF4 was also verified by Western blot analysis . The results demonstrated that the level of IRF4 was knocked down by sh-RNA in comparison with LCL1 or sh-control vector transduced LCL1 cells ( Fig . 10G ) . We then transfected control-vector , Flag-IRF8 , Myc-EBNA3C expression vectors in Sh-Ctrl and Sh-IRF4 Ramos cells and subjected them to cell proliferation analysis . Surprisingly , we found that heterologous expression of IRF8 significantly reduced the proliferation of Sh-IRF4 Ramos cells compared with the Sh-Ctrl Ramos cells and that the rate of proliferation was partially restored by EBNA3C ( Fig . 10 , compare 10I and 10J ) . Overall , the data demonstrated a critical role for EBNA3C in enhancing the oncogenic effect of IRF4 for promoting B-cell proliferation . To further corroborate these results we extended our study using FACS analysis . The results clearly indicated that IRF4 knockdown Ramos cells showed a higher level of apoptosis compared to the control knockdown cells . Moreover , we observed a substantial level of apoptosis with increased expression of IRF8 in IRF4 knockdown Ramos cells . Interestingly , co-expression with IRF8 and EBNA3C reduced the level of apoptosis ( Fig . 10E and 10H ) . Therefore , EBNA3C co-operates with IRF4 a major regulator of EBV positive cells through downregulation of IRF8 .
EBNA3C , one of the EBV essential latent proteins , regulates transcription of several viral and cellular genes . Previous studies showed that EBNA3C also co-operates with EBNA2 to activate the viral LMP1 promoter via interaction with cellular transcription factors , including Spi-1/Spi-B [52] . Additionally , EBNA3C associates with the metastasis suppressor protein Nm23-H1 to regulate the transcription of cellular genes which are critically involved in cell migration and invasion [63] . Recent studies also demonstrated that EBNA3C can interact and stabilize cellular oncoproteins , including c-Myc [11] , and the major cell cycle regulatory protein Cyclin D1 [64] to drive B-cell transformation . IRF4 is an important member of the IRF family of transcription factors , which plays a key role in activation of lymphocytes and generation of antibody producing plasma cells during immune response [65] . Immunohistochemical analysis showed that IRF4 expression was observed in a variety of B-cell lymphomas including Diffuse large B-cell lymphomas ( DLBCLs ) , marginal zone lymphomas ( MZLs ) and B-cell chronic lymphocytic leukemias ( B-CLL ) or small lymphocytic lymphomas ( SLL ) strongly suggesting its involvement with various myeloid and lymphoid malignancies [66] . Notably , IRF4 alone is not sufficient to drive the oncogenic process in B cells , but requires the help of additional factors for the induction of its oncogenic activity [67] . Moreover , the molecular interplay between viral factors and the cellular microenvironment may further determine the specific contributions of IRF4 for driving lymphomagenesis . Among the IRF family members , IRF4 is closely related to IRF8 by sequence homology . Interestingly both IRF4 and IRF8 weakly bind to ISRE in the presence of other DNA binding proteins [53] . In particular , IRF4 forms a complex with IRF8 to regulate the expressions of different cellular genes [67] . Earlier reports have suggested that cellular IRF4 is a key mediator of EBV-induced B cell transformation [43] . However , a lack of expression of the ICSBP/IRF8 gene may add to the progression of lympho-proliferative diseases , as the loss of expression was linked to increased resistance to apoptosis induced by DNA damage or CD95/FAS [68] . Some studies reported that the functions of IRF4 are dependent on the interaction with other cellular proteins [69] . This motivated us to explore the precise interplay between EBNA3C , IRF4 and IRF8 so as to decipher the underlying molecular mechanism . Our current study showed a direct association between IRF4 , IRF8 and EBNA3C . Here , we explored the molecular association between EBNA3C , IRF4 and IRF8 complexes to identify different domains of EBNA3C which regulates the activity of IRF4 and IRF8 . Noteworthy , our present investigation demonstrated that EBNA3C binds with IRF4 and IRF8 via the same residues 130–190 within the N-terminal domain . Additionally , we performed different functional assays with an N-terminal deleted mutant of EBNA3C involving IRF4 and IRF8 which ultimately demonstrated a critical regulatory role for this N-terminal domain in cell proliferation and protein stability . Recent genetic studies also suggested that deletion of this specific domain could not support the proliferation of EBV-transformed cells [70] . Our data also supports and re-confirmed this important finding . Interestingly , we identified Spi-1/B like motif in IRF4 and examined the binding affinity of EBNA3C with IRF4 using wild type and Spi-1/B motif deleted mutant . We observed minimal or no binding with Spi-1/B deleted IRF4 and EBNA3C . Our data strongly suggest that this specific Spi-1/B motif permits IRF4 greater flexibility for interacting with EBNA3C . Furthermore , additional studies may require in-depth understanding of the functional significance of Spi-1/B motif . We established that EBNA3C co-localizes with IRF4 and IRF8 proteins in the nuclear compartments from our immunofluorescence assay . These results provide new information which shows that EBNA3C and IRF4 interaction can enhance the stabilization and nuclear accumulation of IRF4 creating a favorable environment important for transformation of EBV-infected cells . Our study further showed that EBV infection of peripheral blood mononuclear cells as well as EBV positive immortalized B-cells increased the stability of IRF4 but not IRF8 . However , the mRNA expression level was unchanged , strongly demonstrating that EBNA3C-mediated regulation of IRF4 and IRF8 expression was based primarily on post-translational modification . It was reported that LMP1 was one of the viral factors involved in increased expression of IRF4 in EBV transformed cells [43] . However , the precise molecular mechanism , by which IRF4 contributes to EBV-mediated lymphomagenesis has not yet been delineated . Our study clearly demonstrated a direct role of EBNA3C in regulation of IRF4 and IRF8 expressions independent of other EBNAs or LMP1 . Studies in the past have suggested that IRF8 is a target for Ubiquitin-dependent degradation but provided no evidence [71] . Interestingly , ubiquitination assays confirmed that poly-ubiquitination of IRF4 was inhibited by EBNA3C . These findings also correlated with higher expression levels and accumulation of IRF4 in EBV transformed and EBNA3C expressing cells . Interestingly , EBNA3C enhanced the degradation of IRF8 through the Ub-proteasome pathway . Our study now provides validation for a major role of EBNA3C in contributing to IRF4-mediated IRF8 down regulation in EBV transformed B-lymphocytes . Our future study will address the underlying mechanism of IRF4 mediated enhanced poly-ubiquitination of IRF8 , involving EBNA3C which will provide clues to further our understanding of the contribution of transcription factors in EBV-mediated oncogenesis . Our knockdown assays confirmed that inhibition of IRF8 was critically linked to EBNA3C-mediated up-regulation of IRF4 thus contributing to its oncogenic activity and overall EBV-mediated B-cell immortalization . This molecular mechanism is important and opens new therapeutic avenues by which IRF4 can be targeted as a potential candidate for neutralizing EBV-mediated B-cell malignancies . Recent reports suggested that siRNA mediated IRF4 knockdown inhibits Hodgkin Lymphoma cell proliferation and survival [72] . Additionally , IRF4 also possesses anti-apoptotic activities and the regulation of IRF8 by IRF4 may contribute to the biological functions of IRF4 in the context of EBV transformation . In our current study , IRF4 knockdown sufficiently inhibited the proliferation of EBV transformed cells and also augmented the level of etoposide induced apoptosis . Moreover , inhibition of cellular proliferation was directly associated with increased IRF8 expression in IRF4 knockdown LCL1 . Importantly , some downstream target molecules of IRF4 such as , c-Myc , Cyclin B1 , Cyclin-dependent kinase 6 which are directly associated with cell proliferation , apoptosis and cell-cycle regulation , were found downregulated upon IRF4 knockdown . Interestingly , re-introduction of IRF4 in stable IRF4 knockdown LCL1 cells restored the expression of those downstream signaling molecules . These findings thus infer that EBNA3C-mediated upregulation of IRF4 leads to activation of its downstream signaling cascades which facilitates a favorable condition for B-cell transformation . Few earlier reports provided definitive evidence for the role of IRF8 in inducing apoptosis [73] . Specifically , in humans , IRF8 expression was high in normal hematopoietic cells but impaired in myeloid leukemia [41] . Moreover , IRF8 expression was extremely low or undetectable in 79% of chronic myelogeneous leukemia ( CML ) patients and 66% of acute myeloid leukemia ( AML ) patients [41] . Mouse model systems , with a null mutation in IRF8 a myeloproliferative syndrome was observed with marked expansion of undifferentiated myeloid cells that can progress to significant and fatal blast crisis of human CML [39] . On the basis of these previous reports we hypothesized that IRF8 may function as a tumor suppressor in EBV associated B-cell lymphomas . Our studies using EBV negative stable IRF4 knockdown Ramos cells showed a significant level of apoptosis , and a reduction of cell proliferation upon IRF8 expression . Expectedly , cell proliferation was restored and the apoptotic level reduced with transfection of EBNA3C . These findings also correlated with our colony formation assays and cell proliferation assays where we showed that EBNA3C suppressed the growth inhibitory effect of IRF8 in association with IRF4 . Furthermore , knockdown of oncogenic IRF4 induced the tumor suppressive activities of IRF8 . This cemented our findings that EBNA3C and IRF4 do play a critical role in EBV-infected B-cell proliferation by downmodulating IRF8 . In our study , we now focus on the intermolecular interactions and regulatory roles of EBNA3C associated with IRFs . This study provides new evidence which shows a complex of EBNA3C with IRF4 and IRF8 in EBV transformed cells . We have identified the specific interaction domain of EBNA3C for IRF4 and IRF8 binding , and also showed that the specific interaction of EBNA3C and IRF4 ultimately led to enhanced stabilization of IRF4 . Additionally , this new role for EBNA3C in stabilizing IRF4 and at the same time enhancing ubiquitin-mediated IRF8 degradation is a novel finding which adds to the overall depth of our understanding of the range of molecular activities which contributes to EBV mediated lymphomagenesis ( Fig . 11 ) . Furthermore , siRNA mediated knockdown of IRF4 results in apoptosis in EBV-transformed cells and inhibited proteasome-mediated degradation of IRF8 . These knockdown experiments of EBNA3C and IRF4 further strengthened their critical roles in EBV-mediated B-cell proliferation by suppressing the apoptotic process . The downstream molecular targets of IRF4 , which include , c-Myc , Cyclin B1 , Cyclin-dependent kinase 6 are directly linked to different cellular functions and the deregulated expression of these molecules are implicated in EBV-mediated pathogenesis . Our findings thus provide another insight into the role of EBNA3C expressed in EBV-infected B-cells and its association with critical IRF family members which contributes to viral induced cell transformation . This study may provide novel therapeutic targets to treat and prevent EBV- associated lymphomas .
Plasmids expressing full length EBNA3C or its truncations such as 1–365 , 366–620 , 621–992 , and different N-terminal truncated or deleted mutants with C-terminal Flag or Myc-tagged , catalytic domain mutant Myc-tagged EBNA3C , GST-EBNA3C with single or double point mutations and EBNA3C tagged with GFP have been mentioned previously [11] , [55] , [56] , [74] . Flag-tagged human IRF4 construct was generated by using Invitrogen cDNA clone pOTB7-IRF4 . PCR amplified insert was digested with EcoRI/NotI and ligated into pA3F and pA3M vectors . Flag or Myc-tagged constructs expressing different truncations of IRF4 and IRF8 domains , Spi-1/B motif deleted Flag-tagged IRF4 were generated by PCR mutagenesis . Retroviral pMSCV-IRF8-IRES-EGFP plasmid was kindly provided by Ben-Zion Levi ( Technion-Israel Institute of Technology ) . This construct was used to generate human pA3F-IRF8 by cloning the PCR amplified insert into Myc and Flag-tagged vectors . pGEX-IRF4 and IRF8 constructs were cloned by using pA3F-IRF4 and IRF8 constructs as templates for the PCR amplification . PCR amplified gene products were inserted in pGEX2TK vectors ( GE Healthcare Biosciences , Pittsburgh , PA ) . pCDNA3-HA-Ub construct was kindly provided by George Mosialos ( Alexander Fleming Biomedical Science research center , Vari , Greece ) pGIPZ ( Open Biosystems , Inc . Huntsvillle , AL ) was used as the sh-RNA vector . Plasmids used for lentiviral packaging were described previously [75] . Antibodies of IRF4 ( H-140 ) , IRF8 ( S-15 ) , Ub ( FL-76 ) , PARP-1 ( F-2 ) were purchased from Santa Cruz Biotechnology , Inc ( Santa Cruz , CA ) GAPDH antibody was purchased from US-Biological Corp . ( Swampscott , MA ) . Flag ( M2 ) -epitope , anti-mouse antibody was purchased from Sigma-Aldrich Corp . ( ST . LOUIS , MO ) . Other antibodies to mouse anti-Myc ( 9E10 ) , anti-Hemaggutinin ( 12CA5 ) , A10 were previously described [75] . HEK-293 ( human embryonic kidney cell line ) was kindly provided by Jon Aster ( Brigham and Woman's Hospital , Boston , MA , USA ) . Cells were grown in Dulbeccoo's modified Eagle's medium ( DMEM; Hyclone , Logan , UT ) supplemented with 5% fetal bovine serum ( FBS; Hyclone , Logan , UT ) , 25 U/ml penicillin 50 µg/mal streptomycin , 2 mM L-glutamine ( Hyclone , Logan , UT ) . MutuI and MutuIII cells were provided by Yan Yuan ( School of Dental Medicine , university of Pennsylvania , Philadelphia , PA ) . EBV negative BL cells BJAB , Ramos , DG75 , BL41 and B95 . 8 infected BL41 were kindly provided by Elliot Kieff ( Harvard medical School , Boston , MA ) . BJAB stably expressing EBNA3C ( BJAB7 , BJAB10 ) were previously described [76] . In vitro-transformed EBV positive lymphoblastoid cell lines ( LCL1 , LCL2 ) , EBV positive P3HR1 , Jijoye cells and other B-cells were maintained in RPMI 1640 media ( Hyclone , Logan , UT ) . The above mentioned cell lines were incubated at 37°C in humidified 5% Co2 environment . Adherent HEK-293 cells and B-cells were transfected by electroporation system with Bio-Rad Gene Pulser II electroporator using 0 . 4 cm gap cuvette and cells were electroporated at 210 V and 975 µF ( for HEK-293 ) or 220 V and 975 µF ( for DG75 ) . After transfection , cells were grown in 10 ml of complete media in 100 mm Petri dish . PBMC were obtained from University of Pennsylvania Immunology core donated by the healthy donors . As mentioned earlier [48] , the Core maintains an IRB approved protocol in which declaration of Helsinki protocols were followed and each donor gave written , informed consent . 10 million PBMC were mixed well with BAC-GFP EBV supernatant in 1 ml of RPMI 1640 media supplemented with 10% FBS . Cells were incubated for 4 hrs at 37°C . Cells were centrifuged and cell pellet was re-suspended with 2 ml of complete RPMI 1640 media . EBV GFP expression was observed by using fluorescence microscope . The cells were harvested after 0 , 2 , 4 , 7 , 15 days of post-infection . Cells were harvested and washed with 1X Phosphate Buffered Saline ( PBS ) . 0 . 5 ml radioimmunoprecipitation assay ( RIPA ) buffer ( 0 . 5% NP-40 , 10 mM Tris pH 7 . 5 , 2 mM EDTA , 150 mM NaCl supplemented with 1 mM phenylmethylsulphonyl fluoride ( PMSF ) , Aprotinin , pepstatin and leupeptin were used as 1 µg/ml for cell lysis . Lysates were then pre-cleared with normal mouse or rabbit serum by rotating with 30 µl of Protein-A and Protein-G ( 1∶1 mixture ) -conjugated Sepharose beads for 1 hr at 4°C . Approximately 5% of the protein lysate was saved as input . 1 µg of specific antibody was used to capture the specific protein of interest by overnight rotation at 4°C . Immuno–complexes were precipitated with 30 µl of Protein-A and Protein-G-conjugated Sepharose beads . The immune-precipitated samples were washed with RIPA buffer . Protein samples were boiled in laemmli [77] buffer and resolved by SDS-PAGE and transferred to nitrocellulose membrane ( 0 . 45 µm ) . The membranes were probed with appropriate antibodies and scanned by Odyssey imager ( LiCor Inc . , Lincoln , NE ) Quantitation and image analysis were performed by Odyssey infrared imaging System application software . Glutathione S-transferase ( GST ) , GST-IRF4 , GST-IRF8 constructs were transformed in Escherichia coli BL21 cells and single colonies were grown in 3 ml of Luria broth overnight culture supplemented with 100 µg/ml ampicillin . 1 ml of this overnight culture was used to inoculate 500 ml of culture . When OD600 of that culture reached approximately 0 . 6 , Isopropyl-β-D-thiogalactopyranoside ( IPTG ) induction was performed with 0 . 5 mm concentration for 12 h at 30°C . Bacterial pellet was washed with STE buffer ( 100 mM NaCl , 10 mM Tris , and 1 mM EDTA , pH 7 . 5 ) , and resuspended with 3 ml of NETN buffer ( 0 . 5% NP-40 , 100 mM NaCl , 20 mM Tris , 1 mM EDTA , pH 8 . 0 ) supplemented with protease inhibitors and incubated 15 min on ice . 150 µl of 1 M dithiothreitol ( DTT ) and 1 . 8 ml of 10% Sarkosyl were added in STE buffer and the suspension was sonicated . The post-sonicated samples were centrifuged at 12 , 000×g for 10 min at 4°C . The supernatant was transferred into a fresh tube . 3 ml of 10% Triton X-100 in STE buffer and 200 µl of GST beads were added to the samples were rotated at 4°C for overnight . Purified GST protein samples were washed with NETN buffer supplemented with protease inhibitors . Purified protein expression was checked by SDS-PAGE . For GST pull-down assay , BJAB , BJAB7 , BJAB10 , LCL1 , LCL2 cell lysates were incubated with GST fusion proteins and control GST protein . Protein samples were washed with Binding Buffer ( 1X PBS , 0 . 1% NP-40 , 0 . 5 mM DTT , 10% glycerol , protease inhibitors ) and resolved with 8% SDS-PAGE . Western blot was performed with A10 antibody . HEK-293 cells were plated on coverslips and different expression plasmids were by Lipofectamine 2000 transfection reagents ( Invitrogen , Carlsbad , CA ) . After 36 hrs of post-transfection , transfected cells were fixed with 3% paraformaldehyde ( PFA ) with 0 . 1% Triton X-100 for 20 mins at room temperature . Fixed cells were washed with 1X PBS and 1% Bovine serum albumin was used for blocking . Flag-tagged IRF4 were detected by anti-flag ( M2 ) antibody and GFP-tagged EBNA3C was detected by GFP-fluorescence . BJAB , BJAB7 , BJAB10 , LCL1 and LCL2 cells were semi-air-dried on slides and fixed as mentioned above . To check endogenous expressions of EBNA3C , and IRF4 , specific antibodies were used . Primary antibodies were diluted in blocking solution . Fixed cells were incubated with these primary antibodies for overnight at 4°C . Cells were washed with 1X PBS and incubated with secondary antibodies ( 1∶1000 ) for 1 hr at room temperature . Nuclear staining was performed with DAPI ( 4′ , 6′ , -diamidino-2-phenylindole; Pierce , Rockford , IL ) . Cells were washed in 1X PBS and mounted with antifade mounting medium . The slides were observed by Fluoview FV300 confocal microscope . Images were analyzed by FLUOVIEW software ( Olympus Inc . , Melville , NY ) . Cells were washed with ice-cold 1X PBS prior to RNA isolation . RNA extraction was performed by Trizol reagent ( Invitrogen , Inc . , Carlsbad , CA ) according to manufacturer's protocol . cDNA was prepared by using Superscript II reverse transcriptase kit ( Invitrogen , Inc . , Carlsbad , CA ) according to the instructions of the manufacturer . The primers for IRF4 , IRF8 , and EBNA3C were 5′-CAAGAGCAATGACTTTGAGG-3′ and 5′-TGGGACATTGGTACGGGAT-3′ [78] , 5′-CAGTGGCTGATCGAGCAGATTGA-3′ and 5′-ATTCACGCAGCCAGCAGTTGCCA-3′ [41] , 5′-AGAAGGGGAGCGTGTGTTGT-3′ and 5′-GGCTCGTTTTTGACGTCGGC-3′ respectively . Primers for GAPDH were 5′-TGCACCACCAACTGCTTAG-3′ and 5′-GATGCAGGGATGATGTTC-3′ [64] . Quantitative real-time PCR analysis was performed by using SYBER green Real-time master mix ( MJ Research Inc . , Waltham , MA ) . A melting curve analysis was performed to determine the specificity of the products and the values for the relative quantitation were calculated by threshold cycle method . Each sample was examined in triplicate . Transiently transfected HEK-293 cells and B-cells ( BJAB , BJAB7 , BJAB10 , LCL1 , and LCL2 ) were treated with protein synthesis inhibitor cyclohexamide ( CalBiochem , Gibbstown , NJ ) as 40 µg/ml concentration . Cells were harvested in different time points . Cells were lysed with RIPA buffer and protein samples were used for Western blot analysis . Protein band intensities were quantified by Odyssey 3 . 0 software . HEK-293 cells were transfected with control-vector , Flag-IRF4 , Flag-IRF8 , HA-Ub , Myc-EBNA3C expression plasmids by electroporation . After 36 hours post-transfection , cells were pre-treated with 20 µM concentration of MG132 ( Enzo Life Sciences International , Inc . , Plymouth Meeting , PA ) for additional 6 hours . Cell lysates were prepared and specific proteins were immunoprecipitated by using specific antibodies . Immunoprecipitated samples were resolved by SDS-PAGE . The status of ubiquitination was determined by HA-specific ( 12CA5 ) antibody . The sense strand of IRF4 shRNA and EBNA3C shRNA sequences are 5′- tcgagtgctgttgacagtgagcgaGCATGAACCTGGAGGGCGGtagtgaagccacagatgtaCCGCCCTCCAGGTTCATGC gtgcctactgcctcggaa-3′ [43] and 5′- tcgagtgctgttgacagtgagcgaCCATATACCGCAAGGAATAtagtgaagccacagatgtaTATTCCTTGCGGTATATGGgtgcctactgcctcggaa-3′ [64] respectively . Here , upper-case letters designate either IRF4 or EBNA3C target sequences and lower-case letters specify hairpin and sequences which are required for the directional cloning in pGIPZ vector . These single stranded oligonucleotides were individually cloned into the pGIPZ vector using XhoI and MluI restriction sites . Also , a control shRNA sequence; 5′-TCTCGCTTGGGCGAGAGTAAG-3′ ( Dharmacon Research , Chicago , IL ) was used to make Sh-Ctrl vector which lack the complementary sequences in the human genome . For production of lentivirus , 2×106 HEK 293T cells were grown in DMEM media with 10% FBS for 24 hrs prior to transfection . Total 20 µg of plasmid expression vector was used for the transfection of each set , including 1 . 5 µg of pCMV-VSV-G , 3 µg of pRSV-REV , 5 µg of pMDLg/Prre ( Addgene , Inc . , Cambridge , MA ) , and 10 . 5 µg of lentiviral vector plasmid . For precipitation , plasmids were added to a final volume of 438 µl of sterile H20 and 62 µl of 2 M CaCl2 , and solutions mixed well , then 500 µl of 2×HEPES-buffered saline added . Each transfection set was incubated at room temperature for 30 min . Before transfection , chloroquine was added to the 10 ml of media with a final concentration of 25 µM for 5 min . The media was replaced with DMEM supplemented with 10% FBS and 10 mM HEPES , and 10 mM sodium butyrate after 12 hrs of incubation . Again , the media was replaced after 10 hrs by DMEM supplemented with 10% FBS with 10 mM HEPES . To collect virus , the conditioned media was collected four times at 12 hrs interval . Conditioned medium was filtered through cellulose acetate filters ( 0 . 45 µm ) and stored in ice . The virus was concentrated by centrifuging the medium at 70 , 000×g for 2 . 5 hrs . The concentrated virus was re-suspended in RPMI medium and the virus used to infect 106 LCL1 cells with Polybrene as 20 µM/ml concentration . After 72 hrs of incubation , puromycin antibiotic was added as 2 µg/ml concentration for selection . To check the rate of selection , GFP-immunofluorescence was observed by Olympus 1X71 microscope with 560 nm excitation and 645 nm emission filters . Puromycin selected cells were grown up to 80% confluence and the expression levels of target proteins were checked by western blot analysis . HEK-293 cells were transfected with different expression vectors by electroporation . Transfected cells were grown in DMEM . Cells were selected with 1000 µg/ml G418 antibiotic ( Invitrogen , Inc . , Carlsbad , CA ) for 2-weeks . After selection , cell lysates were prepared by RIPA buffer and protein expression was checked by Western blot analysis . From each transfected set , 0 . 1×106 cells were plated and allowed them to grow for 6 days . In case of stable knockdown LCL1 cells , the same number of cells were plated and grown in RPMI media . Viable cells were counted in specific time points with Trypan Blue dye exclusion technique . All experiments were performed in triplicates . 5×106 Human kidney embryonic cells were transfected with Ctrl-vector , Flag-IRF8 , Flag-IRF4 , Myc-EBNA3C , GFP-control vector by electroporation and allowed to grow in DMEM with G418 as 1 mg/ml concentration . After 2-weeks of selection , GFP fluorescence of each plate was scanned by PhosphorImager ( Molecular Dynamics , Piscataway , NJ ) and the area of the colonies measured by using Image J software ( Adobe Inc . , San Jose , CA ) . Three independent experiments were performed to take average data . Control vector , IRF4 knockdown LCL1 cells were treated with or without etoposide ( MP Biomedicals , LLC ) overnight and cells were harvested and washed with 1xPBS three times . Flag-IRF8 co-transfected with Ctrl-vector and Myc-EBNA3C in IRF4 knockdown and sh-control vector transfected stable Ramos cell lines . These cells were washed with 1X PBS and fixed with 70% cold ethanol . Cells were kept at 4°C until used for FACS analysis . Fixed cells were stained with PBS containing 10 µg/ml of propidium iodide ( PI ) , 250 µg/ml of RNase A ( Sigma ) and 0 . 05% of Triton X-100 for 1 hr at room temperature in dark . Stained cells were analyzed on FACScalibur cytometer and Cellquest software ( Becton-Dickinson Inc . , San Jose , CA ) . Data here are represented as mean values with standard errors of means ( SEM ) . 2-tailed student's t-test was performed to evaluate the significance of differences in the mean values . A P-value of <0 . 05 was considered as statistically significant . Homo sapiens interferon regulatory factor 4 ( IRF4 ) -GenBank: BC015752 . 1 , Homo sapiens interferon regulatory factor 8 ( IRF8 ) -NCBI Reference Sequence: NM_002163 . 2 , Epstein-Barr virus ( EBV ) genome , strain B95-8- GenBank: V01555 . 2 , IRF4 protein ( Homo sapiens ) - GenBank: AAC50779 . 1 , IRF8 protein ( Homo sapiens ) -NCBI Reference Sequence: NP_002154 . 1 , EBNA3C protein- UniProtKB/Swiss-Prot: P03204 . 1 , Spi-1 protein- UniProtKB/Swiss-Prot: SPI1_HUMAN , P17947 , Spi-B protein- UniProtKB/Swiss-Prot: SPIB_HUMAN , Q01892 .
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Interferon regulatory factor ( IRF ) family members have different roles in context of pathogen response , signal transduction , cell proliferation and hematopoietic development . IRF4 and IRF8 are members of the IRF family and are critical mediators of B-cell development . Enhanced expression of IRF4 is often associated with multiple myeloma and adult T-cell lymphomas . Furthermore , IRF8 can function as a tumor suppressor in myeloid cancers . Epstein-Barr virus ( EBV ) , one of the first characterized human tumor viruses is associated with several lymphoid malignancies . One of the essential antigens , EBV encoded nuclear antigen 3C ( EBNA3C ) , plays a critical role in EBV-induced B-cell transformation . In our study , we now demonstrate that EBNA3C forms a molecular complex with IRF4 and IRF8 specifically through its N-terminal domain . We show that IRF4 is stabilized by EBNA3C , which resulted in downregulation of IRF8 through proteasome-mediated degradation and subsequent inhibition of its tumor suppressive activity . Moreover , si-RNA-mediated inhibition of IRF4 showed a substantial reduction in EBV transformed B-cell proliferation , and also enhanced their sensitivity to DNA-damage induced apoptosis . Therefore , our findings demonstrated that targeted disruption of EBNA3C-mediated differential regulation of IRF4 and IRF8 may have potential therapeutic value for treating EBV induced B-cell malignancies .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"viruses",
"and",
"cancer",
"virology",
"biology",
"microbiology"
] |
2013
|
The EBV Latent Antigen 3C Inhibits Apoptosis through Targeted Regulation of Interferon Regulatory Factors 4 and 8
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The downstream functions of the DNA binding tumor suppressor p53 vary depending on the cellular context , and persistent p53 activation has recently been implicated in tumor suppression and senescence . However , genome-wide information about p53-target gene regulation has been derived mostly from acute genotoxic conditions . Using ChIP-seq and expression data , we have found distinct p53 binding profiles between acutely activated ( through DNA damage ) and chronically activated ( in senescent or pro-apoptotic conditions ) p53 . Compared to the classical ‘acute’ p53 binding profile , ‘chronic’ p53 peaks were closely associated with CpG-islands . Furthermore , the chronic CpG-island binding of p53 conferred distinct expression patterns between senescent and pro-apoptotic conditions . Using the p53 targets seen in the chronic conditions together with external high-throughput datasets , we have built p53 networks that revealed extensive self-regulatory ‘p53 hubs’ where p53 and many p53 targets can physically interact with each other . Integrating these results with public clinical datasets identified the cancer-associated lipogenic enzyme , SCD , which we found to be directly repressed by p53 through the CpG-island promoter , providing a mechanistic link between p53 and the ‘lipogenic phenotype’ , a hallmark of cancer . Our data reveal distinct phenotype associations of chronic p53 targets that underlie specific gene regulatory mechanisms .
The TP53 ( p53 ) tumor suppressor , a stress-responsive transcription factor ( TF ) , is somatically mutated in more than 50% of human cancers , with a range between 10% and nearly 100% depending on the tumor type . Furthermore , germ line mutations of p53 , in both humans and mice , predispose individuals to malignant tumor development [1 , 2] . p53 plays critical roles in the induction of cell death and cell cycle arrest in response to stress , including DNA damage , oncogenic stress , and metabolic stress . Hence p53 is implicated in a wide range of cellular processes , such as cell cycle checkpoint , apoptosis , senescence and quiescence [3–5] . Despite increasing knowledge about p53 target genes , however , it is not entirely clear which aspects of p53 function are attributable to each of these p53-associated phenotypes and its tumor suppressor activity [6] . p53 is typically regulated at the protein level through post-translational modification . In normal conditions , p53 is under the regulation of a strong negative feedback loop , where MDM2 , a direct p53 target , serves as the E3 ubiquitin ligase , leading to the constant proteasomal degradation of p53 [7] . Thus p53 is highly unstable in non-stress conditions but upon stress induction , such as DNA damage , it can be rapidly stabilized through its dissociation from MDM2 . However , whether or not the prevailing model of acute p53 induction represents the major program of p53’s tumor suppressive functions is under debate [8] . For example , studying whole body irradiated p53 inducible knock-in mice , Christophorou et al . showed that a late restoration of p53 function , rather than the usual acute p53-mediated pathological response , led to a reduced lymphoma burden [9] . In addition , Brady et al . recently showed that p53 differentially regulates specific transcriptional programs of the acute DNA damage response ( DDR ) and its more chronic tumor suppression functions through its use of different transactivation domains . Their data indicate a close correlation between p53 activities in driving tumor suppression and senescence [10] . Notably , senescence has been shown to be largely dependent on a persistent , rather than an acute , DDR [11] . Thus these studies suggest that the downstream effects of acutely activated p53 and p53-mediated tumor suppression may well be separable processes . Several studies of p53 genomic binding profile have recently been published , revealing a number of new p53 targets , which include genes potentially associated with its tumor suppressor functions . An early study found p53 targets that potentially suppress metastasis [12] . A number of autophagy genes were recently identified as direct p53 targets and p53-induced autophagy was shown to be important for DNA damage-induced apoptosis and the anti-transformation activity of p53 [13] . In addition , in ES cells , p53 regulates self-renewal and pluripotency upon DNA damage [14] , and early-differentiation p53 targets include many developmental transcription factors [15] . Currently , however , efforts at genome-wide p53 mapping have mostly been focused on acutely or dynamically activated p53 . Thus comprehensive analyses of the persistent activities of p53 , which may be more relevant to its tumor suppressor function , are still missing . Here we show distinct regulatory mechanisms for p53-targets between acute and more persistent modes of p53 activation . In addition to the classical DDR , where p53 is acutely induced ( ‘acute’ p53 ) , we have determined profiles of genome-wide p53 binding and p53-responsive genes in two distinct cellular conditions , where p53 is persistently activated ( ‘chronic’ p53 ) in normal human diploid fibroblasts ( HDFs ) : oncogene-induced senescence ( OIS ) ; and transformed pro-apoptotic conditions . In contrast to acute p53 , chronic p53 was closely associated with CpG island ( CGI ) type promoters . Although the binding profiles of p53 in the OIS and pro-apoptotic conditions were similar , the p53-responsive genes were distinct , suggesting that downstream gene regulation by chronic p53 is highly context dependent . Interestingly , our integrative p53 networks and pathway modeling , combined with external high-throughput datasets , suggest that p53 can be functionally and/or physically associated with many of its own targets , thus forming extensive self-regulatory p53 hubs in the chronic conditions examined in this study . Finally , together with external clinical datasets , our data reinforce the evidence for the anti-lipogenic functions for p53 . Our study not only extends our knowledge of phenotype-associated gene regulation by p53 , but also provides unique and widely useful resources for the targets of persistently activated p53 .
To gain a comprehensive understanding of p53 biology , we established phenotypes that are associated with p53 either acutely activated by DNA damage or persistently activated by oncogenic stress in a single cell type ( IMR90 HDFs ) ( Fig . 1A ) . During the acute DNA damage response ( acDDR ) phase induced by etoposide treatment ( d1 ) , the cells were viable and had stopped proliferating but were not yet fully senescent , whereas most cells became senescent seven days after etoposide treatment ( Fig . 1B-1C ) . Of note , although acDDR cells showed a modest increase in senescence-associated ß-galactosidase activity ( Fig . 1B ) , it was not accompanied by up-regulation of other functional markers of senescence , such as HMGA proteins and p16 ( Fig . 1C ) . As expected , p53 was transiently stabilized in the acDDR phase with a parallel up-regulation of p53 targets , such as p21 and MDM2 , in total cell lysates ( Fig . 1C ) . Interestingly , in chromatin-enriched fractions , p53 levels were comparable between the acute ( d1 ) and senescence phases ( d7 ) . This is perhaps in part due to the enlarged cellular phenotype of senescent cells , the p53 level then being more diluted in total cell lysates of senescent cells . To establish the conditions for the sustained activation of p53 , we used the well-established models of oncogenic stress [16] . Ectopic oncogenic HRASG12V induces senescence ( RAS-induced senescence , RIS ) , a state of irreversible cell cycle arrest , where p53 plays a major role [16] . In contrast , E1A , the ‘immortalizing’ adenoviral oncoprotein , transforms HDFs when used in combination with oncogenic HRASG12V . At the same time , E1A stabilizes p53 and thereby sensitizes cells to apoptosis ( Figs . 1A , 1D , and S1A ) [17] . Thus E1A/RAS-expressing cells are highly proliferative , yet sensitive to apoptosis due to sustained p53 activation ( here we call this condition ‘pro-apoptotic’ , pApo ) . In both cases , a stable accumulation of p53 was readily detectable in chromatin fractions without additional stimuli ( Fig . 1D ) , and again the elevated levels of p53 , particularly in the RIS condition , were more clearly detected in chromatin fractions than in total lysates ( Fig . 1D ) . These data suggest that comparable amounts of p53 can be responsible for the distinct phenotypes . Having established highly distinct p53-associated phenotypes—acDDR , RIS , and pApo—we performed microarray analysis , with and without sh-p53 , for each condition using a miR30 RNAi design in the lentiviral backbone [18] . To reduce secondary effects of p53 knockdown , we introduced sh-p53 after each phenotype was established in the chronic conditions . The efficiency of p53 knockdown was confirmed in the chromatin fractions ( Fig . 1E ) . The set of differentially expressed ( DE ) genes upon sh-p53 introduction in each phenotype differed greatly between all conditions , with only a small number of well-characterized p53 targets in common ( Figs . 1F and S1B , and S1 Table ) . Regulation of three representative core p53 targets was validated using a different sh-p53 ( S1C Fig ) . Pathway analyses of DE gene sets confirmed distinct transcriptional signatures in each phenotype ( Figs . 1G and S1D ) , indicating that p53 can , directly or indirectly , regulate gene sets unique in terms of both their context and phenotype , i . e . in either the ‘acute’ or ‘chronic’ p53 condition , and the RIS or pApo condition . We next examined whether this phenotype-associated gene regulation was achieved through a specific p53 binding profile by using p53 ChIP-seq analyses of the acDDR , RIS and pApo conditions compared with normal-growing cells ( S2 Table ) . We used at least three replicates for each condition ( except the growing condition , with two replicates ) to define high-confidence ( HC ) peak sets ( see materials and methods ) . In contrast to the strong induction of p53 during acDDR , actual peak numbers were substantially lower than in the other conditions ( Fig . 2A ) . The number of HC peaks in the acDDR condition was comparable to peak sets described in earlier reports [12 , 13 , 19–21] . Notably , as in our acDDR condition , these studies were performed on cells treated for less than 24h . Our data suggest that the mode of p53 exposure , acute or chronic , affects the affinity of p53 binding and therefore the outcome . The genomic features of the HC p53 binding sites in the acDDR condition differed from those in RIS and pApo . The proportion of p53 peaks that mapped to transcription start site ( TSS ) proximal regions ( core promoter ) was substantially higher in the RIS and pApo conditions at 64% and 50% , respectively , compared with only 26% in the acDDR condition , where the majority of peaks ( >70% ) were in introns , exons or up-stream distal regions ( Fig . 2B ) . The preferential association of p53 with promoter regions in the chronic conditions is not due to varied numbers of p53 peaks between conditions , because the association was conserved when we selected the same numbers of peaks from each condition for the analysis ( S3 Table ) . Through visual inspection of our ChIP-seq data using a genome browser , we noticed that p53 peaks tended to be either sharp or broad , with acDDR peaks being substantially narrower than in the other conditions ( Fig . 2C ) . There are two major types of core promoter: ‘focused’ with a single or a few densely aggregated TSSs , and ‘dispersed’ with many TSSs . In vertebrates , these ‘focused’ and ‘dispersed’ promoters typically correspond to non-CGI-promoters containing core promoter elements ( e . g . TATA-boxes ) and CGI-type promoters , which are generally TATA-less , respectively [22] . We examined the co-occurrence of p53 peaks and CGIs in each condition . p53 peaks in the chronic ( RIS and pApo ) conditions overlapped substantially more with CGIs than in the acDDR condition . The acDDR-associated peaks in our and other published p53 datasets were mostly of the non-CGI type ( Fig . 2D ) . The higher frequency of CGI-type p53 peaks in chronic conditions is not simply due to their preferential distribution in the promoter regions ( Fig . 2B ) , since this tendency was retained when examining promoter regions only ( Fig . 2E ) . These data show the distinct genomic binding profiles of p53 between the acute and chronic conditions , revealing extensive usage of CGI promoters in the latter . Gene ontology ( GO ) enrichment of non-CGI p53 peaks mapped to genes showed that the functional groups involved in the typical p53-associated functions , such as cell cycle , DNA damage and apoptosis , were overrepresented particularly in the chronic conditions , whereas for the CGI p53 peaks , we observed the most significant enrichment for functional groups involved in RNA metabolism and processing ( S4 Table ) . These data suggest that the outcome of p53 binding in the chronic conditions is different from that of the acute condition , which has been a commonly used experimental system , and thus our data substantially extend not only the list of candidate p53-targets and but also their mode of regulation . We next examined whether these p53-bound regions contained the p53 consensus motif . Using position weight matrices , searching for known canonical p53 responsive elements ( p53REs ) , we identified their enrichment in both types of peaks ( Fig . 2F , see Materials and Methods ) . Reflecting the peak shapes , p53-binding motifs were dispersed throughout the CGI-type peaks , whereas p53REs were focused around the peak center of non-CGI-type peaks ( Fig . 2G ) . Such CGI-type p53 peaks have not been reported even in the promoter of CDKN1A ( p21 ) , the best-characterized p53 target ( Fig . 2H ) . The well-established view is that p21 has two major canonical p53REs at around-2 . 3 kb ( the distal p53RE ) and-1 . 4 kb ( the proximal p53RE ) . The distal p53RE is bound more strongly by p53 than the proximal site [23] . We consistently observed sharp p53 peaks at the distal site in all conditions ( #1 in Fig . 2H ) . In addition , the p21 locus contained prominent p53 enrichment at the major CGI , which encompasses the classic p21 TSS , in chronic conditions only . p53 binding to the CGI , which contained various potential p53REs ( Figs . 2 and S2A ) , coincided with enrichment for H3K4me3 ( a marker of CGI-promoters ) and a downstream spreading of H3K36me3 ( a marker for transcription elongation ) [24] ( Fig . 2H ) , suggesting that this CGI is a promoter for the classic p21 transcript variant 1 ( v1 ) . Both the classic v1 and the alternative transcripts—represented by variant 2 , whose TSSs are located in direct proximity to the distal p53RE ( #2 in Fig . 2H ) —were up-regulated in all conditions , therefore the relative contribution of the distal p53RE and the CGI promoter to p21 v1 is not yet clear ( Figs . 2 and S2B-S2C ) . Nevertheless these data reinforce the unexpected association between chronic p53 and CGI promoters . We next compared our p53-dependent expression data with our p53 binding data . In contrast to the expression profiles ( Fig . 1F ) , the overlap in the p53 binding profiles between conditions was substantially larger , and the similarity was even more striking for the peaks within the promoter regions ( S3A Fig ) . To better predict phenotype-associated p53 function , we developed the “R-based analysis of ChIP-seq And Differential Expression” ( Rcade ) package , integrating genome-wide binding profiles of TFs with their responsive gene expression profiles . Briefly , we coupled the expression analysis to a TSS-local read-based ChIP-seq analysis , thereby circumventing ‘peak-calling’ and thus reducing false-positives and bias issues inherent with peak-calling methods . However , because most of the acDDR peaks failed to fulfill the localization criteria specified ( S3B Fig ) , in our further analyses we only focused on the pApo and RIS chronic conditions , where Rcade identified 1487 and 563 genes , respectively , which included both established and many previously unknown , ‘putative’ p53 targets ( S3C Fig and S5 Table ) . GO analysis of the Rcade-derived genes showed that various biological processes were represented in both conditions , including typical p53-related functions ( cell cycle , DNA damage response , and apoptosis ) ; functions of membrane-bound organelles and metabolism; and gene expression and RNA metabolism/processing ( S3D Fig ) . The Rcade-derived genes include both previously known as well as many unknown/uncharacterized genes as direct targets of p53 . For example , ANKRA2 and HSPA4L , which are poorly characterized , were identified as putative direct p53-inducible targets in both RIS and pApo conditions . Significant down-regulation of ANKRA2 and HSPA4L upon p53 knockdown was confirmed by qPCR in at least two different conditions in IMR90 cells ( S3E Fig ) . Similar results were obtained using the second sh-p53 ( S3E Fig ) . Interestingly , tumor-specific , disruptive mutations of ANKRA2 were previously identified in oral squamous cell carcinoma [25] , and mutations in ANKRA2 are also reported in the Catalogue Of Somatic Mutations In Cancer ( COSMIC , http://www . sanger . ac . uk/genetics/CGP/cosmic/ ) . In addition , methylation of the CGI promoter of HSPA4L as well as the methylation-associated down-regulation of HSPA4L in acute lymphocytic leukemia ( ALL ) have been reported previously [26] , thus underlining the usefulness of our Rcade datasets . Using a PiggyBac transposon system [27] , we established a tetracycline-inducible p53 system in H1299 cells ( a p53-null lung cancer cell line ) and confirmed that ectopic wild type p53 could induce expression of ANKRA2 and HSPA4L ( S3F Fig ) . To gain a comprehensive understanding of the p53 regulome , we first generated integrative networks of the Rcade-derived p53-targets , taking advantage of numerous external high-throughput datasets . Since co-regulated genes are likely to be ‘connected’ , we measured connectivity within the Rcade-derived p53-targets , taking into account topological measures of local ( ‘Degree’ ) and global ( ‘Between-ness centrality’ ) connectivity ( see materials and methods ) . This largely unbiased network approach revealed that the ( putative ) p53-targets were highly inter-connected , providing evidence for the validity of our Rcade gene lists ( Fig . 3 , compare to the random gene set ) . p53 was identified as the most globally ( pApo ) and locally ( both conditions ) connected gene in the networks , indicating the importance of p53 to the integrity of entire networks . To gain insight into the functional relationship between putative p53 targets , we next constructed phenotype-specific , ‘knowledge-based’ pathway models of the p53 regulome ( see materials and methods ) ( S4 and S5 Figs , high resolution figures are available at http://australian-systemsbiology . org/tp53 ) . These revealed a highly complex network in the pro-apoptotic condition and provided the first detailed p53 regulome of senescence . p53 appeared to regulate multiple components within the same pathways or biochemical complexes , but often with distinct aspects depending on the cellular context . Thus many p53-related phenomena fragmented throughout the literature could be seen in a single biological context , and yet each context may involve distinct p53 functions . For example , Rcade genes associated with mitochondria in the pApo condition were largely distinct from those in the RIS condition and included , in addition to apoptotic genes , genes involved in mitochondrial metabolism and homeostasis ( oxidative phosphorylation , fatty acid and lipid metabolism , mitochondrial biogenesis ) . Consistent with a recent study , which showed an extensive transcriptional regulation of autophagy by p53 in response to acute DNA damage in mouse embryonic fibroblasts [13] , we also found that the autophagy program was regulated by p53 in the chronic conditions ( pApo in particular ) but through largely distinct genes compared to the previous report [13] ( S4 Fig ) , extending the role for p53 in autophagy regulation . One striking notion from our pathway modeling is that a subset of the p53 regulome formed a ‘p53 hub’: p53 has been reported to interact with , or be modified by , the components of this hub in diverse experimental conditions , thus suggesting that many of the direct targets of p53 in turn regulate p53 in the chronic conditions ( Figs . 4A , S4 , and S5 , and S6 Table ) . This is in accordance with the high local connectivity of p53 in the networks . Information specifically about protein-protein interactions between the p53 hub components highlighted that many of them can interact with each other ( Fig . 4B ) . The components within the self-regulatory network of p53 are best exemplified by MDM2 , the E3 ubiquitin ligase , which negatively regulates p53 stability , thereby conferring a strong negative feedback loop [7] . However , an MDM2-independent negative feedback loop has been shown in a senescence context [28] . Moreover , additional mechanisms for modulating the MDM2-p53 loop are suspected to exist in the cancer context [29 , 30] . Of note , consistent with the high connectivity of MDM2 in our p53 networks ( Fig . 3 ) , MDM2 itself formed a prominent ‘sub-hub’ within the p53 hub ( Fig . 4A ) , reinforcing the existence of multiple levels of mechanisms for regulating p53 and the p53-MDM2 loop in the chronic conditions . Together , our data suggest that intensive and multi-level fine-tuning of p53 function may be an important mode of phenotype regulation . Finally , to test the clinical relevance of our datasets for chronic p53 targets , we performed recursive partitioning analysis ( RPA ) of each Rcade component for survival in four publicly available cancer datasets ( Fig . 5A ) [31–33] . For example , the RPA identified an association between high levels of MDM2 , a bona fide oncogene , and poor prognosis in two datasets ( Fig . 5A ) . On the other hand , we observed a mixed association between prognosis and p21 ( CDKN1A ) levels , whose clinical relevance in human tumors is controversial , supporting the validity of this method [34] ( Figs . 5A and S6 ) . Interestingly , several autophagy genes were identified in the pApo condition , where high levels of these genes were mostly associated with better prognosis in multiple clinical datasets ( S6 Fig , left ) . Implications of autophagy in cancer are complex and thus careful interpretation is necessary , but these data support the recent study that showed the contribution of autophagy to p53-dependent tumor suppression [13] . Using this method we went on to validate clinically relevant p53 putative targets . We prioritized p53-repressive targets , since p53 mutations are common in cancers where p53-repressed genes are likely to be up-regulated , and if those gene products contribute to tumorigenesis , they may provide good candidates for therapeutic targets in p53-deficient cancers . Of the p53-repressive targets whose expression levels were significantly correlated with prognosis in at least two different datasets , we chose the lipogenic enzyme stearoyl-CoA desaturase ( SCD ) for further validation , for the following reasons ( Fig . 5A ) : ‘lipid metabolism’ was featured in our pathway modeling in both chronic conditions ( S4 and S5 Figs . ) ; the ‘lipogenic phenotype’ is a hallmark of cancer [35]; high SCD expression has been correlated with a transformation phenotype , tumor cell survival , and poor outcome in many cancers , and SCD has been implicated as potential targets for cancer therapy [36] . Although several lipogenic TFs , such as SREBFs and PPARs , have been implicated in the regulation of SCD expression , it is not clear how SCD is regulated under stress as well as in cancer [37] . SCD catalyzes the rate-limiting reaction in the biosynthesis of the major monounsaturated fatty acids ( oleate and palmitoleate ) , which are components of essential building blocks of rapidly proliferating cells [37] . Consistently , SCD was initially up-regulated in response to hyperactive RAS , and then it reduced to an almost undetectable level after the full establishment of senescence , where p16 , a marker of senescence , is highly up-regulated ( Fig . 6A ) . In E1A/RAS expressing transformed pApo cells , SCD levels were relatively high , supporting the role of SCD in rapidly proliferating transformed cells ( Fig . 6B ) . In both cases , however , when we introduced sh-p53 to RIS or pApo cells , SCD levels were up-regulated , suggesting that SCD is regulated by multiple mechanisms , whereby p53 counteracts the positive control of SCD by pro-tumorigenic signals . To lend further support to the finding that SCD is repressed by p53 in cancer , we analyzed a publicly available breast cancer dataset that contains gene expression and p53 sequencing data [38] . In contrast to p21 and MDM2 , SCD levels were significantly higher in tumors with p53 mutations than with wild-type p53 ( Fig . 6C ) . We also examined the relationship between p53 and Scd1 ( a mouse homologue of SCD ) in Kras-driven mouse pancreatic ductal adenocarcinoma ( mPDA ) cell lines established from KrasLSL-G12D; Pdx1-cre , or KrasLSL-G12D; P48-cre mice ( KC cell lines ) and KrasLSL-G12D; p53lox/+; Pdx1-cre compound mutant mice ( KPΔC cell lines ) [39] . In KC cell lines ( p53-wild type ) , p53 was readily up-regulated by DNA damage treatment , whereas p53 was undetectable in KPΔC cell lines ( p53-null ) ( Fig . 6D ) . Scd1 was down-regulated in the KC , but not in the KPΔC , cell lines ( Fig . 6D ) . Furthermore , repression of SCD by p53 was confirmed in a tetracycline-inducible p53 system in H1299 cells . Upon doxycycline addition , the endogenous SCD level was repressed in a dose- and time-dependent manner ( Figs . 6E and S7A ) . In the SCD locus , chronic p53 accumulation was observed mainly on the CGI ( Fig . 6F ) . Although an early study showed that overexpressed wild type p53 can bind the upstream canonical p53RE in the SCD promoter ( Fig . 6F ) [40] , our data indicate that endogenous p53 preferentially accumulates on a distinct region in the CGI promoter when it is chronically activated . This p53-bound region , containing several p53 motifs ( Figs . 6 and S7B ) , was sufficient for p53 to repress downstream luciferase expression ( Fig . 6G ) . Taken together , our data suggest that SCD expression , which is associated with poor prognosis in some cancers , is directly repressed by chronic p53 through the CGI promoter , providing direct mechanistic insight into the anti-lipogenic role of p53 .
Here we present an extensive study of p53 regulation in different phenotypes using normal human cells . We compared p53 binding profiles in three settings; acDDR , RIS , and E1A and RAS-expressing pApo conditions . In the acDDR condition , which has been the commonly used model for genome-wide mapping of p53 binding sites , p53 peaks were primarily of a sharp non-CGI type , exhibiting a wide distribution in the genome . Interestingly , increasing evidence for distant gene regulation by p53 has been shown using systems where p53 is acutely activated [14 , 41] . This may explain , in part , the diverse locations of non-CGI p53 peaks in the acDDR condition . In contrast , both RIS and pApo conditions were associated with sustained accumulation of p53 on chromatin , where p53 preferentially associated with CGI promoters . In one of the previous p53 ChIP-seq studies , Botcheva et al . identified a substantial number of CGI-type p53 peaks in an acute condition ( Fig . 2D ) [21] . We reanalyzed these external data and found 1811 p53 CGI-peaks , 50% and 52% of which were included in our HC p53 CGI-peaks in the RIS ( 6148 CGI-peaks ) and pApo ( 6566 CGI-peaks ) conditions , respectively . Although the relatively high frequency of CGI-peaks in this external dataset ( compared to 846 HC p53 CGI-peaks in our acDDR condition ) may be an overestimate due to their lack of biological replicates , it reinforces the significance of the connection between p53 and CGI promoters . It is not clear why their study identified many CGI peaks in their acDDR condition . Both studies used HDFs ( IMR90 cells ) , which are highly sensitive to senescence induction by oxidative stress . Notably , we maintained our cells in a physiological ( 5% ) O2 condition to minimize the amount of oxidative stress derived from routine cell culture . Thus the basal levels of p53 and the background senescence phenotype might be different between the studies . The molecular mechanism for the unique profile of chronic p53 seen in our study is unclear . The levels of global chromatin bound p53 were comparable between the acute and chronic ( at least RIS ) conditions ( Fig . 1E ) . Furthermore , p53 binding profiles at promoter regions were almost identical between the RIS and pApo conditions , but the Rcade gene sets were distinct ( compare S3A and S3C Figs ) . Thus , quantitative differences in the global levels of p53 or its genomic distribution alone cannot explain the differential p53 activities . Generally , CGIs are ‘open’ , enriched for the binding sites of many TFs , including Sp1 , which can recruit the TATA-binding general TF complex to TATA-less CGI promoters [22] . Thus in CGI regions , it is conceivable that complex interactions between transcription ( co ) factors can occur depending on cellular contexts . The consensus p53 binding site consists of two decameric half-sites separated by 0–13 nucleotides , but the ‘non-canonical’ half-sites can also function as a p53RE [42 , 43] . Our analysis of two CGI promoters , which are p53-activated ( p21 ) and p53-repressive ( SCD ) , suggests that both CGI-promoters contain multiple ‘weak’ p53REs ( including many half-sites ) , which somehow favor persistent accumulation of p53 ( S2A and S7B Figs ) . These weak p53 associations might well be reinforced by other factors . It is also possible that p53 might associate with DNA through its binding partners . Indeed , our motif enrichment analyses identified known p53-cofactors , including Sp1 ( S7 Table ) within p53 CGI-peaks . Therefore , it is possible that persistent cellular stress creates distinct contexts , where the quality of p53 ( e . g . its post-translational modifications , PTMs ) and the sets of p53 binding proteins are different from acute conditions , thereby facilitating the p53-CGI association . Indeed , p53 can be modified by a multitude of diverse PTMs , including phosphorylation , acetylation , methylation , ubiquitilation , neddylation , sumolyation , and poly-ribosylation [44] . Although the functional roles of these PTMs are not fully understood , some PTMs such as phosphorylation and acetylation typically contribute to stabilization and activation of p53 [44] . Interestingly , as shown in Fig . 4A , many factors involved in PTMs of p53 were included in the p53 self-regulatory hubs derived from the Rcade gene sets ( Fig . 4A ) . This might provide a mechanism for context-dependent fine-tuning of PTMs of p53 at least at a global level . It will be important to determine phenotype-specific genome-wide profiling of individual PTMs of p53 . In addition , a recent study has shown that a genome-wide redistribution of DNA methylation occurs during replicative senescence , where persistent p53 plays a key role [45] . Thus it would also be interesting to examine the structural alterations in CGI regions during RIS and pApo conditions . Notably , these two chronic phenotypes are highly distinct; RIS cells are stably arrested and resistant to apoptosis , whereas pApo cells are rapidly proliferating and sensitive to apoptosis , yet both are largely dependent on p53 [16 , 17] . Such distinct p53-associated phenotypes were not achieved through differential p53 binding alone , since both conditions exhibited highly similar p53-binding profiles , where CGI-type genes are over-represented ( S3A and S3C Fig ) . The unique feature of CGIs , such as their relatively open configuration and their enriched TF binding motifs , might also provide environments that allow for diverse downstream regulation upon p53 binding in conjunction with other ( co ) factors [46] . In addition , our integrated network analyses in chronic conditions identified the extensive capability of p53 for physical interaction with its own targets , further reinforcing the diverse results of p53 binding to the same target promoters . Although the dynamic regulation of p53 through the MDM2-p53 negative feedback loop was readily detected in the DDR condition ( Fig . 1C ) , its relevance in the chronic conditions was not so obvious . In pApo transformed cells , MDM2 was highly up-regulated compared to other conditions , whereas the chromatin bound p53 levels were comparable , or even slightly higher in the pApo condition ( Fig . 1D ) . Although this may be in part due to E1A-induced p14ARF , which inhibits the E3 ligase activity of MDM2 [47] , this is also reminiscent of the tumor specific escape of mutant p53 from Mdm2 degradation in mice harboring germ line p53 mutations , an observation that suggests the existence of additional mechanisms for modulating the p53-MDM2 loop during tumorigenesis [29 , 30] . It has also been shown that the p53-repressive target , malic enzyme 2 , reciprocally suppresses p53 in an MDM2-independent manner during senescence [28] . Together , the dysregulation of p53-hubs particularly in chronic conditions might be a critical step for tumorigenesis . The complex and multi-level gene regulation by chronic p53 appears to apply to its regulation of genes involved in fatty acid synthesis . SCD was previously shown to positively regulate p53 transcription [48] , thus SCD may be a part of the self-regulatory p53 hub . In addition to SCD , Rcade genes included many other genes involved in lipid metabolism in at least in one condition , indicating that p53 regulates fatty acid metabolism at multiple steps ( Fig . 7 ) . Consistently , recent metabolomics studies showed that senescence can be associated with reduced lipid synthesis and increased fatty acid oxidation [49 , 50] . The Rcade genes associated with lipid metabolism include FASN and SREBF1 ( also known as SREBP1 ) , which were repressed by p53 . FASN , which encodes another key lipogenic enzyme , is typically co-regulated with SCD by the lipogenic TF , SREBF1 , and FASN was previously shown to be a target of the p53 family members , p63 and p73 [51] . It was also shown that ectopic p53 can repress the promoter activity of SREBF1 [52] . We confirmed their repression by ectopically expressing p53 in H1299 cells , suggesting that , together with our Rcade analyses , FASN and SREBF1 are also direct p53-repressive targets ( S7C Fig ) . Importantly , the levels of SREBF1 were not reduced but rather slightly up-regulated in the chronic conditions ( S7D Fig ) , thus it is likely that repression of SCD expression by p53 in these settings is direct ( Fig . 6B ) . Given the dynamic regulation of SCD during RIS and pApo , sustained p53 might compete with SREBF1 ( or other lipogenic factors ) at CGI regions . Interestingly , a recent study showed that mutant p53 positively regulates lipogenic genes , including SCD and FASN , in an SREBF1-dependent manner [53] . This study reinforces not only the anti-lipogenic role of p53 but also the functional link between p53 and SREBF1 in lipogenic gene regulation . In addition , it has been shown that p53 is up-regulated in the adipocytes of obese mice , where p53 negatively regulates SREBF1 [52] . It is possible that chronically activated p53 acts as a counter measure against excessive and tumorigenic fatty acid synthesis through various mechanisms . Altogether these results provide additional mechanistic insight into p53 tumor suppression , suggesting that our data represent unique tools for finding cancer therapeutic targets in a p53-mutant context .
IMR90 cells ( normal human diploid fibroblasts ) ( ATTC ) were cultured as previously described under the 5% O2 condition [54] . H1299 cells ( p53-null lung cancer cells ) ( ATCC ) and mouse pancreatic ductal adenocarcinoma ( PDA ) cell lines were cultured in DMEM with 10% fetal bovine serum ( FBS ) under ambient oxygen levels . The PDA cell lines KC1 ( T4878 ) , KC2 ( TB1572 ) and KC3 ( T9394 ) were established from KrasLSL-G12D; Pdx1-cre ( T4878 and T9394 ) , and KrasLSL-G12D; P48-cre ( TB1572 ) mice as described previously [39]; KPΔC was established from KrasLSL-G12D; p53lox/+; Pdx1-cre compound mutant mice , generated after breeding with KrasLSL-G12D [55] , Pdx1-cre [56] and p53lox [57] strains . The following retroviral vectors were used in this study: pBabe-Puro ( HRASG12V ) , pWZL-Hygro ( E1A , HRASG12V ) , and pLNCX2-Neo ( ER:HRASG12V , encoding a fusion protein of the estrogen receptor ligand-binding domain and H-RASV12 ) [54] . The lentiviral RNAi , using a miR30 design , has been described previously [18] . Target sequences of sh-p53: GAGGATTTCATCTCTTGTA ( sh-p53#1 ) [18] and CACTACAACTACATGTGTA ( sh-p53#2 ) . To examine p53-dependent gene expression in each condition , sh-p53 was introduced after the establishment of the phenotype and samples were collected after 5 days , except for the acDDR condition , where sh-p53 was introduced first for at least 5 days before the administration of etoposide ( 100 μM for 24h ) . The tetracycline inducible system ( pCLIIP-i ) for p53 was built into a PiggyBac transposon system [27] in two stages . The first stage plasmid comprised the minimal transposon pCyl50 ( provided by the Wellcome Trust Sanger Institute , Hinxton , United Kingdom ) [58] with a linker , HS4 transcriptional insulators and a PGK-puro expression cassette . The tet-inducible components were added , with a third generation tet-responsive element [59] and a constitutively expressed rtTA3 tet-transactivator ( derived from pTRIPZ; Open Biosystems ) . Wild-type human p53 cDNA was cloned downstream of the tet-responsive element ( pCLIIP-i-p53 ) . p53-null H1299 human lung cancer were co-transfected with pCLIIP-i-p53 with the mouse codon-biased PiggyBac transposon ( mPB ) gene . H1299 cells stably expressing pCLIIP-i-p53 were established in puromycin ( 1 . 5 μg/ml ) containing media for 7 days , and then maintained in the puromycin-free medium . Luciferase activity was assayed using Dual-Luciferase Reporter Assay System ( Promega ) according to the manufacturer’s instructions . Reporter plasmids were transfected to p53-inducible H1299 cells . After 48h of transfection , doxycycline was added to induce p53 expression . Cells were lysed in passive lysis buffer after 24 hours of doxycycline treatment and luciferase activities were measured using a PHERAstar FS microplate reader ( BMG LABTECH ) . The p53-enriched region in the SCD locus in the RIS condition ( Figs . 6F and S7B ) was synthesized ( GeneArt ) , and cloned into the pGL4 . 15 luciferase reporter plasmid ( Promega ) between KpnI and XhoI sites . pGL4 . 38 ( Promega ) , which contains 2x tandem synthetic p53RE , was used as a positive control . The thymidine kinase promoter-Renilla luciferase reporter plasmid ( pRL-TK ) was used as a normalization control . Chromatin isolation was performed as described before [18] . The following antibodies were used for immunoblotting: anti-HRAS ( Santa Cruz , sc-29 ) , anti-human p21 ( Santa Cruz , sc-397 ) , anti-E1A ( Santa Cruz , sc-430 ) ; anti-ß-actin ( Sigma A5441 ) , anti-Cyclin A2 ( Sigma C4710 ) , anti-human p53 ( DO-1 , Sigma P6874 ) , anti-MDM2 ( clones 2A10 and 4B11 ) [18] , anti-Histone H3 ( Abcam ab1791 ) , anti-HMGA2 ( Santa Cruz , sc-30223 ) , anti-SCD/Scd1 ( Cell Signaling , #2438 ) , anti-mouse p53 ( Biovision #3036 ) and anti-mouse p21 ( Santa Cruz #sc-6246 ) , anti-α-Tubulin ( Abcam #Ab18251 ) , anti-SREBP1 ( Santa Cruz , sc-13551 ) . Immunoblotting analysis was carried out as described [18] . Replicating DNA was labeled using BrdU , and SA-ß-Gal activity was assessed as described [18] . Cell viability was determined using a trypan blue exclusion assay . RT-qPCR was performed as described before [18] . CDKN1A ( p21 ) variant specific primer sequences can be found in S2B Fig . Other qPCR primer sequences: p21 Forward primer: AGCAGAGGAAGACCATGTGGA p21 Reverse primer: GCGAGGCACAAGGGTACAA SESN1 Forward: TACCTCAATGCTTAGACGGGCA SESN1 Reverse: TCAGGAGTGCAAACAACAGTTT BTG2 Forward primer: CTCCAGGAGGCACTCACAG BTG2 Reverse primer: ATGATGGGGTCCATCTTGTG ADCK3 Forward: TGATGCCTTTATCAACCCCCA ADCK3 Reverse: CGAAGTATTCCAACTTGTCCCG ANKRA2 Forward: TCACCCATAAAACAGTCAACCA ANKRA2 Reverse: GCCAACTGGTGAACAGACAA HSPA4L Forward: TTCTGCTTAGCGACTTGGGG HSPA4L Reverse: GCTGCTGGTACTGAACCCTT FASN Forward: GCTCCAGCCTCGCTCTC FASN Reverse: TCTCCGACTCTGGCAGCTT SCD Forward: TTCCTACCTGCAAGTTCTACACC SCD Reverse: CCGAGCTTTGTAAGAGCGGT SREBF1 Forward: GCCCCTGTAACGACCACTG SREBF1 Reverse: CAGCGAGTCTGCCTTGATG βActin forward primer: TTCAACACCCCAGCCATGT βActin Reverse primer: GCCAGTGGTACGGCCAGA Gene expression microarray experiments were carried out on Illumina Human WG-6 version 2 arrays as described previously , using three biological replicates per condition [54] . ChIP and library preparation were performed as described previously [54] . In short , the immunoprecipitated DNA was end-repaired , A-tailed , ligated to the sequencing adapters , amplified by 18 cycles of PCR and size selected ( 200–300 bp ) followed by single end sequencing on an Illumina Genome Analyzer IIx ( GAIIx ) according to the manufacturer’s recommendation . Antibodies used were: p53 ( DO-1 Sigma ) ; H3K4me3 ( CMA304 ) , H3K36me3 ( CMA333 ) [54] . Expression microarray and ChIP-seq data are available at the National Center for Biotechnology Information Gene Expression Omnibus under accession numbers GSE53491 and GSE53379 . All data analyses were carried out on R using Bioconductor packages [60] . Raw intensity data from the array scanner were processed using the BASH and HULK algorithms as implemented in the beadarray package [61 , 62] . Log2 transformation and quantile normalization of the data were performed across all sample groups . Differential expression analysis was carried out using the limma package [63] . Differentially expressed genes were determined by computing the log2 contrast between sh-p53#1 and vector control for each condition . Genes were selected using a p-value cut-off of <0 . 01 after application of FDR correction for multiple testing ( Benjamini-Hochberg ) applied globally to correct for multiple contrasts . Data were analysed through the use of IPA ( Ingenuity® Systems , www . ingenuity . com/ ) , and pathway enrichment was determined for genes with log2 ratio >0 . 58 or <-0 . 58 and an FDR corrected p-value < 0 . 01 . Illumina HG6 v2 platform probe list was used as the background set . Pathway heatmaps were generated by plotting negative log of the Fisher’s exact test enrichment p-value against all pathways . The conditions were clustered by hierarchical clustering using R ( R-project ) . Single-end 36 bp reads generated by the Illumina GAIIx or High Seq were aligned against the Human Reference Genome ( assembly hg18 , NCBI Build 36 ) using BWA version 0 . 5 . 5 . Reads were filtered by removing those with a BWA alignment quality score less than 15 . A further filtration was carried out by removing reads falling into the ‘blacklist’ regions identified by ENCODE [64] . Principle Component Analysis ( PCA ) was used to assess the prevalence and quality of read data in TSS regions . Counts were normalized between samples by dividing by effective library size ( bin count sums ) . The MACS algorithm version 1 . 4 . 1 was used together with hg18 aligned , sequence read BAM files for identifying peak regions representing p53 binding sites [65] . Peaks were inspected using the IGV Genome Browser ( v 2 . 3 ) [66] . UCSC defined CpG islands ( CGIs ) were used to identify CGI overlapping peaks . Any peak that overlapped with a CGI was included in the CpG peakset and the remainder included in the non-CGI set . Peaks were mapped to genes using the ChIPpeakAnno BioConductor package and the EBI Peak Annotator . Ensembl 54 ( hg18 ) gtf file downloaded from http://www . ensembl . org/info/data/ftp/index . html was used to annotate genes . The following region definitions were used when calculating genomic distribution of peaks: Core promoter regions ( -3000 to +2000 around TSS ) , distal ( -3000 to-50000 ) , intergenic ( > -50000 ) and downstream extremities ( -2000 to +3000 ) around transcription end site . pApo , acDDR and RIS samples had three biological replicates each , while the growing condition had two replicates . We identified a high confidence ( HC ) peak set consisting of replicated peaks . Peaks that were present in two or more replicates in each condition were included in the HC peak set . Non-replicated singleton peaks in each condition was then compared to peaks in other conditions . Peaks in one condition overlapping with at least two other conditions or peaks in one condition overlapping with peaks in at least two replicates from another condition were also included in the HC peak set . Finally all overlapping peaks were merged to get the final high confidence peak set for each condition . We downloaded the FastQ files for the public data sets and aligned them to hg18 reference genome using BWA and removed contaminants using FastQC [67] . BAM files were generated and peak calling was performed using MACS v1 . 4 . 1 . All other analysis was performed as described . The analysis of gene annotation enrichment was performed using GREAT ( http://great . stanford . edu/ ) using the ‘basal plus extension’ association rules with proximal 10kb upstream and 5kb downstream regulatory domain settings , and the whole human genome ( hg18 ) as background [68] . Peak distributions were plotted and bins 50 bp upstream and 1500 bp downstream of TSS were defined based on p53 signal enrichment . baySeq was used to determine enrichment over input [69] . Counts were normalized using the Quantile method ( baySeq package ) . ChIP-seq and expression data were combined using a Bayesian approach , ranking genes in order of probability of being a p53 target . For each probe , we calculate the posterior probability of a p53 effect on transcription , Pr ( DE and C | data ) , as proportional to Pr ( DE | data ) Pr ( C | data ) —here , Pr ( DE | data ) is the limma-derived posterior probability of differential expression under p53 knockdown , Pr ( C | data ) is the baySeq-derived posterior probability of enrichment for ChIP . Each probe’s posterior probability was logit transformed into a B value , through applying the logit transformation . Probes with B value greater than the threshold-1 . 5 were taken forward in the analysis . IPA upstream regulator analysis method was used as a sequence independent method to confirm the transcriptional regulators of the Rcade gene lists . The DAVID bioinformatics resource ( v6 . 7 ) was used for ontology enrichment analysis of Rcade genes . Illumina HG6 v2 platform probe list was used as the background probe set [70] . Biochemical models of the p53 regulome ( the set of p53 regulated genes ) for each phenotype under consideration was constructed utilizing the following integrative and iterative analytical approach . Putative p53 targets were identified by integrating ChIP-seq and expression datasets using the Rcade method ( Bioconductor ) . Rcade genes with a B value >-1 . 5 were selected as putative p53 targets for further analysis . Reviews , primary scientific publications and phenotype associated biochemical pathways and signaling , regulatory , metabolic and physical interactions involved in each of the conditions were used to build a phenotype specific global network framework . The selected Rcade genes were then used to extract pathway information from multiple public ( KEGG , Reactome , Wikipathways , Pathway Commons , Panther etc . ) and commercial pathway ( Ingenuity Pathway Analysis ) databases [71–75] . Pathways involved were integrated into the model in combination with information integrated from interaction databases and ontology analysis followed by extensive semi-automated literature mining . Sub-cellular localization information and p53 related protein-protein or genetic interactions were integrated by mining relevent biological databases ( InAct , Biogrid , String , IPA , MitoCarta ) [76–79] . Regulation of p53 or by p53 and interaction with p53 or evidence of contribution to or involvement in phenotype for each interaction was documented . Expert manual curation was used to build and iteratively refine these detailed biochemical models of p53 targets . Nodes are represented by p53 induced , repressed genes and those not regulated by p53 providing pathway context . Edges are represented by color-coded arrows denoting catalytic , protein-protein , inhibitory , direct functional , translocation or undefined interactions . A large number of p53 regulated genes identified as p53 interacting or p53 stability modifying proteins documented in S4 and S5 Fig . are shown in detail as regulatory p53 hubs in Fig . 4A . A list of p53 hub genes and evidence for p53 association are provided in S6 Table . The Multiple Association Network Integration Algorithm was used to identify functional association networks . The method uses a large dataset of over 300 functional association networks that are grouped into five categories: co-localization , genetic interaction , physical interaction , predicted interactions and shared protein domains . Networks are weighted according to source-dependent criteria , stored as sparse weighted adjacency matrices , where weight corresponds to gene interaction strength . The algorithm uses the Rcade list to integrate association networks from multiple sources into a composite network using a conjugate gradient optimization method . The computation consists of two parts; an algorithm , based on linear regression , for calculating a single composite functional association network from multiple networks derived from different genomic and proteomic datasets; and a Gaussian label propagation algorithm for predicting gene function given this composite network . Strength of the functional relatedness is represented by the edge density . Network topology and connectivity analysis and biological enrichment analysis of the inferred network was carried out . To determine the specificity of the method we used a similar sized set of random genes ( derived from the universe of human protein coding genes ) and the above network inference methods were applied . This resulted in an extremely sparse network , in which the majority of nodes remained unconnected . The exclusion or inclusion of p53 within the random list had no effect on its connectivity . Networks analysis and visualization was performed with Cytoscape ( ver 2 . 8 . 3 ) software [80] . Biogrid database ( ver 3 . 2 ) was programmatically accessed by perl scripts using the RESTful API . The database was queried with a list of ( pro-apoptosis or senescence ) putative p53 target genes ( Rcade genes with a B value > -1 . 5 ) . Protein-protein interactions were filtered by Rcade lists and then by those consisting of either of the interacting partners being on the previously identified p53 hub gene lists . Interactions between hub genes were clustered into those between p53 , MDM2 and other hub genes and visualized as a circos plot using the Circos program ( ver 0 . 64 ) [81] . CDKN1A and SCD sequences in fasta format were used for transcription factor binding site analysis . The TransfacPro ( v 2013 . 2 ) MATCH algorithm , together with transcription factor position weight matrices and specificity profiles was used to identify TP53 and other transcription factor binding sites [82] . We used the minSUM_good profile to restrict analysis to only high quality matrices and to minimize the sum of both false positive and negative error rates . De novo motif enrichment analysis was performed using MemeChIP package [83] and Position Weight Matrix ( PWM ) scanning based motif enrichment analysis was performed using PscanChip with TransfacPro PWMs and open chromatin background downloaded from UCSC genome browser [84–86] . Distribution of p53 motifs were defined by CentDist [87] . Recursive partitioning ( RP ) was carried out using the R party package on normalized gene expression data from the four datasets , all derived from Affymetrix array platforms [31–33] . Genes were selected as having expression profiles that could stratify patients into subgroups with significantly different survival outcomes , by selecting those genes for which the most significant stratification had a p-value ( adjusted for multiple correction ) of <0 . 05 . p53 expression and mutation status was derived from CEL files for the Miller et al . [38] dataset were downloaded from GEO ( Accession number: GSE3494 ) . All data analyses were carried out on R using Bioconductor packages . The data were normalized using the RMA algorithm . Differential expression analysis was carried out using the limma package . p53 bound , transcriptionally active , putative p53-target genes were derived from Rcade analysis of pro-apoptotic and oncogene RAS-induced senescence conditions . Genes with an Rcade B-value > -1 . 5 was used for further analysis . Core promoter sequences ( -3kb and +2kb around the TSS ) were extracted and transcription factor binding site ( TFBS ) enrichment analysis was performed using the Pscan program together with vertebrate TFBS position weight matrices from the Transfac professional database ( v2013 . 4 ) [85 , 88] . Promoter sequences of equal length to the test set from all protein coding genes were used as a background set .
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The p53 transcription factor is a frequently mutated tumour suppressor that contributes to repairing or eliminating damaged cells . Levels of p53 are typically regulated through its stability; it is constantly produced and degraded , so that upon stress , p53 is up-regulated quickly . This acutely induced p53 has been used as a major model system for studying genome-wide p53 targets . However , emerging evidence suggests that persistently activated p53 is involved in cancer-associated phenotypes , such as cellular senescence . We investigate genome-wide gene regulation by acutely induced p53 through DNA damage as well as chronically activated p53 in oncogene-induced senescence and pro-apoptotic states . Interestingly , acute and chronic p53 DNA binding profiles are highly distinctive , the latter being preferentially associated with larger and relatively open promoters called CpG islands . Furthermore , our integrative analyses of both p53-dependent gene expression and p53-binding genomic DNA profiles reveal that p53 and many of its targets in chronic conditions form extensive self-regulatory hubs , where they can physically interact . The data not only substantially extend the list of direct p53 targets but highlight unique gene regulation by chronic p53 . Finally we show that the cancer-associated lipogenic enzyme , stearoyl-CoA desaturase , is a bona fide p53-repressive target through its CpG island promoter in chronic conditions .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Phenotype Specific Analyses Reveal Distinct Regulatory Mechanism for Chronically Activated p53
|
Land plants have evolved increasingly complex regulatory modes of their flowering time ( or heading date in crops ) . Rice ( Oryza sativa L . ) is a short-day plant that flowers more rapidly in short-day but delays under long-day conditions . Previous studies have shown that the CO-FT module initially identified in long-day plants ( Arabidopsis ) is evolutionary conserved in short-day plants ( Hd1-Hd3a in rice ) . However , in rice , there is a unique Ehd1-dependent flowering pathway that is Hd1-independent . Here , we report isolation and characterization of a positive regulator of Ehd1 , Early heading date 4 ( Ehd4 ) . ehd4 mutants showed a never flowering phenotype under natural long-day conditions . Map-based cloning revealed that Ehd4 encodes a novel CCCH-type zinc finger protein , which is localized to the nucleus and is able to bind to nucleic acids in vitro and transactivate transcription in yeast , suggesting that it likely functions as a transcriptional regulator . Ehd4 expression is most active in young leaves with a diurnal expression pattern similar to that of Ehd1 under both short-day and long-day conditions . We show that Ehd4 up-regulates the expression of the “florigen” genes Hd3a and RFT1 through Ehd1 , but it acts independently of other known Ehd1 regulators . Strikingly , Ehd4 is highly conserved in the Oryza genus including wild and cultivated rice , but has no homologs in other species , suggesting that Ehd4 is originated along with the diversification of the Oryza genus from the grass family during evolution . We conclude that Ehd4 is a novel Oryza-genus-specific regulator of Ehd1 , and it plays an essential role in photoperiodic control of flowering time in rice .
Flowering is a profound transition from vegetative to reproductive development in plants , and is largely determined by genetic pathways that integrate endogenous and environmental signals [1] . Plants control flowering by perceiving their surroundings , such as day-length ( photoperiod ) and temperature that is synchronized with seasonal changes , in order to maximize their reproductive fitness [2] . Flowering time or heading date in crops is also a critical agronomic trait that determines the cropping season and regional adaptability of plants . Thus , control of flowering time has been extensively studied by plant breeders and scientists for more than 100 years [3] . Photoperiod control of flowering refers to the ability of plants to measure day-length and use it as an indicator to initiate flowering . Extensive studies in a model long-day plant ( LDP ) , Arabidopsis thaliana , have revealed that light regulation of the GIGANTEA ( GI ) -CONSTANT ( CO ) -FLOWERING LOCUS T ( FT ) pathway is essential for integrating cellular signals from light signaling transduction and the circadian clock to promote flowering under long-day conditions ( LDs ) [4]–[6] . Phytochrome A ( phyA ) , phytochrome B ( phyB ) and cryptochrome 2 ( cry2 ) regulate FT expression by post-translationally regulating CO protein [7] , [8] . In addition , blue light promotes CO expression by stabilizing the FLAVIN-binding KELCH DOMAIN F BOX PROTEIN1 ( FKF1 ) -GI protein complex [9] , [10] . CO , a zinc finger transcription factor , promotes FT expression under LDs by directly binding to its promoter [11] , [12] . FT , a small mobile protein functioning as the ‘florigen’ , is synthesized in the phloem of leaves , and is then transported to the apical meristem where it initiates flowering by inducing the expression of the floral meristem identity genes , such as AP1 [13]–[15] . Rice ( Oryza sativa L . ) is an important source of calories for mankind and a model short-day plant ( SDP ) that flowers more rapidly in short-day conditions ( SDs ) but delays under LDs with a critical day-length response [16] , [17] . Previous studies have revealed that rice flowering is regulated both by a “SD-activation pathway” and a “LD-suppression pathway” . OsGIGANTEA ( OsGI ) , Heading date 1 ( Hd1 ) and Heading date 3a ( Hd3a ) have been identified as the counterpart of GI , CO and FT , respectively [18]–[20] . Hd1 executes dual function that promotes flowering by regulating Hd3a ( the major SD ‘florigen’ ) expression under SDs , but suppresses it through unknown mechanisms under LDs [19] , [21] , [22] . However , the OsGI-Hd1-Hd3a pathway only plays a limited role in flowering time control in rice because there is a high degree of polymorphism in Hd1 and non-functional alleles of Hd1 are associated with only moderate phenotypic changes [23] . Rice has a unique , Hd1-independent flowering pathway that is mediated by Early heading date 1 ( Ehd1 ) . Ehd1 encodes a B-type response regulator that is highly conserved in cultivated rice , but has no homolog in Arabidopsis [23] , [24] . It has been shown that Ehd1 positively regulates the expression of Hd3a and RICE FLOWERING LOCUS T 1 ( RFT1 ) , the closest paralog of Hd3a that works as a LD ‘florigen’ 22 , 24 , 25 . Circumstantial evidence suggests that Ehd1 is a critical convergence point of regulation by multiple signaling pathways . Among them , OsphyB inhibits flowering under both SDs and LDs by suppressing Hd3a expression through posttranslational modification of HD1 protein function and transcriptional suppression of Ehd1 expression [25]–[27] . The OsphyB-mediated suppression of Ehd1 is regulated by OsCOL4 , which encodes a protein containing two B-box zinc finger domains and one CCT domain and it also acts as a constitutive suppressor of flowering in rice under both SD and LD conditions [26] , [27] . In addition , both Ghd7 ( Grain number , plant height and heading date 7 ) , encoding a CCT domain protein [28] , and DTH8 ( Days to heading 8 ) , encoding a putative HAP3 subunit of the CCAAT-box-binding transcription factor , down-regulate Ehd1 expression and delay flowering under LDs [29] . On the other hand , Ehd1 expression is promoted by a number of positive regulators . Among them , OsMADS51 encodes a type I MADS-box protein and induces Ehd1 expression under SDs [30] , whereas a rice homolog of Arabidopsis SOC1 ( Suppressor of Overexpression of Constant1 ) , OsMADS50 , was identified as a promoter of Ehd1 expression under LDs [31] . Recently , it was shown that Ehd1 expression could be independently up-regulated by Early heading date 2/Rice Indeterminate 1/Oryza sativa Indeterminate 1 ( referred to as Ehd2 hereafter ) and Early heading date 3 ( Ehd3 ) under both SDs and LDs [32]–[34] . The former encodes a Cys2/His2-type zinc finger protein with high homology to maize Indeterminate1 [35] , while the latter encodes a putative plant homeodomain ( PHD ) finger-containing protein . Notably , loss of function of OsMADS50 , Ehd2 and Ehd3 showed a never-flowering phenotype under LDs [25] , [32] , [34] , [36] . Thus , it appears that OsMAD50 , Ehd2 , Ehd3 and Ehd1 may constitute a “LD-activation pathway” in rice . Although these studies have revealed much insight into the photoperiodic flowering of rice , the underlying molecular mechanisms are still not well understood . Here we report the identification of Early heading date 4 ( Ehd4 ) using a mutagenesis approach and its positional cloning . Ehd4 encodes a novel CCCH ( C-X7-C-X5-C-X3-H ) -type zinc finger protein and it acts as a critical regulator promoting flowering under both SDs and LDs , particularly under LDs . Mutation in Ehd4 causes a never-flowering phenotype under natural long-day conditions ( NLDs ) . EHD4 protein is localized to the nucleus and it has nucleic acid-binding and transcriptional activation properties , consistent with a plausible function as a transcription factor . We show that Ehd4 promotes flowering by up-regulating the expression of Hd3a and RFT1 through stimulation of Ehd1 expression . Interestingly , Ehd4 is highly conserved in the Oryza genus and it has no homologs in other plant species . Thus , our findings identified a novel , highly conserved rice-specific regulator of flowering time .
In an effort to isolate genes that are essential for promoting flowering time in rice , we generated a large T-DNA population in a day-length neutral , early flowering variety Kita-ake ( O . sativa ssp . japonica ) . Kita-ake ( Kit ) has been widely used in rice transformation experiments because of its short life cycle . Kit flowers about two months after germination under both SDs ( 10 h light/14 h dark ) and LDs ( 14 . 5 h light/9 . 5 h dark ) conditions in the controlled growth chamber , as well as under natural long-day field conditions ( NLDs ) in Beijing ( 39°54′N , 116°23′E ) , North China ( Figure 1A and 1B ) . To understand the day-length neutral nature of Kita-ake , we cloned ten genes reported to have significant effect on flowering time in rice , including seven genes that promote flowering ( Ehd 1 to 3 , OsMADS50 , OsMADS51 , Hd3a and RFT1 ) and three genes that suppress flowering under LDs ( Hd6 , Hd1 and Ghd7 ) , and compared them with the corresponding genes in Nipponbare ( Nip ) , a japonica variety that is sensitive to day-length . Those flowering-promoting genes are identical in Kit and Nip varieties , except OsMADS51 that contains one amino acid variation ( Figure S1 ) . In contrast , Kit has an immature stop in Ghd7 and a 36-bp insertion and two amino acid changes in Hd1 ( Figure S1 ) . Although there is no difference in Hd6 sequences between Kit and Nip , both of them have an early stop compared with the allele of the indica variety Kasalash ( Figure S1 ) , which delays flowering in Nip background under LDs [37] , [38] . Therefore , complete or partial loss of function of those three genes in Kit could at least partially explain its insensitivity to day-length . We screened our T-DNA population in the NLDs and identified a mutant that failed to flower during the 160 days of growing season ( from late April to early October , 2006 ) , whereas the wild-type ( WT ) Kit flowered 55 days after germination ( Figure 1A and 1B ) . We were able to produce seeds by moving this mutant plant to a controlled SDs . Plants from an F2 population derived from a cross of the mutant and WT segregated in field conditions into three categories based on their flowering time ( days after germination ) : 56 . 9±1 . 8 , 70 . 8±1 . 8 and never flowering mutants in a ratio of 1∶2∶1 ( χ2[1∶2∶1] = 0 . 415<χ20 . 05 , 2 = 5 . 99 , n = 200 ) . This result indicates that the mutation is semidominant and is controlled by a single gene . We named this locus Ehd4 ( Early heading date 4 ) . Compared with WT , ehd4 delayed flowering time by 49 d and 106 d under SDs and LDs , respectively ( Figure 1B ) . Consistent with field observations , flowering time of the heterozygotes was also delayed under both SDs and LDs ( Figure 1B ) . Notably , ehd4 had a similar leaf emergence rate to WT under both SDs and LDs ( Figure 1C ) , indicating that the late flowering phenotype is not caused by retardation in growth rate . The mature ehd4 plants were taller , producing more but smaller seeds . The fertility of ehd4 plants was similar to that of WT ( Figure 1D–1H ) . To test whether the delayed flowering phenotype is genetic background-dependent , we introduced the ehd4 locus into Nip by backcrossing five times , followed by selfing . The ehd4-NIP plants ( BC5F3 ) delayed flowering by 23 d under SDs compared to the WT NIP , but did not flower in NLDs or LDs ( Figure 1B ) . Flowering time of the heterozygotes was also significantly delayed ( Figure 1B ) . Thus , ehd4 has a profound effect on flowering time , especially under LDs , in both a day-length neutral and a day-length sensitive genetic backgrounds . Flowering time control in rice is regulated by the interaction of multiple QTLs and the environments . Generally , flowering time of F2 population derived from japonica×indica displays a normal distribution pattern . Therefore , we crossed ehd4 with 93-11 , an indica variety with an available genome sequence [39] , and generated a BC1F2 population for mapping the ehd4 locus by backcrossing the F1 with 93-11 . The ehd4 locus was initially mapped to the short arm of chromosome 3 ( Figure 2A ) . Using 871 extremely late flowering plants from approximately 25 , 000 BC1F2 plants grown in Hainan Island ( 18°48′N , 110°02′E , average day length 11 hours ) , South China , during the winter of 2008 , we further delimited Ehd4 to a 103 kb region , between the markers EJ-4 and EJ-5 ( Figure 2B ) . This region contains 16 annotated ORFs ( http://rapdb . dna . affrc . go . jp ) ( Figure 2C ) . Sequencing of the genomic DNA of all these genes revealed that there is a single nucleotide substitution ( G to A ) in the first exon of LOC_Os03g02160 , which is predicted to encode a CCCH-Type zinc finger protein . The nucleotide change creates a premature stop codon at the very beginning of the predicted coding region ( Figure 2D ) . Genomic sequence of this gene is identical between Kit and Nip ( Figure S1 ) . Quantitative real-time PCR ( qRT-PCR ) assay showed comparable expression of LOC_Os03g02160 in wild type , heterozygote and ehd4 mutant plants ( Figure S2 ) . Transgenic plants carrying the full-length cDNA of LOC_Os03g02160 , driven by the maize Ubiquitin-1 promoter , fully complemented the ehd4 phenotype under both SDs and LDs . Further , cDNA driven by its native promoter ( 2 . 7 kb upstream from ATG ) also partially rescued the ehd4 phenotype . The phenotypes of these transgenic lines ( days to flowering ) appeared to correlate with the expression level of Ehd4 ( Figure 2E and Figure S2 ) . Thus , we concluded that the LOC_Os03g02160 locus corresponds to Ehd4 . We examined the expression levels of Ehd4 in various tissues and at different stages of leaf development ( Figure 3A ) by using qRT-PCR . Ehd4 transcripts were detected in all tissues examined , but the highest expression was found in emerging young leaves and the lowest level in fully expanded leaves ( Figure 3B ) . Histochemical staining of transgenic plants carrying the GUS reporter gene driven by the Ehd4 promoter indicated that GUS was expressed in all tissues examined and was most abundant in the vascular tissue and apical meristem ( Figure 3C–3I ) . The expression of Ehd4 showed a diurnal expression pattern in leaves . It accumulates after dusk , reaching a peak at dawn , and damping rapidly thereafter under both SDs and LDs ( Figure 3J ) . Moreover , Ehd4 was expressed constantly during the vegetative growth from the second week to the 10th week after germination ( Figure 3K ) . In higher plants , CCCH-type zinc finger proteins have been shown to regulate gene expression by binding to DNA or RNA molecules in the nucleus [40]–[42] . We fused Ehd4 with GFP and transiently expressed the EHD4-GFP fusion protein in rice leaf protoplasts . EHD4-GFP was exclusively co-localized with the OsMADS3-mCherry fusion protein ( a nuclear marker ) in the nucleus ( Figure 4A–4C ) , indicating that EHD4 functions in the nucleus . We further fused EHD4 and its various deletions with the GAL4 DNA binding domain and investigated if EHD4 has transcriptional activation activity in yeast . Full-length wild type EHD4 and an EHD4 variant with only the CCCH motif removed were able to activate the reporter gene expression ( Figure 4D ) . Further deletion of the C terminal region resulted in a dramatic reduction of the activation activity , whereas deletion of both the N-terminal and CCCH motif only had mild effects ( Figure 4D ) . These observations suggest that the activation domain is located in the middle region close to the C-terminal of EHD4 . In addition , a nucleic acid binding assay demonstrated that the C-terminal region , but not the N-terminal region , can bind to both double- and single-stranded calf thymus DNA and ribohomopolymers in vitro , and that removal of the CCCH motif from the C-terminal abolished the binding activity ( Figure 4E ) . These results strongly support the notion that EHD4 likely functions as a transcriptional activator and that the CCCH motif is essential for its nucleic acid binding activity . Photoperiodic induction of the floral transition in rice requires transcriptional activation of Hd3a and RFT1 , the two ‘florigen’ genes , in leaves [20]–[22] . The diurnal expression pattern of Ehd4 implies that it could be involved in photoperiodic control of flowering . To test this , we examined mRNA abundance of Hd3a and RFT1 in ehd4 and WT plants by qRT-PCR . The expression levels of Hd3a and RFT1 were undetectable in ehd4 under both SDs and LDs at all-time points examined during the 48 h period ( Figure 5A–5D ) . Subsequently , expression of the downstream genes OsMADS1 , OsMADS14 and OsMADS15 ( three floral meristem identity genes; [22] , [25] ) was severely impaired in the ehd4 mutants ( Figure S3 ) . Hd1 and Ehd1 are known to regulate Hd3a and RFT1 [19] , [24] . To investigate whether the activation of ‘florigen’ genes by Ehd4 is mediated by Hd1 and/or Ehd1 , we compared their mRNA levels between ehd4 and WT plants . Strikingly , expression of Ehd1 , but not Hd1 , was abolished in ehd4 mutants , indicating that Ehd4 is essential for Ehd1 expression ( Figure 5E–5H ) . Ehd4 has a diurnal expression pattern similar to that of Ehd1 , typically peaking at dawn ( Compare Figure 3J with Figure 5E and 5F ) . Next , we examined whether Ehd4 affects the expression of other known regulators of Ehd1 . To our surprise , the transcription levels of five positive regulators ( Ehd2 , Ehd3 , OsMADS50 , OsGI and OsMADS51 ) and four negative regulators of Ehd1 ( OsphyB , OsCOL4 , DTH8 and Ghd7 ) were not significantly affected in ehd4 ( Figure 6A and 6B ) . These observations suggest that Ehd4 functions upstream of Ehd1 , but largely independent of other known regulators of Ehd1 . Consistent with this , down regulation of Ehd1 , Hd3a and RFT1 in ehd4 was also seen in the Nipponbare background and constantly seen at different stages during plant development ( Figure 6B and Figure S4 ) . To investigate whether Ehd4 expression is regulated by other flowering genes , we examined the expression of Ehd4 in osphyb , ehd2 , ehd3 , osmads50 and osmads51 mutants and near-isogenic lines ( NILs ) which carrying a deficient Hd1 , Ghd7 or DTH8 alleles . Notably , we detected no significant differences of Ehd4 expression in these mutants or NILs , as compared to their corresponding WT plants ( Figure 6C ) . In addition , no significant change of Ehd4 expression was seen in NILs deficient in Ehd1 or Hd3a either ( Figure 6C ) . These results suggest that Ehd4 acts independent of other Ehd1 regulators we examined . Together , these observations suggest that Ehd4 regulates the expression of Hd3a and RFT1 through Ehd1 . This notion was also supported by the observation that over-expression of Ehd1 fully rescued the late flowering phenotype of ehd4 under SDs ( Figure 7 ) . Since EHD4 has a transcriptional activation and nucleic acid binding activity and it promotes Ehd1 expression , we next carried out a yeast one-hybrid assay and a transient transcription assay [43] , [44] to test whether Ehd1 is a direct downstream target of EHD4 . However , only OsLFL1 [45] , but not EHD4 , was able to interact with the Ehd1 promoter ( Figure S5 ) , indicating that Ehd1 is likely an indirect target of Ehd4 . In addition , yeast three-hybrid assay [46] also failed to detect a direct binding of EHD4 to the Ehd1 mRNA ( Figure S6 ) . Moreover , neither EHD2 nor EHD3 , directly binds to the Ehd1 promoter ( Figure S5 ) . Our yeast two-hybrid assay showed that there was no direct interaction among the EHD2 , EHD3 and EHD4 proteins ( Figure S7 ) . Together , these results suggest that Ehd2 , Ehd3 and Ehd4 likely act through distinct pathways to promote the expression of Ehd1 . To further reveal the molecular basis of the flowering phenotype of ehd4 , we performed a transcriptome analysis of ehd4 and wild-type plants using RNA-seq to identify genes downstream of Ehd4 . RNA samples were extracted from the penultimate leaves ( collected at dawn ) of 30 d-old ehd4 and WT plants ( Kita-ake ) grown under LDs . We obtained 2 . 5 M tags and found a total of 256 genes altered in expression with an estimated false-discovery rate of 0 . 1% and the absolute value of log2Ratio at 3 . 15 under the Bayesian model ( Table S1; [47] ) . We found that the transcript numbers of Hd3a , RFT1 , Ehd1 , OsMADS1 , OsMADS14 and OsMADS15 reduced dramatically in ehd4 plants ( Table S1 ) , consistent with the qRT-PCR results ( Figure 5A–5F and Figure S3 ) . Our qRT-PCR analysis with other four genes ( with a log2 Ratio of −11 . 73 , −10 . 33 , −5 . 80 and −3 . 15 , respectively ) also further confirmed the reliability of the RNA-seq results ( Figure S8 ) . Notably , we found that among the genes down-regulated in end4 , 25 of them are known or putative transcription factors , including MADS box , Zinc finger , MYB , SBP and B3 proteins ( Table S1 ) . These genes could be potential candidates involved in the Ehd4-Ehd1-Hd3a/RFT1 pathway to regulate photoperiodic flowering in rice . Ehd4 is a single copy gene in the rice genome . It is predicted to code for a polypeptide of 832 amino acids long , which contains a CCCH ( C-X7-C-X5-C-X3-H ) -type zinc finger motif at the C-terminus ( Figure S9 ) . A blast search ( http://www . ncbi . nlm . nih . gov/ ) found that EHD4 has no clear homologs in other plant or animal species . Thus it appears that Ehd4 represents a unique regulator of flowering time in rice . To investigate the evolutionary history of the gene in rice , we analyzed the Ehd4 sequences from 86 rice accessions with wide geographic distribution and diverse genetic backgrounds , including 32 wild rice species ( O . rufipogon and O . nivara ) and 54 cultivated rice ( Table S2; [48] ) . Ehd4 appears to be highly conserved across these accessions ( share >99 . 2% or higher amino acid sequence identities ) ( Table S2 ) . Sequence analysis identified 25 haplotypes among these accessions . Strikingly , 21 haplotypes were identified in 32 wild rice accessions ( O . rufipogon and O . nivara ) but only 8 haplotypes were identified in 54 cultivated rice accessions analyzed in this study . The dramatic reduction in genetic diversity at this locus suggests that Ehd4 might subject to bottleneck effect [49] . Notably , 4 haplotypes ( Hap_2 , 3 , 6 and 7 ) are shared in cultivated and wild rice ( Figure 8A , Table S2 ) , and among them , Hap_2 and Hap_3 together account 25% of the 32 wild rice and 85% of the 54 cultivated rice ( O . sativa ) respectively ( Figure 8A , 8B and Table S2 ) . Among the cultivated rice , 20 ( 77% ) indica and 6 ( 23% ) japonica accessions belong to Hap_2 , while 19 ( 95% ) japonica and 1 ( 5% ) indica accessions belong to Hap_3 ( Figure 8A and Table S2 ) . This result suggests that the Hap_2 and Hap_3 represent the two major haplotypes at the Ehd4 locus in cultivated rice and that they exist in wild rice before domestication . The distribution pattern of Hap_2 and Hap_3 in indica ( mostly distributed in lower latitude and elevation zones ) and japonica ( mostly distributed in higher latitude and elevation zones ) ( Figure 8C ) implies a likely correlation between the geographic distribution and the functional differences of Ehd4 haplotypes among these cultivated accessions analyzed . To test the possible functional differences of these two haplotypes , we introduced the full-length Ehd4 cDNA of indica variety 93-11 ( Hap_2 ) and Kita-ake ( a japonica landrace , Hap_3 ) driven by the maize Ubiquitin-1 promoter into the ehd4 mutant ( Kita-ake background ) . Strikingly , over-expression of Hap_3 , but not Hap_2 , fully complemented the ehd4 phenotype under NLDs , although their expression levels are comparable ( Figure 8D and Figure S10 ) . This result suggests that Hap_3 of Ehd4 is functionally more potent in promoting flowering than Hap_2 . As another test of this notion , we introduced the Hap_3 allele from Kita-ake into 93-11 by backcrossing five times , followed by selfing . Strikingly , the NIL Ehd4Hap_3 plants ( BC5F3 ) flowered earlier by 19 d under NLDs compared to the parental 93-11 plants ( Figure 8D ) . Together , these results suggest that the functional differences of Ehd4 haplotypes might play a role in geographic adaptation of cultivated rice .
In this study , we have uncovered Ehd4 , which codes for a CCCH-type zinc finger protein essential for promoting flowering under both SD and LD conditions in rice , irrespective of genetic backgrounds . We demonstrated that Ehd4 promotes flowering by positively regulating the expression of Hd3a and RFT1 through Ehd1 but independent of other known important Ehd1 regulators . We further showed that the late-flowering phenotype of ehd4 is more profound in Kita-ake ( Kit ) ( a day-length neutral variety ) than in Nipponbare ( Nip ) ( a day-length sensitive variety ) under SDs , but ehd4 plants flowered eventually in Kit ( 164 days after germination ) but not in Nip under LDs ( Figure 1B ) . It is known that Hd1 acts to promote flowering under SDs but delay flowering under LDs [19] . We found that Hd1 has a 36-bp insertion and two SNPs in Kit compared to Nip ( Figure S1 ) , implying that in Kit , the promoting role under SDs and repressing role under LDs of Hd1 may be impaired . This may at least partially explains why the late-flowering phenotype of ehd4-Nip is less severe under SDs but more severe under LDs . In addition , we found that Kit carries a truncated allele of Ghd7 , a repressor of Ehd1 under LDs , whereas Nip carries a partially functional Ghd7 allele ( Figure S1; [28] ) . Therefore , the never-flowering phenotype of ehd4 in Nip under LDs could be due to the repressive effect of Hd1 and Ghd7 . Strikingly , even in the absence of the functional Hd1 and Ghd7 alleles in Kit , ehd4 alone delayed flowering time by three folds under LDs ( Figure 1B ) , suggesting that Ehd4 plays a major role in promoting flowering in rice , particularly under LDs . Previous studies revealed that rice Ehd1 is a critical convergence point of flowering time regulation by multiple signaling pathways and that Ehd1 acts independently of Hd1 . Ehd1 encodes a B-type response regulator that is highly conserved in cultivated rice , but has no homolog in Arabidopsis [23] , [24] . Up to date , 12 genes have been shown to regulate Ehd1 expression , including 5 positive regulators ( Ehd2 , Ehd3 , OsGI , OsMADS50 and OsMADS51 ) and 7 negative regulators ( SE5 , OsphyB , Ghd7 , DTH8 , OsLFL1 , OsCOL4 and OsMADS56 ) . We demonstrated that Ehd4 promotes flowering by positively regulating the expression of Hd3a and RFT1 through Ehd1 , but independently of these known Ehd1 regulators . It is also of interest to note that the majority of Ehd1 regulators uncovered thus far are nuclear proteins and many of them act as transcriptional regulators , including GHD7 , DTH8 , OsMAD50 , OsMAD51 , EHD2 , EHD3 , OsLFL1 , OsMAD56 and OsCOL4 [26] , [28]–[34] , [36] , [45] , [50] . Map-based cloning revealed that Ehd4 encodes a novel CCCH-type zinc finger protein also localized to the nucleus . The CCCH-type zinc finger protein family is defined as a group of proteins containing 1–6 copies of the canonical C-X-C-X-C-X-H motif ( C-X6–14-C-X4–5-C-X3-H , where X is any amino acid ) [51] . This type of proteins has been found in organisms ranging from human to yeast and many of them have been shown to have either an RNA binding function involved in RNA processing or DNA binding activity [40]–[42] . There are at least 68 CCCH-type genes in Arabidopsis and 67 in rice , respectively [52] . However , only a few plant CCCH proteins have been functionally characterized . EHD4 is the first CCCH-type protein found to regulate photoperiodic flowering . We found that EHD4 is capable of binding to nucleic acids in vitro and transactivate transcription in yeast , suggesting that it likely functions as a transcription factor . Further , our transcriptome analysis revealed that a significant portion of Ehd4-regulated downstream genes are also transcription factors , including several previously identified flowering regulators , such as Ehd1 , OsLFL1 OsMADS1 , OsMADS14 and OsMADS15 , and other putative transcription factors , including MADS box , Zinc finger , MYB , SBP and B3 proteins ( Table S1 ) . These findings together suggest that transcriptional regulation plays a critical role in photoperiodic regulation of flowering in rice . However , despite we have demonstrated that EHD4 has double-stranded DNA and ribohomopolymer binding activity and transactivation activity in yeast , we have not been able to identify the direct target genes of EHD4 in this study . It is also possible that EHD4 may bind to RNA molecules and degrades transcripts of unknown Ehd1 repressors . Further studies are required to elucidate the biochemical function of EHD4 and its functional relationship with other nuclear regulators of flowering time . Rice is known as a short day plant . However , cultivated rice ( O . sativa ) is grown widely in Asia , with a northern limit of nearly 53°N in northern Asia ( Northern provinces of China and Korea , where natural day length during rice cultivation is nearly 15 hours light; [53] ) , whereas O . rufipogon , a wild rice that is the most relative ancestor of O . sativa , is mainly distributed at tropical latitudes with a northern limit about 28°N [54] . The northward expansion of cultivated rice into higher latitudes must be accompanied by human selection of the flowering time trait during rice domestication and breeding , to secure a harvest before cold weather approaches . Strikingly , Ehd4 has no obvious homologs in other plant species including Arabidopsis , maize and sorghum , suggesting that Ehd4 originated along with the diversification of the Oryza genus from the grass family during evolution . Amino acid sequence comparison of EHD4 showed identities at 99 . 2% or higher among a core collection of rice germplasm with wide geographic distribution and diverse genetic backgrounds , including wild rice species ( [48]; Table S2 ) . Interestingly , we found two major haplotypes of Ehd4 , Hap_2 ( the major haplotype in indica ) and Hap_3 ( the major haplotype in japonica ) and that Hap_3 is functional more potent in promoting flowering under NLDs . Since indica rice is known to distribute mostly in lower latitude and elevation zones ( between the latitude 3°S-35°N ) , while japonica varieties are mostly distributed in higher latitude and elevation zones ( between the latitude 15°N-53°N ) , our findings suggest that Ehd4 may have contributed to the northward expansion and regional adaptation of cultivated rice into higher latitudes .
The ehd4 mutant was initially identified from a tissue culture-derived population of rice cv Kita-ake ( japonica ) under natural-day conditions in a paddy field in Beijing ( 39°54′N , 116°23′E ) , China ( 2006 ) . To generate ehd4-nip plants , the mutant locus was introgressed into Nipponbare ( japonica ) background by crossing and backcrossing for five generations ( BC5 ) , where ehd4 mutant is the donor parent and Nipponbare is the recurrent parent , by using marker assisted selection ( MAS ) . Plants were grown in controlled-growth chambers ( Conviron ) under SDs ( 10 h light at 30°C/14 h dark at 25°C ) or LDs ( 14 . 5 h light at 30°C/9 . 5 h dark at 25°C ) with a relative humidity of ∼70% . The light intensity was ∼800 µmol m−2 s−1 . To map the ehd4 locus , the mutant was crossed with the indica cv 93-11 and then the F1 plants were backcrossed with 93-11 to produce a BC1F2 population . We used two DNA pools generated from 15 BC1F2 late-flowering and 15 normal plants , respectively , for rough mapping . For fine mapping , 871 never-flowering plants segregated in the BC1F2 population were used . For the complementary test , the Ehd4 full-length cDNA driven by its native ( 2 . 7-kb ) or the maize Ubiquitin-1 ( Ubi ) promoter were cloned into the binary vector pCAMBIA1390 by using In-Fusion Advantage PCR Cloning Kits ( Clontech ) to create pEhd4::Ehd4 and pUbi::Ehd4 , respectively . The 2 . 7-kb long promoter was also cloned into pCAMBIA-1305 . 1 to create pEhd4::GUS . The resultant plasmids were transformed into the Agrobacterium tumefaciens strain EHA105 and then introduced into ehd4 ( for complementary test ) or Kita-ake WT plants ( pEhd4::GUS ) . At least 15 transgenic events were produced for each construct . GFP was fused to the C-terminus of EHD4 under the control of the 35S CaMV promoter in the pA7 vector . The EHD4-GFP fusion and the nucleus marker OsMADS3-mCherry were transiently co-expressed in rice leaf protoplasts by PEG ( polyethylene glycol ) treatment [55] . Fluorescence was observed using a Leica TCS-SP4 confocal microscope . Transactivation activity assay was performed using the Matchmaker GAL4 Two-Hybrid System 3 ( Clontech ) . Plasmids containing GAL4 DNA binding domain fused with EHD4 deletions were transformed into the yeast strain AH109 . The substrate chlorophenol red-β-D-galactopyranoside ( CPRG; Roche Biochemicals ) was used to measure the β-galactosidase activity according to the Yeast Protocols Handbook ( Clontech ) . EHD4 deletions were cloned into the pMAL-c2x ( NEB ) and expressed in E . coli . 0 . 5 mg purified protein was incubated with 20 mL of poly rG , poly rC , or poly rU attached to agarose beads or double- or single-stranded calf thymus DNA attached to cellulose beads ( Sigma ) in 500 mL of RHPA binding buffer ( 10 mM Tris , pH 7 . 4 , 2 . 5 mM MgCl2 , 0 . 5% Triton X-100 , NaCl at various concentrations ) with 1 mg/mL heparin . After incubation at 4°C for 10 min , the beads were washed five times in the RHPA buffer and then boiled in the SDS loading buffer . Binding of fusion proteins to RNA or DNA was confirmed by protein gel blot using anti-MBP antibodies ( NEB ) . Yeast one-hybrid assay was performed according to the method described in [43] . To generate GAD-EHD4 , GAD-EHD2 , GAD-EHD3 and GAD-OsLFL1 , their full-length cDNAs were cloned into pJG4-5 vector . To generate the Ehd1p::LacZ reporter gene , a 3 . 2 kb fragment of Ehd1 promoter ( including the 5′-UTR ) was amplified from Nipponbare genomic DNA and inserted into the corresponding sites of the reporter plasmid pLacZi2μ . Plasmids were co-transformed into the yeast strain EGY48 . Transformants were grown onto SD/Trp-/Ura plates for 48 hours and then transferred onto X-gal ( 5-bromo-4-chloro-3-indolyl-β-D-galactopyranoside ) plates for blue color development . Yeast three-hybrid assay was performed according to the method described in [46] . Full-length Ehd4 cDNA was cloned into pACTII vector to generate GAD-EHD4 . A series DNA fragments ( about 140 bp ) that transcripting Ehd1 mRNA sequence were cloned into pMS2-1 vector . Plasmids were co-transformed into the yeast strain YBZ-1 . Transformants were grown on plates containing selective media ( SD/Ura-/Leu-/His-+0 , 2 or 8 mM 3-aminotriazole ) for 48 hours before assay . Isolation of rice leaf protoplast and PEG-mediated transfection were performed as described [55] . The reporter construct pGreen-Ehd1p-LUC and effector plasmids ( pEGAD-MycEHD4 , EHD2 , EHD3 or OsLFL1 ) were co-transformed into protoplasts . After transformation , the protoplasts were incubated in darkness for 12–16 h . Bioluminescence assay was performed according to the method described in [44] . Total RNA was extracted using the RNeasy Plant Mini Kit ( QIAGEN ) . For quantitative real-time RT-PCR , the first-strand cDNA was synthesized using the QuantiTect Reverse Transcription Kit ( QIAGEN ) and then PCR was performed using gene-specific primers and SYBR Premix ExTaq reagent ( Takara ) with an ABI Prism 7900 HT Sequence Detection System ( Applied Biosystems ) according to the manufacturer's instructions . PCR reactions were carried out in triplicate for each sample from two independent biological replicates and the rice Ubiquitin-1 gene was used as the internal control . We used the Illumina HiSeq 2000 Genome Analyzer to get tags with CATG site , in which the adapter sequences are 2*100 bp . With Illumina's digital gene expression assay , we obtained 11 . 7 million sequence tags per sample . After removing low quality reads and low quality bases of quality value , clean reads were mapped to the O . ssp . japonica reference sequences using SOAPaligner/soap2 . Mismatches of not more than one base were allowed in the alignment and we generated 8 . 9 million perfect match tags ( 76 . 08% ) for each sample . Initially , we determine 27020 genes of significant differences in expression between the groups of wild-type and mutants by a Student's t-test . With a dedicated Bayesian model , we found 256 transcripts of differential expression with an estimated false-discovery rate of 0 . 1% and the absolute value of log2Ratio is more than 3 . 15 . All primers used in this study are listed in Table S3 . Data deposition: The Ehd4 sequence reported in this paper has been deposited in the GenBank database accession no . JQ828863 ( cDNA ) .
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Rice is an important source of calories for mankind . Flowering time determines cropping seasons and regional adaptability of crops . Rice is originated from its wild progenitor , O . rufipogon , which is mainly distributed at tropical latitudes with a northern limit about 28 °N , more than 10 , 000 years ago . However , cultivated rice is now grown widely in Asia , with a northern limit of nearly 53 °N . The northward expansion of cultivated rice must be accompanied by human selection of the flowering time trait during domestication and breeding , to secure a harvest before cold weather approaches . By identifying a rice mutant that never flowers under natural long-day conditions ( NLDs ) , we cloned Ehd4 as a novel transcriptional regulator that promotes flowering through activation of two “florigen” genes , the signals for flowering initiation . We found that Ehd4 has two major haplotypes: Hap_2 is the major haplotype in indica accessions mostly distributed in lower latitude and elevation zones , whereas Hap_3 is the major haplotype in japonica accessions mostly distributed in higher latitudes and elevation zones . Genetic studies showed that Hap_3 is functionally more potent in promoting flowering under NLDs , implying that Ehd4 may have contributed to the northward expansion and regional adaptability of cultivated rice into higher latitudes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"developmental",
"biology",
"plant",
"science",
"plant",
"biology",
"genetics",
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2013
|
Ehd4 Encodes a Novel and Oryza-Genus-Specific Regulator of Photoperiodic Flowering in Rice
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Candida metapsilosis is a rarely-isolated , opportunistic pathogen that belongs to a clade of pathogenic yeasts known as the C . parapsilosis sensu lato species complex . To gain insight into the recent evolution of C . metapsilosis and the genetic basis of its virulence , we sequenced the genome of 11 clinical isolates from various locations , which we compared to each other and to the available genomes of the two remaining members of the complex: C . orthopsilosis and C . parapsilosis . Unexpectedly , we found compelling genomic evidence that C . metapsilosis is a highly heterozygous hybrid species , with all sequenced clinical strains resulting from the same past hybridization event involving two parental lineages that were approximately 4 . 5% divergent in sequence . This result indicates that the parental species are non-pathogenic , but that hybridization between them formed a new opportunistic pathogen , C . metapsilosis , that has achieved a worldwide distribution . We show that these hybrids are diploid and we identified strains carrying loci for both alternative mating types , which supports mating as the initial mechanism for hybrid formation . We trace the aftermath of this hybridization at the genomic level , and reconstruct the evolutionary relationships among the different strains . Recombination and introgression -resulting in loss of heterozygosis- between the two subgenomes have been rampant , and includes the partial overwriting of the MTLa mating locus in all strains . Collectively , our results shed light on the recent genomic evolution within the C . parapsilosis sensu lato complex , and argue for a re-definition of species within this clade , with at least five distinct homozygous lineages , some of which having the ability to form hybrids .
Hybridization between species is an important evolutionary mechanism that can drive the origin of novel lineages and adaptation to new environments . Hybridization results in the combination of two diverged genomes , which are subsequently shaped by processes of recombination , deletion , and other genomic rearrangements . Genomics have recently paved the way to investigate the stochastic and adaptive processes that follow genomic hybridization . As compared to metazoans or plants , fungi have lower prezygotic barriers and can reproduce clonally for long periods of time , thus hybridization is thought to have a large impact in the evolution of this clade . Consistently , the presence of hybrids in fungi have been extensively documented and an increasing number of cases are being described in the literature [1–8] . Hybridization has been proposed as a mechanism to drive the origin of new human fungal pathogens [8] . Indeed several hybrid species have been described among several human fungal pathogens [8–10] , although in all these cases also non-hybrid strains of the parental species can infect humans . So far , only few studies have focused on population genomics of hybrid species . Here we report a population genomics analysis of an opportunistic pathogen that belongs to the Candida parapsilosis species complex . This species complex comprises opportunistic pathogen species that cause serious infections in immunocompromised patients , and whose incidence has significantly increased in recent years [11] . Three distinct clades within this complex , formerly known as C . parapsilosis groups I , II and III , have been re-defined as different species: C . parapsilosis sensu stricto , C . orthopsilosis and C . metapsilosis , respectively [12] . These species differ in their degrees of prevalence and virulence , C . metapsilosis being the one with the lowest clinical prevalence , and accounting for only 1 . 1 to 8 . 4% of the infections caused by the complex [13] . In addition , the species differ in their degree of prevalence across different types of patients [14–15] . There are few studies investigating the virulence of C . parapsilosis sensu lato species , and particularly little is known about the rarer species C . orthopsilosis and C . metapsilosis . Nonetheless , results of several in vitro and in vivo studies suggest that , consistent with its lower prevalence , C . metapsilosis is the least virulent species of the complex [16–20] . A recent study involving 93 different C . parapsilosis sensu lato isolates , revealed that C . metapsilosis strains were unable to produce extracellular lipases and form pseudohyphae , attributes that are both recognized as important virulence factors for Candida spp . [18] . Furthermore , it has been shown that C . metapsilosis isolates are killed more efficiently by and are less cytotoxic to human primary macrophages [17 , 18] . Finally , other studies have focused on the antifungal susceptibility of different species within the complex showing that strain-to-strain differences within species are common [13 , 21 , 22] . The growing incidence of infections due to C . parapsilosis sensu lato spp . underlines the importance of studies investigating the virulence attributes and molecular genetics of these species . Furthermore , the C . parapsilosis species complex offers an exquisite system for the study of the evolution of pathogenic yeasts and their adaptation to the human host . The complex belongs to the broader CTG clade of Saccharomycetales , which include species that decode the CUG codon as serine instead of leucine . Although the CTG clade includes other clinically important species such as C . albicans and C . tropicalis [23] , their phylogenetic position ( see below ) and particular virulence properties indicates that the species within the Candida parapsilosis species complex evolved pathogenesis towards humans independently of C . albicans and their closest relatives . The sequencing of reference strains for C . parapsilosis [24] and C . orthopsilosis [25] has been instrumental in assessing the main differences with other pathogens within the CTG clade , particularly with the model yeast pathogen C . albicans . Such analyses have revealed that , whereas most Candida species display a similar content of families represented by singleton genes , most of the variability is related to copy number differences in multi-gene families , with pathogens having increased number of members in families related to virulence [24] . For instance , initial comparisons found that C . parapsilosis has an expanded Hyr/Iff family of virulence-related cell wall genes relative to the less virulent species C . orthopsilosis [25] . Subsequent analyses have assessed the genomic diversity among C . parapsilosis [26] and C . orthopsilosis [8] isolates . These studies have enabled important discoveries , such as the realization of the existence of recombination between clinical and environmental lineages in C . parapsilosis , pointing to several recent and recurrent clinical outbreaks from the environment [26] , or the discovery of hybrids between differentiated C . orthopsilosis subspecies , including the description of one virulent hybrid lineage isolated from two very distant locations [8] . In contrast to the growing awareness on the genomic diversity of other C . parapsilosis sensu lato species , for C . metapsilosis we lack both a reference genome and a comprehensive insight on the genomic diversity across isolates . This situation precludes understanding the emergence of virulence traits within this complex . To fill in this important gap we undertook the sequencing and analysis of the genomes of eleven C . metapsilosis clinical isolates . Unexpectedly , we found that all sequenced isolates , sampled from geographically distant locations , presented highly heterozygous genomes , which we show to result from a single hybridization event between two parental lineages differing by 4 . 5% at the nucleotide level .
We used Illumina technology to sequence a panel of eleven C . metapsilosis clinical isolates from different geographical locations ( Table 1 ) . Initial attempts to assemble the individual strains using standard approaches proved unsuccessful , independently of sequencing coverage or the combined use of libraries of different read lengths and insert sizes ( S1 Table ) . In particular , for the strain PL429 four different libraries were used at varying read lengths and insert sizes , totaling an overall coverage of 1 , 308x ( Table 1 ) , yet this still yielded a highly fragmented assembly with thousands of contigs . This elusive assembly for a relatively small genome was reminiscent of what we had previously observed in a highly heterozygous strain of C . orthopsilosis [8] . Indeed assemblies from highly heterozygous genomes are highly fragmented and result in a total genome size larger than expected [8 , 27] . This is because two alternative contigs are recovered for each heterozygous region , while a single , collapsed contig is recovered from each homozygous region . Such assemblies are difficult to scaffold further , as each homozygous contig could be joined , at each side , to either of the two heterozygous contigs . To generate a suitable reference assembled genome for C . metapsilosis , we used a previously developed heterozygous genome assembly strategy [8] , which we describe here in greater detail ( see Materials and Methods ) . To obtain an optimal assembly we had to apply this procedure to the combined data from two strains: the one with the highest sequencing coverage and the larger number of libraries , PL429 ( SZMC1548 ) , and the one producing the least fragmented de novo assembly , SZMC8094 ( Table 1 , S1 and S2 Tables ) . Thus the resulting reference assembly is chimeric in nature and comprises sequences from the two isolates . In addition , similar to previous highly heterozygous assemblies [8] , only one of the haplotypes for each heterozygous region is represented in the final assembly . We then mapped heterozygous regions in each strain relative to this reference assembly . The final assembly resulted in a total size of 13 . 3 Mb in seven putative chromosomes and two unplaced scaffolds , which is similar to the number of bands observed in a Pulsed Field Gel Electrophoresis ( PFGE ) ( S1 Fig ) . The observed band patterning was also indicative of possible genomic rearrangements in several of the analyzed strains , including the two strains used in the reference assembly . Note that PFGE and short range pair-end reads provide information at different scales and thus integration of both sources of information is difficult . Predicted chromosome ends were enriched in C . metapsilosis telomere repeats ( GGTTAGGATGTCCAAAGTATTGA ) , corresponding to the template domain of the telomerase ( TER1 ) [28] in a region ( 827 , 407–829 , 461 ) of scaffold 2 . The annotation of the genome ( see Materials and Methods ) resulted in 5 , 973 protein-coding genes in C . metapsilosis , which is roughly similar to the gene counts in C . parapsilosis ( 5 , 752 ) and C . orthopsilosis ( 5 , 784 ) . The mitochondrial genome was assembled in a single 21 kb-long contig [29] . Species from the Candida parapsilosis complex generally display linear mitochondrial chromosomes , but rare isolates presenting circularized mitochondrial DNA ( mtDNA ) have been identified in C . orthopsilosis and C . metapsilosis [23 , 29] . Our panel includes five strains whose mitochondrial architecture has been determined earlier ( BP57 , CP61 , CP367 , MCO448 , PL448 and PL429 ) , with PL448 being the only known case of a C . metapsilosis strain bearing a circular mitochondrial chromosome [30] . We here determined the architecture of the mitochondrial chromosomes of six additional strains from the genomic data ( See Materials and Methods ) . Notably , we found a new case of circular mitochondrial chromosome in the strain SZMC21154 , whereas the remaining mtDNAs of the newly-tested strains were predicted to be linear ( S2A Fig ) . All these in-silico predictions were confirmed experimentally through PCR and PFGE tests ( see Materials and Methods , Fig 1 ) . As described in [31] the strain PL448 is a direct derivative of the clinical strain MCO448 , and thus the two circularisation events must be necessarily independent evolutionary events . This is consistent with our phylogenetic analysis of the nuclear genomes of the strains ( see below ) and with the fact that , although the circularization results from end-to-end fusion events in both strains , it involves different specific sites in each case ( S2B Fig ) . There is extremely low sequence variability of mtDNA among C . metapsilosis isolates . Hence , the mtDNA-based phylogeny cannot resolve this issue . We next mapped the reads obtained from the sequencing of each of the strains onto the above reference genome , which served to assess sequence variation ( Fig 2 and S1 File ) . All sequenced strains were found to be highly heterozygous ( 22–26 heterozygous SNPs/kb , Table 1 ) , with divergence between the alleles in heterozygous regions averaging approximately 4 . 5% ( see Materials and Methods ) . This high divergence made it possible to delimit heterozygous and homozygous regions , and to calculate the fraction of the genome that was occupied by heterozygous blocks . We will refer to blocks of homozygosity as loss of heterozygosity blocks ( LOH , a genome track where heterozygosity has been lost ) . Such LOH blocks could be the result from several basic mechanisms , including mitotic recombination , break-induced replication or gene conversion [32] . Alternatively an homozygous track of a certain length can occur simply by chance as SNPs in heterozygous regions are not distributed uniformly , but the likelihood of this diminishes quickly with the size of the block . The definition of a threshold is challenging and any arbitrary value will produce false positives or false negatives at different rates . We explored this issue and opted for using a more relaxed ( 100 bp ) and more stringent ( 200 bp ) thresholds for the minimum gap between SNPs in a region designated as an LOH block ( see Materials and Methods ) . Unless indicated otherwise the results at 100 bp threshold are indicated . The fraction of the genome occupied by heterozygous regions varied significantly across strains , ranging from 54 . 5% to 61 . 3% of the genome by length when the 100 bp threshold was applied ( Table 1 ) , and 63 . 4–68 . 5% at the 200 bp threshold . Overall 50% of the homozygous tracks in the genome were in LOH blocks larger than 3 , 626 bp ( LOH-50 ) . The fraction of heterozygous regions is much higher than the 17% found in a C . orthopsilosis hybrid ( where a 100 bp threshold was used ) [8] . This difference may indicate that the C . metapsilosis hybridization is a more recent event or , alternatively , that C . orthopsilosis lost heterozygosity more rapidly . LOH tracts were generally short , with an average size of 535 bp ( 1 , 183 bp at 200 bp threshold ) as compared to 2 , 151 bp in C . orthopsilosis ( S3 Fig ) . This difference may be related to the lower level of heterozygosity in the latter , as multiple , partially overlapping or adjacent LOH events will be seen as a single longer homozygous blocks . Indeed in C . orthopsilosis 20% of the LOH blocks were longer than 1 kb , whereas in C . metapsilosis this fraction was only 7 . 2% . Interestingly , longer LOH blocks were enriched in sub-telomeric regions ( Welch's t-test P<3 . 5e-06 , S4 Fig ) . Importantly , all C . metapsilosis strains shared a significant fraction ( ~ 43% ) of LOH blocks , with 1 , 581 LOH blocks having identical boundaries across all sequenced strains ( out of an average of 10 , 920 LOH blocks , Table 1 ) . Even at a stricter threshold of 200 bp , 125 blocks had identical boundaries in all 11 strains . Of these blocks , 29 were larger than 500bp , including 6 longer than 1kb . This indicates that all sequenced strains derive from the same primary hybridization event and shared a number of LOH events before they diverged . The alternative scenario that those regions with exact boundaries were identical in the parental strains differing on average 4 . 5% is very unlikely . Subsequently other LOH events were shared by only a fraction of the strains , with 19% of LOH blocks being strain-specific in a typical strain . Contrary to the C . orthopsilosis case , where a completely homozygous strain ( i . e . one of the putative hybrid parentals ) exists [8] , none of the sequenced C . metapsilosis strains is homozygous . Furthermore , both haplotypes in a given heterozygous region are roughly equally distant to either C . orthopsilosis or C . parapsilosis out-groups ( 0 . 35% and 0 . 51% difference between the two haplotypes , recpectively ) . This prevents assignment of each haplotype in a heterozygous region to a particular parent , and prevents phasing the homozygous regions ( i . e . in Fig 2 we cannot say whether the grey homozygous regions come from one or the other parent ) . In the C . orthopsilosis hybrid both parents were found to be similarly represented among homozygous regions [8] . In the absence of an unequivocal parental mapping for C . metapsilosis , we approached the question of parental lineage representation using several indirect strategies . Firstly , our assembly process randomly incorporates one of the two haplotypes in a given heterozygous region . Thus , even if we cannot distinguish among parentals , we can arbitrarily name haplotype A the one included in the reference assembly , and assess for the remaining nine strains how often this or the alternative haplotype ( haplotype B ) is present in homozygous regions . We applied this procedure to scaffold6 from PL448 , which underwent LOH of the entire chromosome ( S1 File ) . This provided an overall estimate of 54 . 8% and 45 . 2% representation of the haplotypes A and B , respectively . We stress that these haplotypes do not involve any assignment to a given parental genome . Nevertheless , considering the random incorporation of parental haplotypes in the assembly , this result suggests an approximately balanced presence of both parentals in these homogenized regions . For the rest of the genome , haplotype B is highly underrepresented among LOHs , but this is the result of most LOH blocks being shared among most strains ( S1 File ) . Finally , to study the pattern of LOH on a local scale , we examined one specific region in four strains by PCR and re-sequencing . This 3 . 6 kb-long region around the gene g3863 . t1 ( coding for a protein with a DEAD-box RNA helicase domain ) , is interesting because it encompasses eight recent LOH blocks that are present specifically in 1 to 3 of the four strains . We can consider these eight LOH blocks to have originated independently and we can assess whether the same or a distinct parental haplotype was introgressed in each of these by selectively amplifying and sequencing each of the DNA molecules . Notably , in all cases LOHs present in a given strain resulted from haplotype A overwriting haplotype B ( S5 , S6 and S7 Figs ) . The probability that this occurred by chance assuming equal probability for both haplotypes is 0 . 0039 , which suggests this local region has some preference to lose one of the haplotypes . Altogether these results suggest that , despite a bias towards preferential retention of one parental at the local level in some regions , there is no genome-wide preference for either of the two parental strains . This result is in line with that obtained for a C . orthopsilosis hybrid with similar divergence between parents [8] . This supports the idea that hybrids from less divergent parentals display more balanced inheritance due to a lower risk of genetic incompatibility ( Bateson-Dobzhansky-Muller effect ) . Larger divergence such as the 10% found in Pichia sorbitophila has led to more unbalanced inheritance in that species [33] . The distribution of read counts at biallelic single nucleotide polymorphisms ( SNPs ) suggested a diploid state for the sequenced C . metapsilosis strains ( S8 Fig ) . In addition , this analysis revealed partial aneuploidies in two strains , namely triploidy of scaffold5 in PL448 and partial triploidy of scaffold2 in PL448 and SZMC21154 ( S8 Fig ) . These aneuploidies were independently confirmed by depth-of-coverage analyses ( S3 Table ) . FACS ( Fluorescence-Activated Cell Sorting ) analyses were consistent with the predicted diploidy of 11 C . metapsilosis hybrid strains and C . orthopsilosis MCO456 , although comparison of FACS results across species must be interpreted with caution ( Materials and Methods , S9 Fig ) . Of note PL448 is the strain with more ploidy changes and the one that recently circularized its mitochondrial chromosome ( see above ) . In addition some results suggested some level of heterogeneity in the samples of this strain ( e . g . peak of biallelic counts closer to 40% rather than 50% in diploid chromosomes ) , which may be interpreted as an ongoing genomic instability . The diploid state of the hybrids suggests mating between two haploid cells with genomes ~4 . 5% divergent as the probable mechanism of hybridization . It has been observed that Candida species respond to mating pheromones of different species within the clade [34] . Based on this , mating was suggested as the mechanism of formation of the previously reported C . orthopsilosis diploid hybrid [8] . However , the presence of a single mating type ( MTL ) idiomorph in the two sequenced C . orthopsilosis strains prevented a definitive conclusion . In the current study , however , we found that 10 out of the 11 sequenced C . metapsilosis genomes contain both MTLa and MTLa idiomorphs ( Fig 3 ) , albeit with MTLa incomplete ( see below ) . This result is consistent with mating as the mechanism for hybrid formation and lends further support to the hypothesis that haploid forms and mating occurs in species of the C . parapsilosis clade , a clade which is generally considered asexual [24] . The parasexual cycle , as it occurs in C . albicans can also involve strains of opposite mating type , however in that case diploid state is achieved by concerted loss of chromosomes with little recombination between them [25] and thus most chromosomes would be homozygous for one or the other parental lineage . Of note , the proposal of mating as the origin of hybridization does not imply that the hybrid lineage is able to undergo a sexual cycle , and thus we cannot confidently assign the source of LOH to meiotic or mitotic recombination . Remarkably , the genome sequences indicate that the MTLa idiomorph has partially overwritten the nonhomologous MTLa idiomorph in C . metapsilosis . Our reference genome assembly contained an MTLalpha idiomorph at the MTL locus ( Fig 3A ) on scaffold 5 , with the MTLa genes assembled separately as a small contig ( scaffold 28 , Fig 3B ) . In species such as C . albicans [35] and C . orthopsilosis [36] , the MTLalpha and MTLa idiomorphs are highly divergent in sequence ( <50% identity ) over a region of ~9 kb . In addition to containing the MTLalpha1/alpha2 or MTLa1/a2 genes , which are unrelated in sequence , this idiomorph-specific region also includes three divergent pairs of genes ( OBPa/OBPalpha; PIKa/PIKalpha; PAPa/PAPalpha ) that code for proteins that are not involved in mating and that appear to have diverged into separate alpha and a isoforms with low amino acid sequence identity because they became trapped in the non-recombining region of the mating-type locus millions of years ago [35] . These three genes are also arranged in a different order in the two idiomorphs . In 10 of the 11 C . metapsilosis strains , read-depth and mate-pair data indicated that MTLa haplotype appears to have the structure GAP1 –MTLalpha2 –OBPalpha–PIKhybrid–MTLa2 –MTLa1- orf19 . 3202 . In other words , a 6-kb region derived from MTLalpha and containing MTLalpha2 , OBPalpha and part of PIKalpha ( in that order ) has overwritten a nonhomologous 6 kb region that is normally present in MTLa and contains PAPa , OBPa and PIKa ( in that order ) . Consistent with this introgression happening after the single hybridization event , the divergence between alleles in the introgressed region is very low ( 0 . 025% ) . These results were confirmed by PCR amplification and re-sequencing of five representative strains ( SZMC21154 , SZMC8094 , SZMC8095 , DNS94 ( CP61 ) , DNS100 ( CP376 ) ) . The resulting haplotype contains an intact copy of MTLalpha2 as well as MTLa2 and MTLa1 , it has no PAP gene of any kind , and its PIK gene is chimeric ( S10A and S10B Fig ) . Finally , SZMC21154 experienced an additional LOH removing the remaining MTLa cassette ( MTLa1 , MTLa2 , PAPa ) , a situation which may be reminiscent of what may have occurred in the C . orthopsilosis hybrid . These results are in contrast with an earlier survey that reported that only the MTLα idiomorph was present in 18 isolates of C . metapsilosis [36] based on long-range PCR amplification . However , this discrepancy is likely to result from problems in the PCR in the former study , perhaps attributable to the introgression , because six of these 18 strains were fully sequenced in this study , and in all of them we found intact MTLa1 and MTLa2 ( Fig 3 ) . Predicted duplications and deletions ( copy number variations , CNVs ) in sequenced strains were subjected to restrictive manual curation ( see Materials and Methods ) , resulting in 84 deletions and 87 duplications relative to the reference assembly ( S4 Table ) . Most CNVs affected coding regions , 71 deletions and 85 duplications , but we found no functional enrichment in deleted regions , while nucleic acid binding ( GO:0003676 ) was enriched in duplicated regions . Nearly all CNVs are shared by more than one strain ( 82 deletions and 86 duplications ) and 31 deletions and 15 duplications are shared by all strains , which further support a common origin for all strains . The largest duplication ( DUP65 , 20 kb ) , spanning 13 genes involved in DNA binding , transport and various enzymatic activities , is shared by eight strains . The largest deletion ( DEL8 , 13 , 976 bp ) is heterozygous and is shared by all eleven strains . This suggests that the deletion was either present in one parental undergoing hybridization or happened subsequently but prior to the divergence of the strains considered . To assess the population structure of the species and reconstruct the diversification history of the different C . metapsilosis clinical isolates we employed several alternative strategies . First , multiple correspondence analyses ( MCA ) was conducted using the SNPs ( Fig 4 ) . Secondly , SNP based trees were reconstructed using either all SNPs or homozygous SNPs exclusively ( S11A , S11B and S11C Fig ) . Finally , we reconstructed the evolutionary relationships among the strains using LOH blocks and CNVs as characters ( S11D and S11E Fig ) . All of these approaches resulted in a roughly similar clustering of the strains . Particularly , the MCA shows four major groups: SZMC8094 and CP367 from Italy appear close to each other and well separated from the rest; CP61 ( Italy ) and BP57 ( Hungary ) appear close together , two strains derived from a single isolate from Washington State ( PL448 and MCO448 ) group together , whereas PL429 from Livermore , California ( US ) is rather distant from all the rest . The largest cluster is formed by the rest of the strains from various origins ( Italy , Hungary , Spain and US ) , although the two US strains in this cluster appear somewhat more distant from the rest . These broad separations are also apparent in the phylogenetic trees , particularly when branch lengths are considered . The observed clustering is also consistent with earlier reported clusters based on Amplification Fragment Length Polymorphisms ( AFLP ) , for the five strains common in both studies [37] . The significant differences between the hybrid isolates and the certain degree of geographical structure suggest that this lineage is relatively ancient and spread globally a long time ago . This is in stark contrast with what has been found for the C . orthopsilosis hybrid lineage , where the two sequenced isolates from distant locations were found to be nearly identical [8] . Given our lack of knowledge on mutation rates , generation time and life cycle of C . metapsilosis , we can only speculate on the relative time of when the hybridization occurred . Of note we can only measure divergence among the sequenced strains , while hybridization must have predated this time as indicated by the number of shared events . The low level of differences found between the two most diverged isolates ( MCO448 and SZMC8094 ) suggests that a limited number of point mutations accumulated during this time: 3 SNPs in the mitochondrial genome ( 0 . 0124% divergence ) and 53 SNPs in the longest common homozygous region ( 0 . 01767% ) . The availability of the genome sequence of C . metapsilosis allows , for the first time , to perform a comprehensive comparative genome analysis of the entire C . parapsilosis species complex . Whole genome alignments show that synteny is largely conserved among the three species of the complex ( S12 Fig ) . Overall C . parapsilosis and C . orthopsilosis are closer to each other ( 98% of conserved synteny , 154 inversions ) than either of them to C . metapsilosis ( 97%/231 , and 96%/176 conserved synteny/inversions , respectively ) . We compared the gene content of the three species and compared them with other 23 sequenced Saccharomycetes by reconstructing the complete collection of evolutionary histories of the genes encoded in their genomes ( i . e . the phylome ) and establishing orthology and paralogy relationships among them [38] . The phylogenies , alignments and inferred homology relationships are available through phylomeDB [22] . We used 396 conserved , single-copy orthologs to reconstruct the evolutionary relationships among sequenced Candida species ( Fig 5 ) . This phylogeny was largely congruent with that of a super-tree derived from the whole phylome using a gene tree parsimony approach ( S13 Fig ) . In contrast to earlier analyses based on an smaller sample of genes [25] , but in line with the synteny analyses mentioned above and with an earlier phylogenetic analysis of mitochondrial genomes [29 , 31] , our results support a basal position of C . metapsilosis to the exclusion of C . orthopsilosis and C . parapsilosis . Predicted genes in the three species from the Candida parapsilosis species complex were grouped into 5 , 743 orthologous groups ( including orthologs and in-paralogs ) , of which 5 , 045 ( 88% ) are present across all three species . Of the widespread groups , 4 , 574 ( 91% ) were present as one-to-one orthologs , while 226 , 107 and 124 groups contained C . metapsilosis , C . orthopsilosis and C . parapsilosis specific paralogs , respectively . Differences in gene content for the three species are presented in ( S5 Table ) . We here limit the discussion to several families considered relevant to explain virulence differences between species ( Fig 5 ) . The ability to form pseudohyphae has been associated to virulence in this clade [17] . Unlike C . parapsilosis and C . orthopsilosis , C . metapsilosis does not produce pseudohyphae [18] , and this has been related to the lower virulence of the latter . Pseudohyphae production has been associated with two protein families: the cell-wall proteins Hyr/Iff and adhesion cell-surface glycoproteins ALS . Overall , C . metapsilosis encodes fewer members of Hyr/Iff family ( 13 ) , than C . parapsilosis ( 17 ) , but more than C . orthopsilosis ( 3 in 90–125 and 4 in MCO456 ) ( see Phy00767CU tree in PhylomeDB ) . Interestingly , C . metapsilosis encodes one ALS gene , which is very close to ALS6 ( CPAG_05054/CPAR2_404790 ) , while the two C . orthopsilosis strains encode an ortholog closer to ALS7 ( CPAG_05056/CPAR2_404800; see orf19 . 5736 in phylomeDB , phylome 464 ) . Thus the lack of some ALS genes but not the number of members of Hyr/Iff family correlates with the inability to produce pseudohyphae and consequent lower virulence than in the remaining C . parapsilosis complex species . We and others have previously shown that secreted lipases play an important role in the virulence of C . albicans and C . parapsilosis [18 , 40–42] . Despite earlier reports suggesting that C . metapsilosis strains were unable to produce extracellular lipases [19] , we found that its genome actually codes for a similar number of secreted lipases ( 5 ) as C . parapsilosis and C . orthopsilosis ( 4 ) . This indicates that the observed phenotypic differences may be due to different regulation of the lipase activity rather than to an inherent inability to produce secreted lipases . It has been demonstrated that individual lipase genes are differentially regulated in C . albicans during infection [43 , 44] , and although we lack direct evidence on the function of C . metapsilosis lipase genes , it is appealing to speculate that a similar phenomenon exists in this species . Secreted aspartic proteases are also considered an important virulence factor in C . albicans and C . parapsilosis [45 , 46] , and the other two species of the Candida parapsilosis complex have also been shown to exhibit this activity [18] . Interestingly , C . metapsilosis and C . parapsilosis encode more ( 14 ) secreted aspartic proteases ( SAP ) than any other Candida spp . : C . orthopsilosis ( 11 in MCO456 and 11 in 90–125 ) or C . albicans ( 10 ) ( S5 Table and Phy0076724 in PhylomeDB ) . Although the capacity of C . orthopsilosis and C . metapsilosis SAPs to affect virulence has yet to be demonstrated , an extended SAP toolkit in species of the C . parapsilosis complex , which are not obligate commensals , may represent adaptation to both , environment and host . Similarly , C . metapsilosis , and C . parapsilosis encode more extracellular CFEM domain proteins ( 7 ) , that are important for iron acquisition , than C . albicans ( 5 ) . Overall , the broad functional class corresponding to cell wall and adhesion proteins seems to have a tendency to show larger numbers in pathogenic species as compared to less pathogenic ones , and is the only broad functional class that seems also expanded in non-CTG yeast pathogens , such as those in the Nakaseomyces clade [47] . Our results show compelling evidence that the opportunistic pathogen C . metapsilosis is a diploid hybrid species resulting from a single hybridization event , likely through mating , of two parental lineages that were ~4 . 5% divergent . This hybrid lineage expanded globally and currently isolated strains differ to a significant extent in their genomic background . Divergence has been mostly driven by differential LOH events but also by lineage-specific copy number variations , including large partial aneuploidies . Earlier studies based on AFLP have previously described a high degree of genetic heterogeneity among C . metapsilosis strains [37] , which is consistent with our observations . In addition , our results provide a mechanistic basis for the source of this large heterogeneity: hybridization followed by differential LOH . It remains to be established , however , whether LOH is achieved mainly through mitotic recombination in clonal reproduction or whether sexual recombination or parasexual cycle also take place . In this respect most ( 10/11 ) of the strains harbor at least partial regions of both mating type loci , although in one of the analyzed strains the MTLa locus has completely overwritten MTLa . The levels of heterozygosity found for C . metapsilosis ( 22–26 SNPs/kb ) , are much larger than those described in C . albicans ( 2 . 5–3 SNPs/kb ) [24] . However , considering the trend to lose heterozygosity with time , our findings open the question of whether the heterozygosity in C . albicans- and perhaps other highly heterozygous species in the CTG clade—may have originated via a similar process a longer time ago . Our results argue for a re-definition of the species within the C . parapsilosis clade . We propose the existence of at least five different homozygous lineages and at least two hybrid lineages resulting from distinct combinations of the former . Two of the five homozygous lineages would be nowadays represented by C . parapsilosis and homozygous C . orthopsilosis Type 2 strains such as 90–125 , whereas the remaining three are only partially represented by the sequences of C . orthopsilosis MCO456 and the C . metapsilosis sequences presented in this work ( Fig 6 ) . Whether homozygous strains for these three lineages are extinct or still exist remains to be determined . Considering the pervasiveness of hybrid strains across C . metapsilosis clinical isolates , it can be suspected that the corresponding homozygous , parental lineages are not able to infect humans . This would imply that hybridization has resulted in the evolutionary emergence of the ability to colonize and infect humans by combining characteristics from two parental species that are not able to do so . Hybridization is known to drive the adaptation to new niches and this work emphasizes the idea that new pathogenic lineages can emerge through hybridization of non-pathogenic parental species . Ability to colonize humans may not necessarily be the key advantageous trait that promoted the survival of a new hybrid lineage , but rather human can be a secondary niche that can be exploited opportunistically . Alternatively , a higher ability to persist in humans may promote the survival of hybrids between species that can only sporadically colonize humans . An interesting idea is whether the stress environment provided by humans to species that are not well adapted may promote activation of mating competence , which in turn may open the way for inter-species crossings . In this respect , metagenomics analyses have identified C . metapsilosis in the normal microbiota of one healthy individual , among 20 investigated [48] , although in the absence of a genome sequence we do not know whether this commensal strain was homozygous or heterozygous . In addition , the relative divergence between C . metapsilosis hybrid strains seems to indicate that this lineage did not emerge recently , and that it did not expand as a clinical outbreak . Rather , recursive infections from an already diverged population seem more plausible . If this is the case , the presence of similar hybrid lineages in the natural environment of C . metapsilosis is expected . The earlier reported case of C . orthopsilosis hybrid seems to be different , as two distant isolates had nearly identical sequences . Resolving these open questions requires analysis of the diversity present in healthy individuals and environmental samples , a topic which is largely unexplored .
C . metapsilosis cultures were grown overnight in an orbital shaker ( 200 rpm , 30°C ) in 2 ml YPD medium ( 0 . 5% ( w/v ) yeast extract , 1% ( w/v ) peptone , 1% ( w/v ) glucose ) supplemented with 100 unit/ml penicillin-streptomycin solution ( Sigma ) . Subsequently , cells were centrifuged ( 850 xg , 5 minutes ) and were washed twice with 1x sterile PBS . The pellet was resuspended in 500 μl lysis buffer ( 1% ( w/v ) SDS , 50 mM EDTA , 100 mM TRIS pH = 8 ) , 500 μl glass bead was added to the cells and were disrupted by using a vortex for 3 minutes . 275 μl 7M ammonium-acetate was added ( 65°C , 5 min ) and the samples were then cooled on ice for 5 minutes . 500 μl of chloroform-isoamylalcohol ( 24:1 ) was added to the mixture , and the samples were centrifuged for 10 minutes at 16000 xg . The upper phase was transferred to a new microcentrifuge tube , and the previous step was repeated . 500 μl isopropanol was mixed with the upper phase in a new microcentrifuge tube , and the mixture was held in a refrigerator at -20°C for 5 minutes . The solution was centrifuged at 16000 xg for 10 minutes . The supernatant was discarded , and the pellet was washed twice with 500 μl 70% ethanol . After the second washing step the pellet was dried , and resuspended in 100 μl sterile bi-distilled water containing 250 μg/ml RN-ase ( Sigma ) . The genome sequences for the 11 strains were obtained at the Ultra-sequencing core facility of the CRG , using Illumina GAIIx , HiSeq2000 and MiSeq sequencing machines . For paired-end libraries , DNA was fragmented by nebulization or in Covaris to a size ~300 bp , ~400 bp , ~600 bp . The ends of the DNA fragments were blunted with T4 DNA polymerase and Klenow fragment ( New England Biolabs ) , after shearing . DNA was purified with a QIAquick PCR purification kit ( Qiagen ) . 3’-adenylation was performed by incubation with dATP and 3’-5’-exo- Klenow fragment ( New England Biolabs ) . DNA was purified using MinElute spin columns ( Qiagen ) and double-stranded Illumina paired-end adapters were ligated to the DNA using rapid T4 DNA ligase ( New England Biolabs ) . After another purification step , adapter-ligated fragments were enriched , and adapters were extended by selective amplification in an 18-cycle PCR reaction using Phusion DNA polymerase ( Finnzymes ) . Libraries were quantified and loaded into Illumina flow-cells at concentrations of 7–20 pM . Cluster generation was performed in an Illumina cluster station . Sequence runs of 2x50 , 2×76 , 2x100 or 2x250 cycles were performed on the sequencing instrument . For the preparation of mate-pair libraries 15 micrograms of genomic DNA were sheared using a covaris instrument to the desired size range of 2 . 5 or 5 kb , respectively . Following size selection on a 0 . 8% agarose gel , the size fraction of interest was recovered , and library preparation was performed using a modification of the Illumina mate-pair preparation protocol , whereby a biotinylated double-stranded adapter was included in the circularisation reaction [49] . After circularisation , linear background was removed by exonuclease digestion , and the sample further fragmented in the covaris . Fragments that included the biotinylated adapter were enriched using streptavidin beads , and used to prepare an Illumina library . Sequencing was performed on an Illumina HiSeq 2000 sequencer using a 2 x 50 nt paired-end sequencing protocol . Base calling was performed using Illumina pipeline software . In multiplexed libraries , we used 4 bp internal indices ( 5’ indexed sequences ) . De-convolution was performed using the CASAVA software ( Illumina ) . Reads were pre-processed before assembly to trim at the first undetermined base or at the first base having PHRED quality below 10 . We filtered out pairs with one ( or both ) reads shorter than 31 bases after trimming . SOAPdenovo2 [50] was used to assemble paired-end reads into supercontigs with K-mer ranging from 31 to 91 . As the initial assembly was very fragmented ( 2–4k scaffolds ) and nearly twice as large ( 21–22 Mb ) as other C . parapsilosis complex species ( ~13 Mb in 7–8 chromosomes ) , we assumed the presence of heterozygous regions in our strains . Heterozygous regions ( 9 Mb in 861 contigs ) were removed by Haplomerger version 20120810 [51] . Subsequently , the remaining supercontigs were further scaffolded by SSPACE2 [52] and gaps were filled using GapCloser from the SOAPdenovo2 package . The random incorporation into the assembly of alternative heterozygous contigs was tested by repeating the whole procedure several times , starting from reads that were randomly re-ordered . Genes were predicted using Augustus version 2 . 5 . 5 [53] and C . parapsilosis CDC317 gene models for training [24] . Predicted gene models were curated using RNA-Seq reads to find evidence for exon-intron boundaries and exon skipping . Subsequently , we grouped predicted genes into orthologous groups and transferred functional annotation from one-to-one orthologs in model species i . e . Candida albicans or Saccharomyces cerevisiae , based on predictions from the MetaPhORs approach [54] . Finally , genes were further annotated using InterProScan 5RC4 [55] . Genomic reads were aligned onto C . metapsilosis assembly using Bowtie2 with “very sensitive local alignment” mode [56] . SNPs and INDELs were called using GATK version 2 . 1–13 [57] . We filtered out clusters of five variants within 20 bases and low quality variants , as described in GATK documentation ( QD < 2 . 0 || MQ < 40 || FS > 60 . 0 || HaplotypeScore > 13 . 0 || MQRankSum < -12 . 5 || ReadPosRankSum < -8 . 0 ) . Subsequently , we divided the genome into three categories: unknown , heterozygous , and homozygous . Firstly , regions having lower ( <75% ) or higher ( >125% ) coverage than expected were assigned as unknown . Then , we marked heterozygous regions as those having two or more heterozygous sites closer than 100 bases . The remaining regions of the genome were considered homozygous , thus loss of heterozygosity ( LOH ) regions ( 100 bp threshold ) . A stricter threshold ( 200 bp ) was established by considering LOH blocks shorter than 200 bp as heterozygous regions . Note that the two methods differ in expected number of false positive and false negatives . At 4 . 5% divergence the probability of having by chance a stretch of 100 bp with no heterozygous SNPs is 0 . 01 ( 0 . 955100 ) and the expected number of LOH blocks of this length or longer in a 13 . 6 Mb genome is approximately 5 , 854 blocks , these numbers vary dramatically to 0 . 0001 and 58 when a 200 bp threshold is applied ( Expected number is approximated as E = Npqk , where N is genome size in basepairs , p and q are the probabilities of having a SNP or not , respectively and k is the required size of the block ) . We compared the number of expected blocks of a given size or longer with the observed sizes in the real strains ( S14 Fig ) . This made clear that a large number of short apparent LOH blocks ( up to ~59% ) may be artefactual when a threshold of 100 bp is applied ( ~2 . 9% at 200 bp ) . However , the stricter threshold would conversely discard many true LOH blocks ( up to 97 . 1% of the discarded blocks would be real if we consider the observed–expected ) . Given that most differences affect blocks of short length , the effects of the total fraction of the genome assigned to homozygous or heterozygous regions is affected to a lesser extend . We further assessed the accuracy of our method by simulating 20 fully heterozygous genomes ( 13 . 6 Mb; 4 . 5% divergence between haplotypes ) to estimate false positive of LOH detection ( how often we would detect LOH in perfectly heterozygous genome using current settings ) . Heterozygous genomes were simulated using fasta2diverged . py v1 . 0 ( https://github . com/Gabaldonlab/ngs_public ) with the homozygous chromosome set of C . metapsilosis assuming 4 . 5% divergence between haplotypes . LOH regions ( at least 100bp regions having less than 2 SNPs ) appear by chance in all simulations and on average sum up 782 , 850 bp ( 5 . 84% of the genome ) . Thus we estimate that less than 6% of the regions detected as LOH in our analysis correspond to false positives . Increasing LOH length cut-off from 100bp to 200bp decreases false positive rate to 0 . 13% , however . Throughout the manuscript we provide estimates based on both of these thresholds . The sequence divergence between the parental haplotypes was calculated as the number of heterozygous sites found in heterozygous regions divided by the cumulative length of heterozygous regions , using a 100 bp threshold . Two main characteristics allow in silico differentiation of linear and circular mtDNA chromosomes in C . metapsilosis . First , due to the presence of telomeres , consisting of tandem arrays of 620 bp repeat , linear chromosomes are expected to be longer ( 24 , 152 bp , NC_006971 ) than circular ones ( 22 , 175 bp , AY391853 ) [29] . Second , paired-end reads resulting from circular mitochondrial genomes when aligned to the termini of the linear mitochondrial chromosome reference assembly should have their partners aligned in the opposite end of the chromosome with disconcordant orientation ( FF or RR instead for FR ) . To check this , genomic reads were aligned on the linear mitochondrial chromosome reference of C . metapsilosis MCO448 ( NC_006971 ) as indicated above . Mitochondrial DNAs in C . metapsilosis isolates were analysed by PFGE and PCR essentially as described in [30 , 31] . Briefly , whole-cell DNA samples were prepared in agarose blocks and separated in a 1 . 5% ( w/v ) agarose gel using a CHEF Mapper XA Chiller System ( Biorad ) with pulse switching set at 5 to 20 seconds ( linear ramping ) and 120o angle for 42 hours at 5 V/cm and 10oC ( Fig 1A ) or in a 1 . 0% ( w/v ) agarose gel in a Pulsaphor apparatus ( LKB ) in contour-clamped homogeneous electric field ( CHEF ) configuration with pulse switching from 5 to 50 seconds ( interpolation ) for 24 hours at 150 V and 9oC ( Fig 1B ) . All separations were performed in 0 . 5x TBE buffer ( 45 mM Tris-borate , 1 mM EDTA , pH 8 . 0 ) . Southern blots were hybridized with radioactively labeled probes derived from the mitochondrial genes cox2 and nad4 . For PCR analysis , the reactions contained diluted total cell DNA , 0 . 5 μM upstream and downstream primers ( 5’-ATTGTTGCTTTTGTTGTTGA-3’ and 5’-TTAGCTGTTGTTGCTATTACT-3’ derived from the subtelomeric genes nad3 and atp6 , respectively ) , 0 . 2 mM dNTPs each , 1× reaction buffer with 2 mM MgCl2 , and 1 U of Taq DNA polymerase ( Invitrogen ) . The amplification was performed using the following cycler profile: 3 min at 95°C; 25× ( 1 min at 94°C , 45 seconds at 56°C , 1 min at 68°C ) ; 3 min at 72°C . The primers bind to the opposite subterminal regions of the linear mitochondrial genome and allow amplification of about 0 . 95 kb long fragment derived from the end-to-end junction of circularized genome forms ( Fig 1C ) . Structural variants were detected using a methodology described and experimentally validated elsewhere [54] , which we have implemented in bam2sv . py python script v1 . 0 ( available at https://github . com/Gabaldonlab/ngs_public/ ) . bam2sv . py v1 . 0 detects duplications , deletion and inversions by means of insert size deviations and incongruent read pairing between paired-end reads . In addition , duplications and deletions are detected from deviations from mean depth of coverage . All detected variants were manually curated . In addition , we generated genome graphs for all chromosomes illustrating copy number variation , as well as , heterozygous and homozygous regions ( S1 File ) . To validate the two parental sequences , we performed PCR and Sanger sequencing of the region scaffold2|size2959145:1 , 570 , 477–1 , 574 , 155 from C . metapsilosis genome in four different strains: BP57 ( DNS25 ) , CP61 ( DNS94 ) , CP376 ( DNS100 ) and PL429 . Four PCR primers were designed using Primer3 v4 webtool [58] , namely two forward primers and two reverse primers , with four and three different bases among them , respectively , corresponding to allelic differences in each parental sequence ( S5 Fig ) . Thus , four touchdown PCR reactions ( FWD_1+REV_1 , FWD_1+REV_2 , FWD_2+REV_1 and FWD_2+REV_2 ) were carried out using Expand Long Range , dNTPack kit ( Roche ) according to manufacturer’s instructions . Briefly , each reaction included primer concentration of 0 . 3 μM , 10 μl of 5X Buffer with MgCl2 ( final MgCl2 concentration of 2 . 5mM ) , 2 . 5 μl of PCR Nucleotide Mix , 3% ( v/v ) of DMSO , 100 ng of DNA and 3 . 5 U of Enzyme Mix in a final volume of 50 μl . Cycling condition began with a warm-up step of 2 min at 92°C , followed by 15 cycles of 10 seconds at 92°C , 15 seconds at the corresponding annealing temperature per each pair of primers ( decreasing 0 . 5°C each cycle ) and 4 min at 68°C . The initial annealing temperatures were: 61 . 6°C , 64 . 1°C , 60°C , and 62 . 5°C for FWD_1+REV_1 , FWD_1+REV_2 , FWD_2+REV_1 and FWD_2+REV_2 , respectively . Then , other 20 cycles of 10 seconds at 92°C , 15 seconds at the corresponding annealing temperature and 4 min at 68°C ( increasing the extension time 20 seconds at each cycle ) were set up , with a final extension step at 68°C for 7 minutes . PCR products were confirmed by 1 . 5% agarose gel electrophoresis and were then purified using QIAquick PCR Purification Kit ( QIAGEN ) . Specific PCR products were only obtained when combining the primer sets FWD_1+REV_2 , and FWD_2+REV_1 ( amplicon size of 3678 bp ) , while no product was obtained when combining FWD_1+REV_1 or FWD_2+REV_2 primers ( S6 Fig ) . The purified PCR products were sequenced using the BigDye Terminator v3 . 1 Cycle Sequencing Kit ( Applied Biosystems ) and sequencing products were precipitated and purified using EDTA 125mM , sodium acetate 3M and 100% ethanol . To cover the entire length of the products , apart from the PCR primers described above , further internal primers common to both parental sequences were designed and used for direct sequencing: The MTL introgression was checked by means of PCR and Sanger sequencing in following strains of C . metapsilosis: SZMC21154 , SZMC8092 , SZMC8094 , SZMC8095 , CP61 ( DNS94 ) , CP367 ( DNS100 ) . We have designed 8 different primers: The introgression was validated by 4 different PCRs ( MTLα1_1F –MTLα1_1R , MTLα2_1F –MTLα2_1R , MTLa1_1F –MTLa1_1R and MTLa2_1F –MTLa2_1R ) using Pfu DNA polymerase from PROMEGA . The reaction mixture consisted of 5μl of Buffer 10X with MgSO4 and1μl of 10 mM dNTPs , both provided by the manufacturer , 2μl 10 μM of both forward and reverse primers , 0 . 4μl of Pfu DNA polymerase 3 U/μl and water filled up to 50μl . The PCR started with initial denaturation at 95°C for 2min , this was followed 30 cycles of 30 seconds at 92°C , 30 seconds at 61 . 0°C , 30 seconds at 72°C , it was finished with final extension for 5min at 72°C and cooled to 4oC . PCR products were confirmed by 1 . 5% agarose gel electrophoresis and were then purified using QIAquick PCR Purification Kit ( QIAGEN ) . Finally , in order to confirm linearity of MTL after introgression , we have amplified and Sanger sequenced genomic regions flanking introgression site . We have designed 6 primers: The linearity of introgression was validated by 4 different PCRs ( P1f ‐ P1rα , P1f—P2ra , P2fα—P2r and P2fa—P2r ) using Pfu DNA Polymerase from PROMEGA . The reaction mixture consisted of 5μl of Buffer 10x with MgSO4 and1μl of 10 mM dNTPs , both provided by the manufacturer , 2μl 10 μM of both forward and reverse primers , 0 . 4μl of Pfu DNA polymerase 3 U/μl and water filled up to 50μl . The PCR started with initial denaturation at 95°C for 2min , this was followed 30 cycles of 30 seconds at 92°C , 30 seconds at either 56 . 2°C ( P1f ‐ P1rα ) , 57 . 2°C ( P1f –P2ra ) or 54 . 2°C ( P2fα–P2r and P2fa–P2r ) ; 30 seconds at 72°C , it was finished with final extension for 5 min at 72°C and cooled to 4oC . PCR products were confirmed by 1 . 5% agarose gel electrophoresis and were then purified using QIAquick PCR Purification Kit ( QIAGEN ) . Sanger sequencing was performed using an ABI Prism 3730xl DNA Analyzer ( Applied Biosystems ) . Yeasts cells were cultured for 24 hours , at 30°C , in an oxygen rich environment , in 5ml YPD ( 0 . 5% ( w/v ) yeast extract , 1% ( w/v ) peptone , 1% ( w/v ) dextrose ) supplemented with 100 unit/ml penicillin-streptomycin ( Sigma ) in an orbital shaker ( 180 rpm ) . After 24 hours 100 μl suspension was transferred to 5 ml YPD and the cells were incubated for 24 hours again , under the same conditions . Agarose blocks containing the intact chromosomes were prepared using the method of Schwartz & Cantor [59] with the following modifications . 1 ml of the yeast suspension was transfered in a sterile microcentrifuge tube , and was washed two times with 4°C 0 . 05 M EDTA ( pH = 7 . 5 ) ( Sigma ) ( 2000 xg , 3 min ) . 1 . 3x108 cells were resuspended in Isotonic Buffer ( 0 . 1 M phosphate–citrate buffer , equipped with 0 . 7 M sorbitol , 0 . 3 M mannitol , 0 . 001 M EDTA pH = 5 . 8 ) containing 1 M potassium-thioglycolate ( Reanal ) , and it was incubated for 1 hour , at 30°C in an orbital shaker ( 180 rpm ) . The suspension was washed once with Isotonic Buffer ( 2000 xg , 3 min ) . The pellet was resuspended in 5 ml Isotonic Buffer containing 3% ( w/v ) Helicase and 0 . 5% ( w/V ) NovoZym 234 ( Novo BioLabs ) , and it was incubated at 30°C , in a sterile 15 ml Falcon tube , overnight , in an orbital shaker ( 180 rpm ) . The spheroplasts were collected and washed once with Isotonic Buffer ( 300 xg , 5 min ) . The pellet was resuspended in 42°C 0 . 125 M EDTA , mixed immediately with prewarmed ( 42°C ) 2% ( w/v ) low-melting-point agarose ( Sigma ) , then placed into a mould chamber . After solidification , inserts were incubated in 2 ml NDS buffer ( 1% ( w/v ) N-laurylsarcosine in 0 . 5 M EDTA , pH = 9 . 5 ) supplemented with 1 mg/ml Proteinase K ( Sigma ) at 50°C . During the two days of incubation the NDS-Proteinase K solution was replaced once . The inserts were washed once with 0 . 5 M EDTA ( pH = 8 ) overnight , then were stored in 0 . 5 M EDTA ( pH = 8 ) at 4°C until usage . Finally , yeast chromosomes were separated by CHEF [60] method by using Bio-Rad CHEF-DR II Drive Module , Bio-Rad Pulsefield 760 Modul and Bio-Rad Power Supply . The chromosomal DNA plugs were placed and separated in 0 . 9% ( w/v ) agarose gel ( Sigma ) prepared with filtered 0 . 5x TBE buffer with the following settings: 60–450 sec switching time , 90 V voltage , 168 h running time . 0 . 5x TBE was used as a running buffer and the temperature was kept at 10°C during the whole procedure . The buffer was replaced to fresh one 3 times during the running process . The gel was stained for 30 min in a 0 . 1% ethidium-bromide solution and was destained in distilled water overnight , at 4°C . The results were documented by using UVP Bio-Doc-It System . Ploidy analyses were confirmed using FACS for 12 Candida samples . Cells were grown in YPD medium at 30°C ( overnight , 200 rpm ) , harvested , resuspended in deionized distilled water and fixed in ethanol at a 107 cells/ml concentration ( overnight , 4°C ) . For the staining of cells with SYBR Green I , cells were first washed and resuspended in 750 μl of 50 mM sodium citrate buffer , treated with 250 μl of 1mg/ml RNase A solution for 1 hour at 50°C and finally with 50 μl of 20 mg/ml proteinase K solution for 1 hour at 50°C . Then , 20 μl of SYBR Green I ( Life Technologies , diluted 1:10 th in Tris-EDTA buffer , pH 8 . 0 ) were added to the samples and they were stained overnight at 4°C protected from light . Triton X-100 was added at a final concentration of 0 . 25% ( v/v ) and samples were vortex . Finally , samples were sonicated ( 3 consecutive ultrasound pulsed at 30 W for 2 seconds with intervals of 2 seconds between each pulse ) to eliminate most of the cell clumps before FACS analysis with FACScan at the FACS Unit from CRG/UPF . Chromosomes/scaffolds of C . parapsilosis CDC317 , C . orthopsilosis 90–125 and C . metapsilosis SZMC8094 were aligned with LAST aligner v189 [61] . Alignments shorter than 1kb were filtered out . Syntenic blocks were defined as contiguous regions in the same chromosome/scaffold of both genomes aligning over 10 kb , percentage of synteny is computed as the total length of syntenic blocks over the length of the genome . Synteny breaks were inferred if fragments longer than 10 kb from a contiguous region in one genome was aligning to at least two different chromosomes in the other species . Inversions in the query sequence were called when alignment direction changed within a given synteny block . The evolutionary histories of all C . metapsilosis protein-coding genes were reconstructed in the context of 27 Saccharomycotina species ( S6 Table ) , using the PhylomeDB pipeline [62] . In brief this pipeline proceeds as follows: first , homologs were retrieved using Smith-Waterman [63] with E-value cut-off of 1e-05 and considering only sequences that aligned with at least 50% of their length . Subsequently , homologs were aligned using three programs: MUSCLE v3 . 8 [64] , MAFFT v6 . 712b [65] and KALIGN v2 . 04 [66] in two directions: forward and reverse . The six resulting alignments were combined with M-COFFEE [67] and finally trimmed using trimAl v1 . 3 [68] applying consistency cutoff of 0 . 1667 and a gap score cutoff of 0 . 1 . Neighbour Joining trees were reconstructed and the likelihood of obtained topology was computed , allowing branch-length optimisation , using seven different models ( JTT , LG , WAG , Blosum62 , MtREV , VT and Dayhoff ) , as implemented in PhyML 3 . 0 [69] . One evolutionary model best fitting the data was determined for each alignment by comparing the likelihood of the used models according to the AIC criterion . Finally , Maximum Likelihood ( ML ) trees were inferred for selected models . In all cases a discrete gamma-distribution model with four rate categories plus invariant positions was used , the gamma parameter and the fraction of invariant positions were estimated from the data . Branch support was computed using an aLRT ( approximate likelihood ratio test ) parametric test based on a chi-square distribution , as implemented in PhyML . All alignments and trees generated have been deposited in PhylomeDB with ID 243 [39] . Orthologs predicted for C . metapsilosis genes can be retrieved from MetaPhOrs database [54] . Five separate analyses were used to reconstruct the evolutionary relationships among the sequenced strains . Alignments were reconstructed from SNP information in three different types of regions: ( i ) Patterns from homozygous SNPs present in the longest LOH block that is shared by all the strains; ( ii ) SNP patterns from the whole genome . Heterozygous SNPs were encoded using the base which is alternative to that in the reference , and choosing randomly one of the alternative bases in heterozygous SNPs if both were different from the reference; and ( iii ) Haplotype patterns based on three-state haplotype ( heterozygous , hapA , hapB ) assignment in windows of 1 kb , resulting in 1 , 798 phylogenetically informative patterns; Separately , character-based matrices were reconstructed using ( iv ) 127 ploidy patterns from 84 deletions and 87 duplications ( S4 Table ) ; ploidy state was coded as 0 for null deletion , 1 for heterozygous deletion , 2 for wild-type ( no deletion and duplication ) , 3 for duplication ( 3 copies of given locus ) , 4 for duplication ( 4 copies of given locus ) , and so on; and ( v ) 587 LOH presence and absence patterns . Maximum Likelihood phylogenetic trees were reconstructed from these alignments using RAxML 7 . 2 . 8 using GTRCAT for sequence alignments ( datasets i to iii ) , and GTRGAMMA for multi-state character matrices ( datasets iv and v ) [70] . Finally , multiple correspondence analysis ( MCA , an extension of Principal Component Analysis to categorical data ) of 618 , 120 SNPs with at least 10x coverage was performed using ade4 package from R [71] . Two different approaches were used to reconstruct a species tree of Candida species and relatives . First a parsimony-based super-tree was reconstructed using duptree v1 . 48 [72] from the 5 , 780 gene trees from C . metapsilosis phylome available at PhylomeDB id 243 [39] . Then a Maximum Likelihood ( ML ) tree was reconstructed with PhyML v3 . 0 [69] and the Jones-Taylor-Thornton ( JTT ) evolutionary model , based on an amino acid super-matrix of 232 , 760 columns resulting from concatenating the alignments of 396 one-to-one orthologs . The two species trees are nearly identical with Robinson-Foulds symmetric distance of 6 , meaning both trees share 50 out of 56 possible splits . All phylogenies were visualised with ETE [73] . Sequencing data , genome assembly and annotation have been deposited to EBI-ENA ( accession: PRJNA238968 ) . Reconstructed trees and alignments were deposited to PhylomeDB ( http://phylomedb . org ) as PhylomeDB ID 243 .
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Human pathogens belong to different phylogenetic clades and it is clear that the ability to infect humans emerged several times independently . The sequencing and comparison of genomes from pathogenic and non-pathogenic species and strains paves the way to identify what genomic changes underlie the emergence of virulence . In this study we sequenced 11 globally-distributed clinical isolates of Candida metapsilosis , an emerging fungal pathogen of growing concern . We found that all isolates were the result of a single hybridization between two unidentified species , which points to hybridization as a mechanism for the origin of a virulent lineage . We found that the hybrids likely originated by sexual reproduction as they were diploids and retained genomic regions of opposite mating types . We reconstructed the aftermath of the genome merging by identifying where recombination led to the removal of one of the parental subgenomes . We finally compare the newly-sequenced genome with those of other pathogens from the Candida clade and establish global trends , such an enriched repertoire in cell-wall proteins in more virulent species . Our results provide insight into how hybridization may play a key role in the emergence of novel pathogenic lineages .
|
[
"Abstract",
"Introduction",
"Results",
"and",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
The Genomic Aftermath of Hybridization in the Opportunistic Pathogen Candida metapsilosis
|
The bloodstream forms of Trypanosoma brucei ( BSF ) , the parasite protist causing sleeping sickness , primarily proliferate in the blood of their mammalian hosts . The skin and adipose tissues were recently identified as additional major sites for parasite development . Glucose was the only carbon source known to be used by bloodstream trypanosomes to feed their central carbon metabolism , however , the metabolic behaviour of extravascular tissue-adapted parasites has not been addressed yet . Since the production of glycerol is an important primary function of adipocytes , we have adapted BSF trypanosomes to a glucose-depleted but glycerol-rich culture medium ( CMM_Glyc/GlcNAc ) and compared their metabolism and proteome to those of parasites grown in standard glucose-rich conditions ( CMM_Glc ) . BSF were shown to consume 2-folds more oxygen per consumed carbon unit in CMM_Glyc/GlcNAc and were 11 . 5-times more sensitive to SHAM , a specific inhibitor of the plant-like alternative oxidase ( TAO ) , which is the only mitochondrial terminal oxidase expressed in BSF . This is consistent with ( i ) the absolute requirement of the mitochondrial respiratory activity to convert glycerol into dihydroxyacetone phosphate , as deduced from the updated metabolic scheme and ( ii ) with the 1 . 8-fold increase of the TAO expression level compared to the presence of glucose . Proton NMR analysis of excreted end products from glycerol and glucose metabolism showed that these two carbon sources are metabolised through the same pathways , although the contributions of the acetate and succinate branches are more important in the presence of glycerol than glucose ( 10 . 2% versus 3 . 4% of the excreted end products , respectively ) . In addition , metabolomic analyses by mass spectrometry showed that , in the absence of glucose , 13C-labelled glycerol was incorporated into hexose phosphates through gluconeogenesis . As expected , RNAi-mediated down-regulation of glycerol kinase expression abolished glycerol metabolism and was lethal for BSF grown in CMM_Glyc/GlcNAc . Interestingly , BSF have adapted their metabolism to grow in CMM_Glyc/GlcNAc by concomitantly increasing their rate of glycerol consumption and decreasing that of glucose . However , the glycerol kinase activity was 7 . 8-fold lower in CMM_Glyc/GlcNAc , as confirmed by both western blotting and proteomic analyses . This suggests that the huge excess in glycerol kinase that is not absolutely required for glycerol metabolism , might be used for another yet undetermined non-essential function in glucose rich-conditions . Altogether , these data demonstrate that BSF trypanosomes are well-adapted to glycerol-rich conditions that could be encountered by the parasite in extravascular niches , such as the skin and adipose tissues .
Trypanosoma brucei is an extracellular protist parasite that causes Human African Trypanosomiasis ( HAT ) or sleeping sickness , a neglected tropical disease in Sub-Saharan Africa [1] . This parasite undergoes a complex life cycle from the bloodstream of a mammalian host ( bloodstream forms—BSF ) to the alimentary tract ( procyclic form—PCF ) and the salivary glands ( epimastigote and metacyclic forms ) of its blood-feeding insect vector ( the tsetse ) [2] . There is no vaccine against HAT and the available drugs are difficult to administer and present a number of side effects [3] . Importantly , up to 10% relapses after treatment have been reported , probably due to resurgences of the original infecting strains [4 , 5] . In addition , tsetse flies may become infected after feeding on microscopy-negative infected humans or pigs , showing that these apparently aparasitaemic hosts actually host the parasite [6 , 7] . Altogether , these observations strongly suggest the existence of extravascular anatomical reservoirs of parasites in the mammalian host that remained unknown until recently . Indeed , this long-lasting question has recently been answered by the description in well-established mouse models that the BSF show a marked tropism to the skin [8 , 9] , from which transmission to the tsetse vector can occur [9] , as well as to adipose tissue [10] . Strikingly , trypanosomes were also detected in the skin of human subjects from a HAT endemic area [9] . Furthermore , within the mouse skin , some parasites were seen in close contact with dermal adipocytes , the major constituent of fat , suggesting that the trypanosome-adipocyte interaction may confer a selective advantage to T . brucei [8] . In the bloodstream of the mammalian host , the pleomorphic BSF proliferate as long-slender BSF or differentiate into the non-proliferative short-stumpy BSF that are pre-adapted to a further differentiation into PCF in the tsetse midgut [11] . These parasitic forms of T . brucei share the particularity to possess glycosomes , peroxisome-derived organelles that contain enzymes required for glycolysis . However , PCF and BSF trypanosomes have developed different strategies to produce ATP . Between bloodmeals , the tsetse digestive tract contains negligible amounts of glucose and the fly mostly uses proline as a main carbon source for flight [12–14] . In this context , PCF have developed a proline-based central metabolism and rely on proline metabolism to establish an infection in the fly midgut [15 , 16] . Proline is mainly converted by PCF into excreted alanine through part of the tricarboxylic acid ( TCA ) cycle , with production of ATP by oxidative phosphorylation from the mitochondrial FO/F1-ATP synthase fed by the proton gradient generated by the respiratory chain [17] . However , the presence of glucose induces a metabolic switch toward glycolysis , accompanied with a down-regulation of proline metabolism [17] . In these glucose-rich conditions , glucose is converted into the excreted end products succinate and acetate , and most ATP molecules are produced by substrate level phosphorylation [18] . In contrast , it is widely accepted that slender BSF exclusively rely upon glycolysis as an energy source . In this context , the down-regulated TCA cycle is now poorly or not active and the respiratory chain does not produce ATP anymore [19] . It was generally accepted that the proliferative slender BSF grown under aerobiosis convert glucose exclusively into pyruvate [20–22] . However , it has recently been demonstrated that BSF actually also convert ~15% of the consumed glucose into excreted acetate , alanine and succinate , with a rate of acetate excretion from glucose breakdown comparable to that in PCF ( Fig 1A ) [23] . More importantly , key enzymes involved in the production of these three "minor" glycolytic end products are essential for BSF viability , i . e . the alanine aminotransferase [24] , the pyruvate dehydrogenase complex [23] and the phosphoenolpyruvate carboxykinase [25] . This highlights the fact that the central metabolism of BSF trypanosomes is probably much more elaborate and flexible than initially considered . Here , we show for the first time that BSF can readily and efficiently adapt their central metabolism to a glycerol-rich medium in the absence of glucose , not only for survival but also to sustain a long-term proliferation . These data further illustrate the adaptive capacity of African trypanosomes and pave the way to study the metabolism of the mammalian forms of the parasite in extravascular compartments such as adipose tissues and especially in the skin , which is also crucial for parasite transmission and where glycerol may be an alternative carbon source .
To identify carbon sources alternative to glucose , we developed a glucose-depleted medium based on the Creek's minimal medium ( CMM ) [26] containing 50 mM N-acetyl glucosamine ( GlcNAc ) to inhibit the uptake of the FCS-derived glucose ( 0 . 5 mM final concentration in the minimal medium ) . GlcNAc is a competitive inhibitor of the T . brucei glucose transporters , as demonstrated by its lethal effect on monomorphic T . brucei 427 90–13 BSF in either glucose-rich CMM ( CMM_Glc/GlcNAc , 10 mM glucose ) or glucose-depleted CMM ( CMM_GlcNAc , 0 . 5 mM glucose ) ( Fig 2A ) . The glucose-transport inhibition effect of GlcNAc was confirmed by the abolition of glucose consumption by BSF trypanosomes in the presence of a 100-fold excess of GlcNAc ( 50 mM GlcNAc ) compared to glucose ( 0 . 5 mM ) ( Fig 2B ) . Strikingly , the 427 90–13 BSF cell line was able to sustain a long-term proliferation in the glucose-depleted CMM containing GlcNAc after addition of 10 mM glycerol ( CMM_Glyc/GlcNAc conditions ) . Transfer of the CMM_Glc-adapted BSF in the CMM_Glyc/GlcNAc medium strongly affected growth of the parasite , which was partially restored after at least one month of adaptation in the CMM_Glyc/GlcNAc conditions , with a doubling time only ~30% higher than in glucose-rich conditions ( CMM_Glc ) ( 11 ± 1 . 6 h versus 7 . 3 ± 0 . 4 h ) ( Fig 2A ) . To investigate the capability of BSF to use glycerol , we measured the rates of glycerol consumption in cells pre-adapted or not to CMM_Glyc/GlcNAc and compared these data to the rates of glucose consumption . Cells were adapted for one month in either CMM_Glyc/GlcNAc or CMM_Glc and then were transferred to fresh CMM medium containing either glycerol/GlcNAc , glucose or glycerol/glucose to measure the consumption of the carbon sources . The rates of glucose and glycerol consumption were determined by enzymatic assay of the carbon sources remaining in the CMM medium . Since glucose contains 6 carbons and glycerol only 3 , data were expressed as carbon molecules equivalent ( mol . C ) for comparison purpose . Cells adapted to CMM_Glyc/GlcNAc consumed glycerol at the rate of 57 . 9 ± 1 . 8 μmol . C per h per 108 cell ( Fig 2C and Table 1 ) . This was lower than the rate of glucose consumption by cells adapted to CMM_Glc medium ( 69 . 0 ± 3 . 6 μmol . C per h per 108 cell ) , which can explain the lower growth rate on glycerol compared to glucose . It is noteworthy that after adaptation to CMM_Glyc/GlcNAc conditions , the rate of glycerol consumption increased by 9 . 9% , while the rate of glucose consumption is reduced by 13% , respectively , compared to cells adapted to CMM_Glc ( Table 1 ) . We compared the release of end products by BSF incubated in PBS containing glucose and/or glycerol using the 1H-NMR profiling approach previously developed [27] . As previously observed , BSF cultivated in CMM_Glc mainly converted glucose into pyruvate ( 85 . 8% of the excreted end products ) and alanine ( 10 . 8% ) , with lower amounts of acetate ( 2 . 6% ) and succinate ( 0 . 8% ) ( Fig 3 ) [23 , 25] . It is noteworthy that glycerol possibly produced from glucose cannot be quantified using our NMR approach due to overlapping resonances between glucose and glycerol . Glycerol was also converted into these four excreted end products , with higher ratio of acetate ( 6 . 8% ) and succinate ( 3 . 4% ) , while the alanine production remained in the same range ( 11 . 4% ) and the pyruvate proportion was decreased ( 78 . 5% ) ( Fig 3 ) . This suggests that glycerol was indeed catabolised through the same pathways as glucose , yet with slight differences in the flow distribution within the different branches of the network . The rate of all end product excretion from glycerol and glucose consumption in cells adapted to CMM_Glyc/GlcNAc were increased by 16 . 1% and reduced by 15 . 2% , respectively , as compared to cells adapted to CMM_Glc , which was consistent with the rates of carbon source consumption described above ( Table 1 and Fig 3 ) . When BSF were grown in the presence of equal amounts of glucose and glycerol ( CMM_Glc/Glyc , 5 mM each ) , both carbon sources were consumed , although the parasites showed a preference for glucose . Indeed , cells adapted to CMM_Glc consumed glycerol at a rate 3 . 3-fold lower in CMM_Glc/Glyc compared to CMM_Glyc/GlcNAc , while the rate of glucose consumption was only 1 . 3-fold reduced in CMM_Glc/Glyc compared to CMM_Glc ( Fig 2C and Table 1 ) . These ratios were equivalent for cells adapted to CMM_Glyc/GlcNAc ( 3 . 5 and 1 . 3 , respectively ) ( Fig 2D and Table 1 ) . Considering that two molecules of glycerol ( 3 carbons ) are the equivalent to one molecule of glucose ( 6 carbons ) , this implies that glucose contributes ~3 . 5-times more than glycerol to the central carbon metabolism at equimolar concentration ( 54 versus 15 . 6 μmol . C per h and per 108 cells , see Table 1 ) . It is noteworthy that the overall carbon consumption was maintained in CMM_Glc and CMM_Glc/Glyc in both cells adapted to CMM_Glc ( 69 and 69 . 6 μmol . C per h and per 108 cells , respectively ) and cells adapted to CMM_Glyc/GlcNAc ( 60 and 62 . 4 μmol . C per h and per 108 cells , respectively ) . To confirm these data , quantitative analyses of excreted end products from glucose and/or glycerol metabolism were achieved by using a metabolite profiling assay based on the ability of 1H-NMR spectrometry to distinguish 13C-enriched molecules from 12C molecules . To discriminate the metabolic origin of end products , cells were incubated in PBS with equal amounts ( 4 mM ) of uniformly [13C]-enriched glucose ( [U-13C]-glucose ) plus glycerol . In these experiments , labelled end products and unlabelled end products were derived from glucose and glycerol , respectively [27 , 28] . Cells adapted to CMM_Glc and CMM_Glyc/GlcNAc excreted 2 . 0- and 2 . 1-times more end products from the catabolism of glucose than from glycerol ( Fig 3 ) , which means that glucose contributed ~2-times more to the carbon supply to central metabolism . This was consistent with the higher contribution of glucose observed in rich medium CMM_Glc/Glyc ( Table 1 ) . These data also showed that the BSF preference for glucose remained equivalent after adaption to CMM_Glyc/GlcNAc ( Fig 3 ) . Although the growth rate was reduced in BSF adapted to CMM_Glyc/GlcNAc , the rate of endogenous oxygen consumption was higher in the presence of glycerol compared to glucose . Indeed , cells adapted to CMM_Glyc/GlcNAc consumed 1 . 64-times more oxygen from glycerol compared to oxygen consumption from glucose of cells adapted to CMM_Glc ( Fig 3A , asterisk ) . These data were consistent with the glucose and glycerol metabolic pathways schematized in Fig 1A and 1B , respectively . Indeed , only one molecule of oxygen ( 2 x ½ O2 ) is required to regenerate , through the glycerol phosphate shuttle ( steps 6 , 21 , 24 and 25; blue pathway in Fig 1 ) , two molecules of NADH produced upon glucose conversion into two molecules of 1 , 3-bisphosphoglycerate ( step 8 ) . In contrast , two oxygen molecules are required to metabolise two molecules of glycerol ( equivalent to one molecule of glucose ) . This additional oxygen molecule is necessary to convert the glycerol-derived glycerol 3-phosphate into dihydroxyacetone phosphate through the glycerol phosphate shuttle ( steps 7 , 21 , 24 and 25 , black pathway in Fig 1B ) . According to our current knowledge on BSF metabolism , respiration strictly depends on the alternative oxidase activity ( TAO , step 25 ) , which is sensitive to salicylhydroxamic acid ( SHAM ) [29] . Indeed , respiration of BSF incubated in CMM_Glc and CMM_Glyc/GlcNAc was almost abolished by the addition of 4 mM SHAM ( Fig 4A ) . Moreover , the BSF respiration in the presence of glucose or glycerol was affected neither by addition of 2 μM CCCP , an uncoupling agent dissipating the mitochondrial proton gradient , nor by the addition of 4 mM oligomycin , a specific inhibitor of the FO/F1-ATP synthase that generates the proton gradient in BSF [30 , 31] . This confirmed that respiration is not linked to the proton gradient and is primarily driven by TAO , regardless the carbon source used between glucose or glycerol . Considering that oxygen is absolutely required for DHAP production from glycerol ( see Fig 1B ) , although glucose can be catabolised in the absence of oxygen to produce glycerol ( see Fig 1A ) [32] , we reasoned that BSF sensitivity to SHAM-induced TAO inhibition could depend on the carbon source metabolised by BSF . As expected , the 427 90–13 BSF cell line maintained in CMM_Glyc/GlcNAc was 11 . 5-times more sensitive to SHAM compared to the same cell line grown in CMM_Glc ( EC50 of 1 . 6 ± 0 . 3 μM versus 18 . 5 ± 5 . 4 μM , respectively ) ( Fig 4B ) . An intermediate sensitivity to SHAM was observed in cells grown in CMM_Glyc ( EC50 of 5 . 8 ± 2 . 8 μM ) , certainly due to the consumption of the residual 0 . 5 mM glucose present in the medium ( Fig 4B ) . It is noteworthy that oxygen consumption from glycerol and glucose metabolism of cells adapted to CMM_Glyc/GlcNAc increased by 18% and was reduced by 7 . 6% , respectively , compared to cells adapted to CMM_Glc , which was consistent with the rate of glucose and glycerol consumption in of cells adapted to these two growth conditions ( Table 1 ) . To further dissect the metabolic fluxes involved in BSF adaptation to glycerol in the absence of glucose , we reasoned that one major pathway could be gluconeogenesis , a glycosomal function that remained unexplored in BSF trypanosomes so far . In the CMM_Glyc/GlcNAc context , gluconeogenesis should be activated in order to produce the glucose 6-phosphate ( G6P ) precursor required for several pathways that are essential for the cells , such as the production of the GPI anchors used for VSG biosynthesis . To investigate the unexpected and unexplored gluconeogenic metabolic pathway in the 427 90–13 BSF strain , we determined by mass spectrometry the incorporation of 13C atoms from uniformly [13C]-enriched glycerol ( [U-13C]-glycerol ) into glycolytic intermediates , as well as other key metabolites of the intermediary metabolism . Cells were incubated 1 h in the presence of 2 mM [U-13C]-glycerol and incorporation of 13C into metabolites was quantified by IC-MS/MS ( Fig 5A , top panel ) . Glycerol rapidly fed the central carbon metabolism as deduced from >98% of fully labelled triose phosphates and alanine . However , only 50–66% of the dicarboxylic acid molecules , i . e . malate , fumarate and succinate , contained at least one 13C-carbon , which was consistent with the relatively low contribution of the succinate production pathway compared to the pyruvate production ( see Fig 3 ) . The high proportion of 3-carbon labelled dicarboxylic acids ( 30–50% ) , instead of 4-carbon ( 3–5% ) , was due to the carboxylation of phosphoenolpyruvate into oxaloacetate ( Figs 1B and 5B ) . Glycerol was also converted into hexose phosphates , with 100% ( fructose 1 , 6-bisphosphate ) to 90% ( G6P ) of them being fully 13C-enriched , which highlighted the relatively high flux through the gluconeogenic pathway . Glycerol-derived G6P fed the pentose phosphate pathway with 70% and 12 . 5% of 6-phosphogluconate and pentose 5-phosphate molecules being fully 13C-enriched , respectively . In the presence of equimolar amounts of glucose , the incorporation of label from [U-13C]-glycerol into hexose phosphates and intermediates of the pentose phosphate pathway was reduced to background levels ( Fig 5A , lower panel ) . 16% to 37% of the triose-phosphate and alanine molecules were fully labelled , which suggests that in these conditions , glucose contributed ~4-times more than glycerol to central metabolism . This was consistent with the analyses of glucose and glycerol consumption ( Table 1 ) and metabolism ( Fig 3 ) in the same incubation conditions . Altogether , these data showed that BSF trypanosomes have developed the metabolic capacity to produce G6P through gluconeogenesis in the absence of glucose . To further study the metabolic modifications occurring in BSF trypanosomes adapted to glycerol conditions , the proteome of cells grown in CMM_Glyc/GlcNAc was compared to that of cells grown in CMM_Glc . Among the 2 , 081 proteins identified by at least 3 different peptides , a total of 1 , 052 proteins were retained for further analyses after having successfully passed the ANOVA statistical test ( p-value ≤0 . 05 ) . In total , only 29 proteins and isoforms were up- or down-regulated more than 2-fold ( 2 . 7% of the proteome ) and 109 proteins with a 1 . 5-fold threshold ( 10 . 4% of the proteome ) , suggesting that BSF are quite well pre-adapted to live and proliferate in a glycerol-rich and glucose-depleted environment ( S1 and S2 Tables ) . Glycerol kinase ( GK , EC 2 . 7 . 1 . 30 , step 7 in Fig 1 ) , which is encoded by 5 tandemly arranged genes ( Tb927 . 9 . 12550 , Tb927 . 9 . 12570 , Tb927 . 9 . 12590 , Tb927 . 9 . 12610 , Tb927 . 9 . 12630 ) was the most down-regulated protein in CMM_Glyc/GlcNAc ( 4-fold ) . This surprising observation was confirmed by western blot analysis ( Fig 6A ) . In addition , the GK activity was 7 . 8-fold reduced after cell adaptation to CMM_Glyc/GlcNAc , while the hexokinase activity was not affected , as confirmed by the proteome analysis ( Fig 6B and 6C , S3 Table ) . This demonstrated the expression of a large excess of GK in CMM_Glc-adapted BSF , since the 7 . 8-fold reduction of the GK activity did not induce a reduction of the rate of glycerol consumption . Actually , the rate of glycerol consumption was increased by 11% , although one would have expected the opposite ( see Table 1 ) . Interestingly , the expression of the 75 kDa invariant surface glycoprotein isoforms ( ISG75 ) [33] were 3- to 4-fold down-regulated after cell adaptation in CMM_Glyc/GlcNAc . ISG75 is implicated in the uptake of suramin , the first-line trypanocidal compound against T . b . rhodesiense , indicating that ISGs may act as receptors , although their ligand ( s ) remain to be identified [34] . ISG75 down-regulation in cells grown in CMM_Glyc/GlcNAc , which was confirmed by western blotting ( Fig 6A ) , is therefore another piece of the puzzle to understand its enigmatic function . Zooming on enzymes involved in glucose and glycerol metabolisms showed that the expression of all glycolytic enzymes was marginally or not affected by the cell growth in glycerol conditions ( ranging from 10% down-regulation to 25% up-regulation ) ( Fig 6C and S3 Table ) . Interestingly , the expression of the gluconeogenic enzyme fructose-1 , 6-bisphosphatase ( FBPase , EC 2 . 7 . 1 . 40 , step 3b ) was unchanged and the glycolytic enzyme performing the reverse reaction , i . e . phosphofructokinase ( PFK , EC 2 . 7 . 1 . 11 , step 3a ) was moderately up-regulated ( 20% ) in CMM_Glyc/GlcNAc-cultured cells . These data confirmed by western blotting ( Fig 6A ) indicated that BSF grown upon glucose-rich conditions maintained the ability to perform gluconeogenesis from glycerol , which favours the hypothesis that parasites could face in vivo conditions requiring gluconeogenesis . The most up-regulated enzymes involved in both glucose and glycerol metabolism were two mitochondrial enzymes involved in the oxidation of glycosomal NADH , i . e . the mitochondrial FAD-dependent glycerol-3-phosphate dehydrogenase ( FAD-GPDH , EC 1 . 1 . 5 . 3 , step 21 ) and the alternative oxidase ( TAO , EC 1 . 10 . 3 , step 25 ) , that were 1 . 5- and 1 . 8-fold up-regulated , respectively ( Fig 6C and S3 Table ) . Up-regulation of the TAO was confirmed by western blotting analysis ( Fig 6A ) , which was in agreement with the increased oxygen consumption from glycerol in cell adapted to CMM_Glyc/GlcNAc as compared to cells grown in glucose-rich conditions ( Fig 4A ) . To further investigate the importance of the GK genes , their expression was down-regulated by RNAi in the 427 90–13 BSF strain . The proliferation of the parental strain and that of the RNAiGK cell line incubated in CMM_Glc were only moderately affected by the tetracycline-induced expression of GK double-stranded RNAs ( RNAiGK . i ) . This was consistent with the relative low amounts of glycerol produced from glucose metabolism in the presence of oxygen in the parental cell line [32] . In contrast , the RNAiGK . i cell line incubated in CMM_Glyc/GlcNAc died after 12 days of induction ( Fig 7A ) . The GK expression in this RNAiGK . i cell line was not detectable any more , neither by western blotting ( Fig 7B ) nor by enzymatic assay ( Fig 7C ) . The direct involvement of the GK in the glycerol metabolism was further quantified by 1H-NMR spectrometry analysis of end products excreted from glycerol metabolism . As expected , the rates of pyruvate , alanine , acetate and succinate excretion from glycerol metabolism were 5 . 9-fold reduced upon tetracycline-induction of the RNAiGK cell line as compared to non-induced cells , while glucose metabolism was not affected ( Fig 4 and S1 Fig ) . It is noteworthy , that glycerol metabolism was not abolished in the RNAiGK . i cell line , although both the GK protein and GK activity were not detectable ( S1 Fig ) . These data were consistent with BSF expressing a large excess of GK , far above the minimal amounts required to maintain the high level of glycerol metabolic flux . Nevertheless , this metabolic flux decrease was sufficient to abolish BSF growth in CMM_Glyc/GlcNAc .
T . brucei BSF are currently considered to strictly depend on glycolysis for their growth and development in their mammalian hosts . Indeed , it is widely accepted that the glucose present in mammalian fluids at relatively high and constant concentrations ( 5 mM ) is the only carbon source used by the parasites for ATP production . It has also previously been reported that BSF can convert glycerol into pyruvate [35–39] , however , the relatively low abundance of glycerol in the bloodstream ( 50–100 μM ) [40 , 41] and the parasite preference for glucose over glycerol ( glucose contributes 4-times more than glycerol to the central metabolism than glycerol when present at equimolar amounts ) , implies that glucose is indeed the main source of ATP for BSF trypanosomes in mammalian fluids . However , the recent descriptions of trypanosomes residing in the skin and adipose tissues raise new fundamental questions about the metabolism of these extravascular trypanosomes . Here , we report for the first time that BSF are able not only to survive but to establish and maintain a long-term proliferation in a minimum medium containing glycerol instead of glucose , which illustrates a greater metabolic flexibility than appreciated so far . The comparison of glucose and glycerol metabolisms by BSF trypanosomes , adapted or not to glycerol conditions , reveals two main metabolic differences . First , parasites consume two times more oxygen per carbon unit consumed when glycerol is the carbon source used . This is consistent with the currently accepted metabolic scheme , since the glycerol phosphate redox shuttle to oxygen has to be performed twice for each glycerol molecule consumed in order to maintain the redox balance within the glycosomes ( Fig 1B ) : to first produce dihydroxyacetone phosphate from the glycerol-derived glycerol 3-phosphate ( step 21 ) and then a second time for the re-oxidation of the glycosomal NADH produced by the glyceraldehyde-3-phosphate dehydrogenase reaction by the glycerol-3-phosphate dehydrogenase ( steps 8 , 6 and 21 ) . In contrast , only a single cycle is required for glucose catabolism to re-oxidize the glycosomal NADH produced by the glyceraldehyde-3-phosphate dehydrogenase reaction ( Fig 1A ) . This also implies that glycerol metabolism is strictly dependent on oxygen , while glycolysis can occur in anaerobiosis , yet with a reduced ATP production rate that does not allow cells to grow [21] . This is illustrated by the 11 . 5-times higher sensitivity to SHAM , a TAO specific inhibitor , of BSF grown in CMM_Glyc/GlcNAc compared to CMM_Glc ( Fig 4B ) . Consequently , TAO specific inhibitors such as derivatives of the lead compound ascofuranone developed for the treatment of sleeping sickness are predicted to be particularly efficient on BSF residing in glycerol-rich environments [29] . The second metabolic difference is the utilisation of gluconeogenesis to produce hexose phosphates in glycerol-rich conditions . The activation of this pathway in the absence of glucose is expected because of the absolute requirement of G6P to feed some essential pathways , such as the production of GPI anchors required for the biosynthesis of the BSF coat composed of a variable surface glycoprotein . Interestingly , the constant expression level of FBPase , the key gluconeogenic enzyme that is yet not used when cells rely on glycolysis , regardless the growth conditions of BSF ( CMM_Glyc/GlcNAc versus CMM_Glc ) and of PCF ( glucose-depleted versus glucose-rich ) ( see Fig 6A ) , suggests that trypanosomes could maintain their gluconeogenic capacity in standard glucose-rich conditions possibly to be prepared for future environments poor or depleted in glucose . It is noteworthy that the simultaneous expression of both an active PFK for glycolysis and an active FBPase for gluconeogenesis in the same glycosomes may generate a cycle leading to depletion of the glycosomal ATP . To prevent this potential futile cycle , the PFK and FBPase activities need to be controlled in BSF , for instance by reciprocal inhibition of the two enzymes by allosteric control and/or by post-translational modification . The absence of glucose in the insect vector midgut between bloodmeals may be the driving force of such an adaptation . However , it cannot be ruled out that FBPase is also required for BSF in a still unknown environmental niche . To our surprise , FBPase is ~8-fold more expressed in BSF compared to PCF ( Fig 6A ) , which further strengthens its important role in BSF , presumably to feed gluconeogenesis . A long-term growth of BSF cells in CMM_Glyc/GlcNAc induces an up- or down-regulation of 2 . 7% of the BSF proteome by at least 2-fold compared to CMM_Glc . This is far lower than the variations observed when comparing procyclic to slender BSF and slender BSF to stumpy BSF , showing 48% and 44% of at least 2-fold changes , respectively [42] . Among these long-term adaptations , glycerol metabolism is stimulated while glucose catabolism is reduced . Indeed , the rate of glycerol consumption , the oxygen consumption from glycerol metabolism and the excretion of end products from glycerol metabolism were increased by 11% ( Fig 2C and 2D , Table 1 ) , 22 . 5% ( Fig 4A ) and 19 . 2% ( Fig 3 ) , respectively , while the glucose consumption , the oxygen consumption from glucose metabolism and the excretion of end products from glucose metabolism were decreased by 15% ( Fig 2C and 2D , Table 1 ) , 8 . 2% ( Fig 4A ) and 17 . 9% ( Fig 3 ) , respectively . Interestingly , the increase of glycerol metabolism is correlated with the 1 . 8- and 1 . 5-fold up-regulation in the mitochondrial TAO and FAD-GPDH expressions , respectively . These enzymes are involved in the maintenance of the glycosomal redox balance through the glycerol phosphate shuttle and the mitochondrial oxidative capacity . This observation strongly suggests that the mitochondrial oxidative capacity is controlling the metabolic flow of the glycerol metabolism . It was previously reported that the expression of TAO can be modulated in response to stimuli and consequently may play a role in controlling the electron flow towards H2O production from O2 . Indeed , BSF trypanosomes showed a ~2-fold increase of TAO expression in response to a continuous stress with ascofuranone , ultimately leading to trypanosome death [43] . Similarly , 12 h of incubation with 2 μM antimycin A or 50 μM H2O2 , induced 1 . 6- and 2 . 1-fold increases of TAO activity , respectively , which was correlated to equivalent increases in TAO expressions [44] . Incidentally , the BSF proliferation in CMM_Glyc/GlcNAc is reduced , as compared to CMM_Glc , probably as a consequence of the limited TAO activity that may be responsible for the suboptimal capacity of oxygen consumption observed when glycerol is the only carbon source available . This reinforces our hypothesis that the mitochondrial oxidative capacity controls the glycerol metabolism . Surprisingly , the first catalytic step of the glycerol metabolism ( GK ) is strongly down-regulated after the cell adaptation to CMM_Glyc/GlcNAc , with 4-fold and 7 . 8-fold reductions of the GK protein and activity , respectively , although the overall glycerol metabolism is concomitantly increased by ~20% . These counterintuitive data suggest that BSF present a large excess of GK activity that is not required to feed the central carbon metabolism from glycerol consumption and that is actually even detrimental to the parasite proliferation in glycerol-rich conditions . Although the reasons for this observed GK down-regulation are currently unknown , one may consider that the possible accumulation of glycerol 3-phosphate , the product of the GK enzymatic reaction , may affect the efficiency of downstream reactions . Indeed , it has previously been reported that incubation of the procyclic trypanosomes with glycerol induced a ~50-fold increase of intracellular amounts of glycerol 3-phosphate as compared to an incubation with glucose; this increase affecting the hexokinase activity [45] . Down-regulation of GK expression in CMM_Glyc/GlcNAc also suggests that BSF grown in glucose-rich conditions require the maintenance of this large excess of GK activity . In anaerobiosis , BSF produce equivalent amounts of pyruvate and glycerol from glucose breakdown and consequently need the GK activity to maintain the glycosomal redox balance required to sustain the glycolytic flow [21] . Interestingly , in vitro and in vivo studies have shown that the glycerol kinase activity considerably reduced the lethal effect of TAO inhibitors , which mimics anaerobiosis [46 , 47] . This highlights the essential role of the GK for BSF during anaerobiosis . However , the relatively high oxygen tension in venous and arterial blood ( pO2 in the range of 40 mmHg and 100 mmHg , respectively ) is ~5-fold higher than the minimal oxygen tension required for the BSF to produced only pyruvate from glucose metabolism , which suggests that the BSF anaerobic pathway appears to be almost completely inoperative in the mammalian intravascular compartment [48] . However , it cannot be ruled out that BSF may encounter lower oxygen levels during their journey in mammalian tissues that would require GK expression for survival . The association between trypanosomes and adipocytes , in mouse adipose tissues [10] as well as in the mouse skin [8] , suggests that this interaction may be beneficial for the parasite by providing specific nutrients differing in nature and/or amounts from those available in the blood circulation . It has been proposed that fatty acids provided by the catabolism of triglycerides that are abundantly present in adipocytes may feed BSF ATP production through ß-oxidation [10] . Alternatively , one may consider that the glycerol also produced from triglyceride or phospholipid breakdown could be used as carbon source by BSF . Indeed , glycerol concentration is 5 to 20-fold higher in the interstitial fluids and adipose tissue than in plasma , as a result of local lipolysis [49 , 50] . In addition , large amounts of glycerol can be produced by adipocytes from glucose and fructose breakdown through lipolysis-independent processes , in especially during hyperglycemia episodes [51 , 52] . Incidentally , T . brucei infection in mice produced a condition resembling type 2 diabetes with decreased peripheral glucose utilization and increased glycemia during the first days of the infection [53 , 54] . Consequently , one may consider that the ability of BSF trypanosomes to efficiently metabolise glycerol may favour the early colonisation of the adipose tissues . This adaptability could also be important for the maintenance of skin-dwelling parasites , possibly in the vicinity of dermal adipocytes [8] , a prominent biological feature of the parasites for their effective transmission to tsetses [9] . Close interactions between pathogens and adipose tissues have already been described in the past [55] . For example , Coxiella burnetti , an obligate intracellular bacterium causing Q-fever , has recently been found inside mice adipocytes , that have consequently been assumed to serve as reservoir during the bacteria latency phase [56] . Incidentally , for its essential cell wall biosynthesis , this bacterium shows a preference for glycerol [57] , which could be provided by adipocytes . Overall , these results strengthen the newly illustrated paradigm that BSF trypanosomes are probably much more well adapted than previously admitted to the glucose-free/glycerol-rich conditions . No glucose-free environment has been described in mammals so far and the interstitial fluids contain glucose in the millimolar range , yet at a lower concentration compared to plasma . However , the high glycerol concentration in tissues as compared to that in plasma , particularly in the adipose tissues , suggests that parasites might encounter in vivo conditions compatible with the use of glycerol as a major carbon source . In addition , the resulting in vivo glycerol gradient between the intra and extravascular compartments would influence the parasite tropism to particular tissues via specific sensing pathways , such as the social motility phenomenon described in procyclic trypanosomes in the tsetse midgut [58] . Although the exact role of glycerol metabolism in BSF trypanosomes in vivo is not understood yet , our data open novel avenues for developing new diagnostic tools and/or treatments based on unexplored molecular targets .
The bloodstream form of T . brucei 427 90–13 ( TetR-HYG T7RNAPOL-NEO ) [59] , a 427 221a line ( MiTat 1 . 2 ) designed for the conditional expression of genes was cultured at 37°C in IMDM ( Iscove's Modified Dulbecco's Medium , Life Technologies ) supplemented with 10% ( v/v ) heat-inactivated fetal calf serum ( FCS ) , 0 . 25 mM ß-mercaptoethanol , 36 mM NaHCO3 , 1 mM hypoxanthine , 0 . 16 mM thymidine , 1 mM sodium pyruvate , 0 . 05 mM bathocuprone and 2 mM L-cysteine [60] . The Creek’s minimal medium ( CMM ) was prepared as described before [25 , 26] without glucose but with the addition of all amino acids at 0 . 1 mM . Cell culture grade ( or high purity ) components were purchased from Sigma-Aldrich . One-milliliter cultures were maintained in 24 wells plates at 37°C with 5% CO2 . Cultures were grown to a maximum density of 3 x 106 cells ml-1 and sub-cultured by 100- or 1 , 000-fold dilution every 2 or 3 days , respectively . Glucose-depleted CMM ( CMM_Glyc/GlcNAc ) was prepared by replacing glucose ( 10 mM ) with 10 mM glycerol and adding 50 mM N-acetyl-D-glucosamine ( GlcNAc ) , a non-metabolised glucose analogue inhibiting glucose transport , to prevent import of FCS-derived glucose ( 0 . 5 mM ) . The procyclic form of T . brucei EATRO1125 . T7T ( TetR-HYG T7RNAPOL-NEO ) was cultivated at 27°C in the presence of 5% CO2 in SDM79 medium containing 10% ( v/v ) heat-inactivated fetal calf serum and 3 . 5 mg ml-1 hemin [61] or in a glucose-depleted medium derived from SDM79 , called SDM79-GlcFree . This SDM79-GlcFree medium consists of a glucose-depleted SDM79 medium , containing 20% ( v/v ) heat-inactivated fetal calf serum , in which parental cells were cultured during 72 hours in order to consume the glucose coming from the serum and then diluted with the same volume of glucose-depleted SDM79 medium without serum to finally obtain SDM79-GlcFree . Glucose depletion was verified by NMR spectrometry analyses ( with a detection threshold ≤ 1μM ) and to prevent import of residual glucose 50 mM GlcNAc were added in the medium . Cell counts were obtained with a Guava EasyCyte Flow Cytometer ( Merck Millipore ) . RNAi-mediated inhibition of expression of the GK genes ( Tb927 . 9 . 12550-Tb927 . 9 . 12630 ) was performed in the 427 90–13 BSF by expression of stem-loop “sense-antisense” RNA molecules of the targeted sequences [62 , 63] using the pLew100 expression vector , that contains the phleomycin resistance gene ( kindly provided by E . Wirtz and G . Cross ) [59] . To do so , a 617-bp fragment of the GK gene ( from position 460 to 1077 ) was introduced in the pLew100 vector to produce the pLew-GK-SAS plasmid . Briefly , a PCR-amplified 617-bp fragment , containing the antisense GK sequence with restriction sites added to the primers , was inserted into the HindIII and BamHI restriction sites of the pLew100 plasmid . The separate 615-bp PCR-amplified fragment containing the sense GK sequence was then inserted upstream of the antisense sequence , using HindIII and XhoI restriction sites ( XhoI was introduced at the 3'-extremity of the antisense PCR fragment ) . The resulting plasmid pLew100-GK-SAS contains a sense and antisense version of the targeted gene fragment , separated by a 89-bp fragment , under the control of a PARP promoter linked to a prokaryotic tetracycline operator . The RNAiGK mutant was generated by transfecting the 427 90–13 parental cell line with the NotI-linearized pLew-GK-SAS plasmid , followed by selection in glucose-rich IMDM medium containing hygromycin ( 5 μg ml-1 ) , neomycin ( 2 . 5 μg ml-1 ) and phleomycin ( 2 . 5 μg ml-1 ) . Aliquots were frozen in liquid nitrogen as soon as possible after clone selection to provide stocks of each line . Induction of RNAi cell lines was performed by addition of 10 μg ml-1 tetracycline . Total protein extracts of T . brucei BSF cell lines harvested at a density of 106 cells ml-1 ( 5 x 106 cells per lane ) were separated by SDS-PAGE ( 10% ) and immunoblotted on TransBlot Turbo Midi-size PVDF Membranes ( Bio-Rad ) [64] . Immunodetection was performed as described [64 , 65] using as primary antibodies , the rabbit anti-GK antibody ( 1:5 , 000 , gift from P . Michels , Edinburgh , UK ) , the rabbit anti-hsp60 antibody ( 1:10 , 000 ) [66] , the rabbit anti-ISG75 antibody ( 1:1 , 000 , gift from P . Overath , Tubingen , Germany ) [67] , the rabbit anti-FBPase antibody ( 1:1 , 000 , gift from P . Michels , Edinburgh , UK ) and the mouse monoclonal anti-TAO antibody ( 7D3 , 1:100 , gift from M . Chaudhuri , Nashville , TN , USA ) [68] . Anti-rabbit or anti-mouse antibodies conjugated to the horseradish peroxidase ( Bio-Rad , 1:5 , 000 dilution ) were used as secondary antibody . Revelation was performed using the Clarity Western ECL Substrate as described by the manufacturer ( Bio-Rad ) . Images were acquired and analysed with the ImageQuant LAS 4000 luminescent image analyser ( GE Healthcare ) . To determine the rate of glucose and glycerol consumption , BSF cells harvested at a density of 106 cells ml-1 were grown in 10 ml of CMM_Glc , CMM_Glyc/GlcNAc or CMM_Glc/Glyc containing 5 mM of glucose and/or 5 mM of glycerol ( inoculated at 2 x 106 cells ml-1 ) . Aliquots of growth medium ( 200 μl ) were collected periodically during the 12 h of incubation at 37°C . The quantity of glucose and glycerol present in the medium was determined using the “Glucose GOD-PAP” kit ( Biolabo SA ) and the “Glycerol assay kit” ( Sigma-Aldrich ) , respectively . The amount of carbon source consumed at a given time of incubation ( Tx ) was calculated by subtracting the remaining amounts in the spent medium at Tx from the initial amounts at T0 . Then , the rate of glucose and glycerol consumed per h and per 108 parasites was calculated from the equation of the linear curve deduced from plotting carbon source consumption as a function of time of incubation . Importantly , we controlled that 100% of the cells remained alive and motile at the end of the 12 h of incubation . For enzymatic activities , BSF cells harvested at a density of 106 cells ml-1 were washed in PBS ( 10 min , RT , 900 g ) , resuspended in assay buffer and after addition of “Complete EDTA-Free” protease-inhibitor cocktail ( Roche ) lysed by sonication ( Bioruptor , Diagenode; high intensity , 5 cycles , 30sec/30sec on/off ) . Debris were spun down ( 1 min , RT , 16 , 000 g ) and the supernatants were used for protein determination with the Pierce protein assay in a FLUOstar Omega plate reader at 660 nm . For higher throughput and smaller assay volumes all activity measurements were performed in a 96-well format with a FLUOstar Optima including an automated injection system . The baseline reactions were measured for 2 min and the reactions were started by injection of the specific substrate ( glucose or glycerol ) for each enzyme . The decrease/increase in absorbance at 350 nm was followed for 3–5 min . The rate was determined from the linear part of the progress curve and from this the specific activity was calculated . The buffer for glycerol kinase determination contains 100 mM triethanolamine pH 7 . 6 , 2 . 5 mM MgSO4 , 10 mM KCl , 0 . 6 mM ATP , 2 mM phosphoenolpyruvate , 0 . 6 mM NADH , ~1U lactate dehydrogenase , ~1U pyruvate kinase and 10 mM of glycerol ( injected substrate ) . The buffer for hexokinase measurements contains 100 mM triethanolamine pH 7 . 6 , 10 mM MgCl2 , 0 . 6 mM ATP , 0 . 6 mM NADP+ , ~1U glucose-6-phosphate dehydrogenase and 10 mM of glucose ( injected substrate ) . A total of 107 cells were collected at the end of the exponential phase growth ( 106 cells ml-1 ) , centrifuged at 800 g for 5 min and resuspended in 2 . 3 ml of CMM_Glc or CMM_Glyc without FCS . Oxygen consumption rate was assessed at 28°C using 107 cells per Oroboros O2K oxygraph chamber . The endogenous respiration of cells incubated in CMM_Glc or CMM_Glyc was recorded during steady state flux over several minutes . The SHAM sensitive respiration was then systematically determined by adding 4 mM SHAM , or from 1 nM to 1mM for EC50 determinations . BSF trypanosomes ( 107 cells , ~0 . 1 mg of protein ) were harvested at a density of 106 cells ml-1 by centrifugation at 1 , 400 g for 10 min , washed once with phosphate-buffered saline ( PBS ) containing 1 mM of the carbon source and incubated for 1 . 5 h at 37°C in 1 ml of incubation buffer ( PBS supplemented with 5 g l-1 NaHCO3 , pH 7 . 4 ) , with [U-13C]-glucose or glucose ( 4 mM ) in the presence or the absence of glycerol ( 4 mM ) . The integrity of the cells during the incubation was checked by microscopic observation . 50 μl of maleate ( 10 mM ) were added as internal reference to a 500 μl aliquot of the collected supernatant and proton NMR ( 1H-NMR ) spectra were performed at 500 . 19MHz on a Bruker Avance III 500 HD spectrometer equipped with a 5 mm cryoprobe Prodigy . Measurements were recorded at 25° . Acquisition conditions were as follows: 90° flip angle , 5 , 000 Hz spectral width , 32 K memory size , and 9 . 3 sec total recycle time . Measurements were performed with 64 scans for a total time close to 10 min 30 sec . Resonances of the obtained spectra were integrated and metabolites concentrations were calculated using the ERETIC2 NMR quantification Bruker program . Two-tailed Student’s t-tests for unpaired samples were performed to analyse the effects of adaptation to CMM_Glyc/GlcNAc on the total excreted products in the 427 90–13 cell line . The comparisons were performed between parasites grown in CMM_Glyc/GlcNAc versus CMM_Glc both incubated with the same carbon sources ( glucose , glycerol or glucose/glycerol ) . Similar statistical analyses were done for the RNAiGK cell line to compare the tetracycline-induced versus non-induced parasites incubated in glucose or glycerol . For analysis of [13C]-incorporation into intracellular metabolites , BSF cells grown in IMDM at a density of 106 cells ml-1 were washed once with PBS containing 0 . 1 mM glycerol and 2 x 107 cells were resuspended in 5 ml incubation solution ( PBS containing 2 mM [U-13C]-glycerol with or without 2 mM glucose ) . The cells were incubated for 1 h at 37°C , then transferred in a 50 ml plastic tube to cool down the medium in a dry ice/ethanol bath ( 20 sec ) , followed by centrifugation at 4°C at 1 , 400 g for 5 min . The cell pellet was then frozen in liquid nitrogen for mass spectrometry analysis , as described before [25 , 26] . The extraction of intracellular metabolites was carried out by adding 2 ml of a cold extraction solution ( acetonitrile/methanol/water , 4:4:2 v/v at -20°C , containing 0 . 1% formic acid v/v ) . The extracts were briefly vortexed ( ~2 sec ) and immediately incubated at -20°C for 20 min . After evaporation , the dried extracts were resuspended in 150 μl ultrapure water and centrifuged to remove cell residues prior to analysis . The analyses of metabolites were carried out on liquid anion exchange chromatography Dionex ICS-5000+ Reagent-Free HPIC ( Thermo Fisher Scientific™ , Sunnyvale , CA , USA ) system coupled to QExactive Plus high resolution mass spectrometer ( Thermo Fisher Scientific , Waltham , MA ) . Central metabolites were separated within 48 min , using linear gradient elution of KOH applied to an IonPac AS11 column ( 250 x 2 mm , Dionex ) equipped with an AG11 guard column ( 50 x 2 mm , Dionex ) at a flow rate of 0 . 35 ml min-1 . The column and autosampler temperature were 30°C and 4°C respectively . Injected sample volume was 15 μl . Mass detection was carried out in a negative electrospray ionization ( ESI ) mode . The settings of the mass spectrometer were as follows: spray voltage 2 . 75 kV , capillary and desolvatation temperature were 325°C and 380°C respectively , maximum injection time 100 ms . Nitrogen was used as sheath gas ( pressure 50 units ) and auxiliary gas ( pressure 5 units ) . The automatic gain control ( AGC ) was set at 1e6 for full scan mode with a mass resolution of 140 , 000 . Identification of 13C carbon isotopologue distribution relied upon matching accurate masses from FTMS ( mass tolerance of 5 ppm ) and retention time using TraceFinder 3 . 2 software . Measurement of alanine 13C incorporation was performed following the method described in Heuillet et al . [69] To obtain 13C-labelling patterns ( 13C isotopologues ) , isotopic clusters were corrected for the natural abundance of isotopes of all elements and for isotopic purity of the tracer , using the in-house software IsoCor ( available at MetaSys ) [70] . The metabolites under examination included alanine , fructose 1 , 6-bisphosphate ( F1 , 6BP ) , fructose 6-phosphate ( F6P ) , fumarate , glucose 6-phosphate ( G6P ) , glycerol 3-phosphate ( Gly3P ) , malate , mannose 6-phosphate ( M6P ) , phosphoenolpyruvate ( PEP ) , 6-phosphogluconate ( 6-PG ) , 2- and 3-phosphoglycerate ( 2/3PG ) , ribose 5-phosphate , ribulose 5-phosphate , xylulose 5-phosphate ( considered together as pentose 5-phosphate , Pentose5P ) and succinate . This analysis was performed by the proteomics core facility at University of Bordeaux ( https://proteome . cgfb . u-bordeaux . fr/en ) . The steps of sample preparation and protein digestion were performed as previously described [71] . Online nanoLC-MS/MS analyses were performed using an Ultimate 3000 RSLC Nano-UPHLC system ( Thermo Scientific , USA ) coupled to a nanospray Q Exactive hybrid quadrupole-Orbitrap mass spectrometer ( Thermo Scientific , USA ) . 500 ng of each peptide extract was loaded on a 300 μm ID x 5 mm PepMap C18 precolumn ( Thermo Scientific , USA ) at a flow rate of 10 μl min-1 . After a 3 min desalting step , peptides were separated on a 75 μm ID x 25 cm C18 Acclaim PepMap RSLC column ( Thermo Scientific , USA ) with a 4–40% linear gradient of solvent B ( 0 . 1% formic acid in 80% ACN ) in 108 min . The separation flow rate was set at 300 nl min-1 . The mass spectrometer operated in positive ion mode at a 1 . 8 kV needle voltage . Data was acquired using Xcalibur 3 . 1 software in a data-dependent mode . MS scans ( m/z 300–1600 ) were recorded at a resolution of R = 70 , 000 ( m/z 200 ) and an AGC target of 3 × 106 ions collected within 100 ms . Dynamic exclusion was set to 30 s and top 12 ions were selected from fragmentation in HCD mode . MS/MS scans with a target value of 105 ions were collected with a maximum fill time of 100 ms and a resolution of R = 17 , 500 . Additionally , only +2 and +3 charged ions were selected for fragmentation . Other settings were as follows: no sheath and no auxiliary gas flow , heated capillary temperature , 200°C; normalized HCD collision energy of 27 eV and an isolation width of 2 m/z . For protein identification , Sequest HT and Mascot 2 . 4 algorithms through Proteome Discoverer 1 . 4 Software ( Thermo Fisher Scientific Inc . ) were used for protein identification in batch mode by searching against a T . brucei protein database ( 9 , 594 entries , TriTrypDB-33_TbruceiTREU927 , release 33 ) . This database was downloaded from http://tritrypdb . org website . Two missed enzyme cleavages were allowed . Mass tolerances in MS and MS/MS were set to 10 ppm and 0 . 02 Da . Oxidation of methionine , acetylation of lysine and deamidation of asparagine and glutamine were searched as dynamic modifications . Carbamidomethylation on cysteine was searched as static modification . Peptide validation was performed using Percolator algorithm and only “high confidence” peptides were retained corresponding to a 1% False Discovery Rate ( FDR ) at peptide level [72] . Raw LC-MS/MS data were imported in Progenesis QI ( version 2 . 0; Nonlinear Dynamics , a Waters Company ) for feature detection , alignment , and quantification . All sample features were aligned according to retention times by manually inserting up to fifty landmarks followed by automatic alignment to maximally overlay all the two-dimensional ( m/z and retention time ) feature maps . Singly charged ions and ions with higher charge states than six were excluded from analysis . All remaining features were used to calculate a normalization factor for each sample that corrects for experimental variation . Peptide identifications ( with FDR<1% ) were imported into Progenesis . Only non-conflicting features and unique peptides were considered for calculation of quantification at protein level . A minimum of three peptides matched to a protein was used as the criteria for identification as a differentially expressed protein . Univariate one-way analysis of variance ( ANOVA ) was performed within Progenesis to calculate the protein p-value according to the sum of the normalized abundances across all runs . Only protein with a p-value cutoffs ≤ 0 . 05 were validated . The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [73] partner repository with the dataset identifier PXD009763 .
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Until very recently , the bloodstream forms ( BSF ) of the Trypanosoma brucei group species have been considered to propagate exclusively in the mammalian fluids , including the blood , the lymphatic network and the cerebrospinal fluid . All these fluids are rich in glucose , which is widely considered by the scientific community as the only carbon source used by the parasite to feed its central carbon metabolism and its ATP production . Here , we show for the first time that the BSF trypanosomes efficiently grow in glucose-free conditions as long as glycerol is supplied . The raison d'être of this capacity developed by BSF trypanosomes to grow in glycerol-rich conditions regardless of the glucose concentration , including in glucose-free conditions , is not yet understood . However , the recent discovery that trypanosomes colonize and proliferate in the skin and the adipose tissues of their mammalian hosts may provide a rational explanation for the development of a glycerol-based metabolism in BSF . Indeed , the adipocytes composing adipose tissues and also abundantly present in subcutaneous layers excrete large amounts of glycerol produced from the catabolism of glucose and triglycerides . We also show that BSF trypanosomes adapted to glucose-depleted conditions activate gluconeogenesis to produce the essential hexose phosphates from glycerol metabolism . Interestingly , the constitutive expression of the key gluconeogenic enzyme fructose-1 , 6-bisphosphatase , which is not used for glycolysis , suggests that BSF trypanosomes maintained in the standard glucose-rich medium are pre-adapted to glucose-depleted conditions . This further strengthens the new paradigm that BSF trypanosomes can use glycerol in tissues producing this carbon source , such as the skin the adipose tissues .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"methods"
] |
[
"cell",
"physiology",
"carbohydrate",
"metabolism",
"chemical",
"compounds",
"monomers",
"phosphates",
"enzymology",
"carbohydrates",
"glucose",
"metabolism",
"organic",
"compounds",
"parasitic",
"protozoans",
"glucose",
"cell",
"metabolism",
"oxygen",
"metabolism",
"protozoans",
"enzyme",
"metabolism",
"enzyme",
"chemistry",
"polymer",
"chemistry",
"chemistry",
"biochemistry",
"trypanosoma",
"eukaryota",
"organic",
"chemistry",
"cell",
"biology",
"glycerol",
"monosaccharides",
"biology",
"and",
"life",
"sciences",
"physical",
"sciences",
"metabolism",
"organisms"
] |
2018
|
Glycerol supports growth of the Trypanosoma brucei bloodstream forms in the absence of glucose: Analysis of metabolic adaptations on glycerol-rich conditions
|
Metabolic reactions of single-cell organisms are routinely observed to become dispensable or even incapable of carrying activity under certain circumstances . Yet , the mechanisms as well as the range of conditions and phenotypes associated with this behavior remain very poorly understood . Here we predict computationally and analytically that any organism evolving to maximize growth rate , ATP production , or any other linear function of metabolic fluxes tends to significantly reduce the number of active metabolic reactions compared to typical nonoptimal states . The reduced number appears to be constant across the microbial species studied and just slightly larger than the minimum number required for the organism to grow at all . We show that this massive spontaneous reaction silencing is triggered by the irreversibility of a large fraction of the metabolic reactions and propagates through the network as a cascade of inactivity . Our results help explain existing experimental data on intracellular flux measurements and the usage of latent pathways , shedding new light on microbial evolution , robustness , and versatility for the execution of specific biochemical tasks . In particular , the identification of optimal reaction activity provides rigorous ground for an intriguing knockout-based method recently proposed for the synthetic recovery of metabolic function .
A fundamental problem in systems biology is to understand how living cells adjust the usage pattern of their components to respond and adapt to specific genetic , epigenetic , and environmental conditions . In complex metabolic networks of single-cell organisms , there is mounting evidence in the experimental [1]–[6] and modeling [7]–[14] literature that a surprisingly small part of the network can carry all metabolic functions required for growth in a given environment , whereas the remaining part is potentially necessary only under alternative conditions [15] . The mechanisms governing this behavior are clearly important for understanding systemic properties of cellular metabolism , such as mutational robustness , but have not received full attention . This is partly because current modeling approaches are mainly focused on predicting whole-cell phenotypic characteristics without resolving the underlying biochemical activity . These approaches are typically based on optimization principles , and hence , by their nature , do not capture processes involving non-optimal states , such as the temporary activation of latent pathways during adaptive evolution towards an optimal state [16] , [17] . To provide mechanistic insight into such behaviors , here we study the metabolic system of single-cell organisms under optimal and non-optimal conditions in terms of the number of active reactions ( those that are actually used ) . We implement our study within a flux balance-based framework [18]–[23] . Figure 1 illustrates key aspects of our analysis using the example of Escherichia coli . For any typical non-optimal state ( Figure 1B ) , all the reactions in the metabolic network are active , except for those that are necessarily inactive due either to mass balance constraints or environmental conditions ( e . g . , nutrient limitation ) . In contrast , a large number of additional reactions are predicted to become inactive for any metabolic flux distribution maximizing the growth rate ( Figure 1A ) . This spontaneous reaction silencing effect , in which optimization causes massive reaction inactivation , is observed in all four organisms analyzed in this study , H . pylori , S . aureus , E . coli , and S . cerevisiae , which have genomes and metabolic networks of increasing size and complexity ( Materials and Methods ) . Our analysis reveals two mechanisms responsible for this effect: ( 1 ) irreversibility of a large number of reactions , which under intracellular physiological conditions [14] is shared by more than 62% of all metabolic reactions in the organisms we analyze ( Table 1 and Note 1 ) ; and ( 2 ) cascade of inactivity triggered by the irreversibility , which propagates through the metabolic network due to stoichiometric and flux balance constraints . We provide experimental evidence of this phenomenon and explore applications to data interpretation by analyzing intracellular flux and gene activity data available in the literature . The drastic difference between optimal and non-optimal behavior is a general phenomenon that we predict not only for the maximization of growth , but also for the optimization of any typical objective function that is linear in metabolic fluxes , such as the production rate of a metabolic compound . Interestingly , we find that the resulting number of active reactions in optimal states is fairly constant across the four organisms analyzed , despite the significant differences in their biochemistry and in the number of available reactions . In glucose media , this number is ∼300 and approaches the minimum required for growth , indicating that optimization tends to drive the metabolism surprisingly close to the onset of cellular growth . This reduced number of active reactions is approximately the same for any typical objective function under the same growth conditions . We suggest that these findings will have implications for the targeted improvement of cellular properties [24] . Recent work predicts that the knockout of specific enzyme-coding genes can enhance metabolic performance and even rescue otherwise nonviable strains [25] . The possibility of such knockouts bears on the issue of whether the inactivation of the corresponding enzyme-catalyzed reactions would bring the whole-cell metabolic state close to the target objective . Thus , our identification of a cascading mechanism for inducing optimal reaction activity for arbitrary objective functions provides a natural set of candidate genetic interventions for the knockout-based enhancement of metabolic function [25] .
We model cellular metabolism as a network of metabolites connected through reaction and transport fluxes . The state of the system is represented by the vector v = ( v1 , … , vN ) T of these fluxes , including the fluxes of n internal and transport reactions , as well as nex exchange fluxes for modeling media conditions . Under the constraints imposed by stoichiometry , reaction irreversibility , substrate availability , and the assumption of steady-state conditions , the state of the system is restricted to a feasible solution space ( Materials and Methods ) . Within this framework , we first consider the number of active reactions in a typical non-optimal state v∈M . We can prove that , with the exception of the reactions that are inactive for all v∈M , all the metabolic reactions are active for almost all v∈M , i . e . , for any typical state chosen randomly from M ( Text S1 , Section 1 ) . Accordingly , the number n+ ( v ) of active reactions in a typical non-optimal state is constant , i . e . , ( 1 ) The reactions that are inactive for all states are so either due to mass balance or environmental conditions , and can be identified numerically using flux coupling [26] and flux variability analysis [9] . We now turn to the maximization of growth rate , which is often hypothesized in flux balance-based approaches and found to be consistent with observation in adaptive evolution experiments [31]–[34] . Performing numerical optimization in glucose minimal media ( Materials and Methods ) , we find that the number of active reactions in such optimal states is reduced by 21%–50% compared to typical non-optimal states , as indicated in the middle bars of Figure 2 . Interestingly , the absolute number of active reactions under maximum growth is ∼300 and appears to be fairly independent of the organism and network size for the cases analyzed . We observe that the minimum number of reactions required merely to sustain positive growth [7] , [8] is only a few reactions smaller than the number of reactions used in growth-maximizing states ( bottom bars , Figure 2 ) . This implies that surprisingly small metabolic adjustment or genetic modification is sufficient for an optimally growing organism to stop growing completely , which reveals a robust-yet-subtle tendency in cellular metabolism: while the large number of inactive reactions offers tremendous mutational and environmental robustness[52] , the system is very sensitive if limited only to the set of reactions optimally active . The flip side of this prediction is that significant increase in growth can result from very few mutations , as observed recently in adaptive evolution experiments [35] . We now turn to mechanisms underlying the observed reaction silencing , which is spread over a wide range of metabolic subsystems ( see Figure 1 for E . coli ) . The phenomenon is caused by growth maximization via reaction irreversibility and cascading of inactivity . Although we have focused so far on maximizing the biomass production rate , the true nature of the fitness function driving evolution is far from clear [44]–[47] . Organisms under different conditions may optimize different objective functions , such as ATP production or nutrient uptake , or not optimize a simple function at all . In particular , some metabolic behaviors , such as the selection between respiration and fermentation in yeast , cannot be explained by growth maximization [48] . Other behaviors may be systematically different in situations mimicking natural environments [49] . Moreover , various alternative target objectives can be conceived and used in metabolic engineering applications . We emphasize , however , that while specific numbers may differ in each case , all the arguments leading to Eqs . ( 2 ) – ( 4 ) are general and apply to any objective function that is linear in metabolic fluxes . To obtain further insights , we now study the number of active reactions in organisms optimizing a typical linear objective function by means of random uniform sampling . We first note the fact ( proved in Text S1 , Section 4 ) that with probability one under uniform sampling , the optimal solution set Mopt consists of a single point , which must be a “corner” of M , termed an extreme point in the linear programming literature . In this case , dopt = 0 , and Eq . ( 2 ) becomes ( 5 ) With the additional requirement that the organism show positive growth , we uniformly sample these extreme points , which represent all distinct optimal states for typical linear objective functions . We find that the number of active reactions in typical optimal states is narrowly distributed around that in growth-maximizing states , as shown in Figure 4 . This implies that various results on growth maximization extend to the optimization of typical objective functions . In particular , we see that a typical optimal state is surprisingly close to the onset of cellular growth ( estimated and shown as dashed vertical lines in Figure 4 ) . Despite the closeness , however , the organism maintains high versatility , which we define as the number of distinct functions that can be optimized under growth conditions . To demonstrate this , consider the H . pylori model , which has 392 reactions that can be active , among which at least 302 must be active to sustain growth ( Table 3 ) . While only a few more than 302 active reactions are sufficient to optimize any objective function , the number of combinations for choosing them can be quite large . For example , there are combinations for choosing , say , 5 extra reactions to be active . Moreover , this number increases quickly with the network size: S . cerevisiae , for example , has less than 2 . 5 times more reactions than H . pylori , but about 500 times more combinations ( ) . Our results help explain previous experimental observations . Analyzing the 22 intracellular fluxes determined by Schmidt et al . [50] for the central metabolism of E . coli in both aerobic and anaerobic conditions , we find that about 45% of the fluxes are smaller than 10% of the glucose uptake rate ( Table 4 ) . However , less than 19% of the reversible fluxes and more than 60% of the irreversible fluxes are found to be in this group ( Fisher exact test , one-sided p<0 . 008 ) . For the 44 fluxes in the S . cerevisiae metabolism experimentally measured by Daran-Lapujade et al . [51] , less than 8% of the reversible fluxes and more than 42% of the irreversible fluxes are zero ( Table 5; Fisher exact test , one-sided p<10−7 ) . This higher probability for reduced fluxes in irreversible reactions is consistent with our theory and simulation results ( Table 6 ) combined with the assumption that the system operates close to an optimal state . For the E . coli data , this assumption is justified by the work of Burgard & Maranas [44] , where a framework for inferring metabolic objective functions was used to show that the organisms are mainly ( but not completely ) driven by the maximization of biomass production . The S . cerevisiae data was also found to be consistent with the fluxes computed under the assumption of maximum growth [52] . Additional evidence for our results is derived from the inspection of 18 intracellular fluxes experimentally determined by Emmerling et al . [53] for both wild-type E . coli and a gene-deficient strain not exposed to adaptive evolution . It has been shown [21] that while the wild-type fluxes can be approximately described by the optimization of biomass production , the genetically perturbed strain operates sub-optimally . We consider the fluxes that are more than 10% ( of the glucose uptake rate ) larger in the gene-deficient mutant than in the wild-type strain . This group comprises less than 27% of the reversible fluxes but more than 45% of the irreversible fluxes ( Table 7; Fisher exact test , one-sided p<0 . 12 ) . This correlation indicates that irreversible fluxes tend to be larger in non-optimal metabolic states , consistently with our predictions . Altogether , our results offer an explanation for the temporary activation of latent pathways observed in adaptive evolution experiments after environmental [16] or genetic perturbations [17] . These initially inactive pathways are transiently activated after a perturbation , but subsequently inactivated again after adaptive evolution . We hypothesize that transient suboptimal states are the leading cause of latent pathway activation . Since we predict that a large number of reactions are inactive in optimal states but active in typical non-optimal states , many reactions are expected to show temporary activation if we assume that the state following the perturbation is suboptimal and both the pre-perturbation and post-adaptation states are near optimality . To demonstrate this computationally for the E . coli model , we consider the idealized scenario where the perturbation to the growth-maximizing wild type is caused by a reaction knockout and the initial response of the metabolic network—before the perturbed strain evolves to a new growth-maximizing state—is well approximated by the method of minimization of metabolic adjustment ( MOMA ) [21] . MOMA assumes that the perturbed organisms minimize the square-sum deviation of its flux distribution from the wild-type distribution ( under the constraints imposed by the perturbation ) . Figure 5A shows the distribution of the number of active reactions for single-reaction knockouts that alter the flux distribution but allow positive MOMA-predicted growth . While the distribution is spread around 400–500 for the suboptimal states in the initial response , it is sharply peaked around 300 for the optimal states at the endpoint of the evolution , which is consistent with our results on random sampling of the extreme points ( Figure 4 ) . We thus predict that the initial number of active reactions for the unperturbed wild-type strain ( which is 297 , as shown by a dashed vertical line in Figure 5A ) typically increases to more than 400 following the perturbation , and then decays back to a number close to 300 after adaptive evolution in the given environment , as illustrated schematically in Figure 5B . A neat implication of our analysis is that the active reactions in the early post-perturbation state includes much more than just a superposition of the reactions that are active in the pre- and post-perturbation optimal states , thus explaining the pronounced burst in gene expression changes observed to accompany media changes and gene knockouts [16] , [17] . For example , for E . coli in glucose minimal medium , temporary activation is predicted for the Entner-Doudoroff pathway after pgi knockout and for the glyoxylate bypass after tpi knockout , in agreement with recent flux measurements in adaptive evolution experiments [17] . Another potential application of our results is to explain previous experimental evidence that antagonistic pleiotropy is important in adaptive evolution [54] , as they indicate that increasing fitness in a single environment requires inactivation of many reactions through regulation and mutation of associated genes , which is likely to cause a decrease of fitness in some other environments [15] .
All the stoichiometric data for the in silico metabolic systems used in our study are available at http://gcrg . ucsd . edu/In_Silico_Organisms . For H . pylori 26695 [77] , we used a medium with unlimited amount of water and protons , and limited amount of oxygen ( 5 mmol/g DW-h ) , L-alanine , D-alanine , L-arginine , L-histidine , L-isoleucine , L-leucine , L-methionine , L-valine , glucose , Iron ( II and III ) , phosphate , sulfate , pimelate , and thiamine ( 20 mmol/g DW-h ) . For S . aureus N315 [78] , we used a medium with limited amount of glucose , L-arginine , cytosine , and nicotinate ( 100 mmol/g DW-h ) , and unlimited amount of iron ( II ) , protons , water , oxygen , phospate , sulfate , and thiamin . For E . coli K12 MG1655 [75] , we used a medium with limited amount of glucose ( 10 mmol/g DW-h ) and oxygen ( 20 mmol/g DW-h ) , and unlimited amount of carbon dioxide , iron ( II ) , protons , water , potassium , sodium , ammonia , phospate , and sulfate . For S . cerevisiae S288C [76] , we used a medium with limited amount of glucose ( 10 mmol/g DW-h ) , oxygen ( 20 mmol/g DW-h ) , and ammonia ( 100 mmol/g DW-h ) , and unlimited amount of water , protons , phosphate , carbon dioxide , potassium , and sulfate . The flux through the ATP maintenance reaction was set to 7 . 6 mmol/g DW-h for E . coli and 1 mmol/g DW-h for S . aureus and S . cerevisiae . Under steady-state conditions , a cellular metabolic state is represented by a solution of a homogeneous linear equation describing the mass balance condition , ( 6 ) where S is the m×N stoichiometric matrix and is the vector of metabolic fluxes . The components of v = ( v1 , … , vN ) T include the fluxes of n internal and transport reactions as well as nex exchange fluxes , which model the transport of metabolites across the system boundary . Constraints of the form vi≤βi imposed on the exchange fluxes are used to define the maximum uptake rates of substrates in the medium . Additional constraints of the form vi≥0 arise for the reactions that are irreversible . Assuming that the cell's operation is mainly limited by the availability of substrates in the medium , we impose no other constraints on the internal reaction fluxes , except for the ATP maintenance flux for S . aureus , E . coli , and S . cerevisiae ( see Strains and media section above ) . The set of all flux vectors v satisfying the above constraints defines the feasible solution space , representing the capability of the metabolic network as a system . The flux balance analysis ( FBA ) [18]–[20] , [22] , [23] used in this study is based on the maximization of a metabolic objective function cTv within the feasible solution space M , which is formulated as a linear programming problem: ( 7 ) We set αi = −∞ if vi is unbounded below and βi = ∞ if vi is unbounded above . For a given objective function , we numerically determine an optimal flux distribution for this problem using an implementation of the simplex method [43] . In the particular case of growth maximization , the objective vector c is taken to be parallel to the biomass flux , which is modeled as an effective reaction that converts metabolites into biomass . To find a set of reactions from which none can be removed without forcing zero growth , we start with the set of all reactions and recursively reduce it until no further reduction is possible . At each recursive step , we first compute how much the maximum growth rate would be reduced if each reaction were removed from the set individually . Then , we choose a reaction that causes the least change in the maximum growth rate , and remove it from the set . We repeat this step until the maximum growth rate becomes zero . The set of reactions we have just before we remove the last reaction is a desired minimal reaction set . Note that , since the algorithm is not exhaustive , the number of reactions in this set is an upper bound and approximation for the minimum number of reactions required to sustain positive growth .
|
Cellular growth and other integrated metabolic functions are manifestations of the coordinated interconversion of a large number of chemical compounds . But what is the relation between such whole-cell behaviors and the activity pattern of the individual biochemical reactions ? In this study , we have used flux balance-based methods and reconstructed networks of Helicobacter pylori , Staphylococcus aureus , Escherichia coli , and Saccharomyces cerevisiae to show that a cell seeking to optimize a metabolic objective , such as growth , has a tendency to spontaneously inactivate a significant number of its metabolic reactions , while all such reactions are recruited for use in typical suboptimal states . The mechanisms governing this behavior not only provide insights into why numerous genes can often be disabled without affecting optimal growth but also lay a foundation for the recently proposed synthetic rescue of metabolic function in which the performance of suboptimally operating cells can be enhanced by disabling specific metabolic reactions . Our findings also offer explanation for another experimentally observed behavior , in which some inactive reactions are temporarily activated following a genetic or environmental perturbation . The latter is of utmost importance given that nonoptimal and transient metabolic behaviors are arguably common in natural environments .
|
[
"Abstract",
"Introduction",
"Results",
"Materials",
"and",
"Methods"
] |
[
"computational",
"biology/metabolic",
"networks",
"computational",
"biology/systems",
"biology"
] |
2008
|
Spontaneous Reaction Silencing in Metabolic Optimization
|
There is a paucity of robust epidemiological data on snakebite , and data available from hospitals and localized or time-limited surveys have major limitations . No study has investigated the incidence of snakebite across a whole country . We undertook a community-based national survey and model based geostatistics to determine incidence , envenoming , mortality and geographical pattern of snakebite in Sri Lanka . The survey was designed to sample a population distributed equally among the nine provinces of the country . The number of data collection clusters was divided among districts in proportion to their population . Within districts clusters were randomly selected . Population based incidence of snakebite and significant envenoming were estimated . Model-based geostatistics was used to develop snakebite risk maps for Sri Lanka . 1118 of the total of 14022 GN divisions with a population of 165665 ( 0 . 8%of the country’s population ) were surveyed . The crude overall community incidence of snakebite , envenoming and mortality were 398 ( 95% CI: 356–441 ) , 151 ( 130–173 ) and 2 . 3 ( 0 . 2–4 . 4 ) per 100000 population , respectively . Risk maps showed wide variation in incidence within the country , and snakebite hotspots and cold spots were determined by considering the probability of exceeding the national incidence . This study provides community based incidence rates of snakebite and envenoming for Sri Lanka . The within-country spatial variation of bites can inform healthcare decision making and highlights the limitations associated with estimates of incidence from hospital data or localized surveys . Our methods are replicable , and these models can be adapted to other geographic regions after re-estimating spatial covariance parameters for the particular region .
Bites of venomous snakes cause significant morbidity and mortality in the rural tropics . Despite this , snakebite did not , until very recently , receive the attention it deserves as an important public health problem . The main reason for this was the paucity of robust epidemiological data on the disease burden associated with snakebite . The most recent estimates of the global burden of snakebite highlighted the need for good quality data on snakebite , particularly from nation-wide population-based studies [1] . The paucity of reliable data is partly related to inherent methodological difficulties , which include: poorly developed reporting and recording systems in countries with the highest burden , limitations in hospital-based data that often under-estimate the problem [2][3][4][5] , and seasonal and geographical variation in bite incidence [6][7] , all of which make extrapolations unreliable . Sound epidemiological data are , however , important to both give credence to the magnitude of the problem and raise awareness of snakebite as an important but neglected public health issue , and to assist prioritization of resources for prevention and treatment . Sri Lanka has a mean elevation of 228 meters and consists of mainly low flat to rolling plains with mountains in the south central interior which reach 2400 meters . The country is divided into three climatic zones based on rainfall: wet ( south western and central parts of the country including the Western , Central and Sabaragamuwa provinces ) ; dry ( northern and south eastern parts of the country including the Northern , Northcentral , Eastern and parts of the Southern and Uva provinces ) ; and intermediate ( the areas in between the wet and dry zones including the Northwestern , and parts of Uva and Southern provinces ) [8][9] . The differences in rainfall have led to much diversity in the flora and fauna , and in land use in these zones , leading to differences in snakebite patterns [1] . Despite being a country where snakebite results in over 30000 hospital admissions annually [10] , the community incidence of snakebite in Sri Lanka is unknown . Previous research has shown that hospital data underestimate deaths due to snakebites by over 50% [4] , and multiple hospital admissions at different levels of care can further distort hospital statistics . Geostatistical modeling provides a method to estimate continuous spatial variation in incidence from community level surveys through modeling the occurrence of spatially correlated events in order to predict the probability or likelihood of occurrence of an event anywhere in the study-region and to identify risk-factors [11][12] . The resulting risk maps can provide useful information for healthcare decision making in resource limited settings; they include the majority of the most snakebite endemic regions , without the need for comprehensive registry data . The aims of this study were to determine the community incidence , rate of envenoming , mortality and geographical pattern of snakebite in Sri Lanka and to develop a snakebite risk map for Sri Lanka based on geo-spatial and socio-demographic predictive factors .
Ethical approval for the study was given by the Ethics Review Committee of the Faculty of Medicine , University of Kelaniya . Data collection was done by using an interviewer administered questionnaire and all interviews were conducted after obtaining informed written consent . No animals were used in the study . Permission for conducting the study was obtained from District and Divisional level public administrators before data collection . Grama Niladharis of the sampled GN divisions were informed about the study through the public administration system .
Data relating to 165665 individuals ( 0 . 8% of the population of Sri Lanka ) living in 44136 households in 1118 clusters were collected ( Fig 1 ) . 695 snakebites , 323 envenomings and 5 deaths ( four of them male ) were reported in the sample population in the 12 months preceding the interview . The incidence of snakebites , envenoming and deaths in the complete sample population was 398 ( 95% CI 356–441 ) , 151 ( 95% CI 130–173 ) and 2 . 3 ( 95% CI 0 . 2–4 . 4 ) per 100000 population respectively . Extrapolating this to the population of the whole country , the estimated national numbers of snakebites , envenoming and deaths were 80514 ( 95% CI 71774–89254 ) , 30543 ( 95% CI 26203–34883 ) and 464 ( 95% CI 45–884 ) respectively . There was wide geographical variation in incidence within the country: the Northcentral province ( rural , agricultural , dry region ) had the highest incidence rate of 623 snakebites per 100000 and the Central province ( which includes the high altitude areas of the country ) the lowest incidence rate of 277 per 100000 ( Table 1 ) . The differences were more marked for envenoming . The Northcentral province had the highest envenoming rate of 440 per 100000 and the Central province the lowest rate of 92 per 100000 ( Table 1 ) . The proportion of snakebite victims who were envenomed varied from 20% in Western province to 70% in Northern and Northcentral province . Incidence rates of snakebite and envenoming among males were 478 ( 95% CI: 415–541 ) and 176 ( 95% CI: 146–207 ) per 100000 population . Males were approximately 1 . 5 times more likely to experience both snakebites and envenoming than females ( Table 2 ) . Median age ( interquartile range ) of snakebite victims was 42 ( 31–54 ) years and for victims with envenoming bites was 42 ( 30–53 ) . Almost 40% of the snakebites occurred between 4 pm and 8 pm . Snakebite was rarest in the early morning ( 4 am to 8 am ) . More than 55% of the male victims were involved in labour-intensive outdoor occupations such as farming and manual labour . The commonest clinical feature recalled by the snakebite victims was swelling . Symptoms representing neurotoxicity were reported in 28% of all bites . 37% of the significantly envenomed reported neurotoxic features without bleeding . Bleeding manifestations alone were reported by 8% . Neurotoxicity and bleeding together were reported by 24% ( Table 3 ) . Exploratory analysis for snakebite incidence using generalized linear models , ignoring spatial dependence , showed population density , elevation , occupation distribution and climatic zones to be significantly associated with incidence , with non-linear effects of elevation and occupation distribution . Elevation , population density and climatic zone were significantly associated with envenoming incidence with a non-linear effect of elevation ( S1 Appendix ) . According to the geostatistical model , the median predicted incidence for Sri Lanka was 397 per 100000 ( IQR: 295 to 515 per 100 000 ) which is similar to the estimated national snakebite incidence derived from the survey . The fitted geostatistical model for snakebite incidence is summarised in table 4 . There was a positive association between elevation and incidence up to 160 meters above sea level , with incidence dropping thereafter . Intermediate and wet climatic zones had higher snakebite incidence compared to the dry zone . Snakebite incidence decreased with increasing population density . Snakebite incidence rapidly increased as the proportion of the population engaged in agriculture increased up to 9% , with a more gradual increase thereafter . Table 5 shows the results of the geostatistical model for the incidence of envenoming . There was a positive association with elevation up to 195 meters above sea level , with incidence dropping at higher elevations . The incidence of envenoming was higher in the dry zone compared to intermediate and wet climatic zones and decreased with increasing population density . Estimated snakebite incidence and envenoming incidence maps for the whole of Sri Lanka are shown in Fig 2 ( A ) and 2 ( B ) respectively . The three estimated incidence maps shown in Fig 3 include contours demarcating incidence higher than the national snakebite incidence rate ( Incidence>398 per 100000 ) and approximately +/- 100 per 100000 from the national incidence rate for snakebites ( i . e . incidence 300 per 100000 and 500 per 100000 ) . Corresponding PCMs based on exceedance probabilities of 300 per 100000 , 398 per 100000 ( i . e . national rate ) and 500 per 100000 are shown in Fig 4 . The green areas of Fig 4 ( A ) indicate low probability areas for snakebites ( cold spots ) ; in this region the probability of observing a snakebite incidence more than 300 per 100000 is less than 0 . 3 . The red islands of Fig 4 ( C ) show the high probability areas for snakebites ( hot spots ) , where the probability of having a snakebite incidence more than 500 per 100000 is greater than 0 . 7 . The estimated envenoming incidence maps are shown in Fig 5; contours are drawn to demarcate the national rate ( 151 per 100000 ) , 50 per 100000 lower than the national rate and 100 per 100000 higher than the national rate . PCMs for exceedance thresholds of 100 per 100000 , 151 per 100000 ( i . e . national rate ) and 250 per 100000 are shown in Fig 6 ( A ) , 6 ( B ) and 6 ( C ) respectively . The green areas of Fig 6 ( A ) indicate low probability areas for envenoming ( cold spots ) , in this region; the probability of observing a snakebite incidence more than 100 per 100000 is less than 0 . 3 . The red islands of Fig 6 ( C ) shows the high probability areas for snakebites ( hot spots ) ; the probability of having a snakebite incidence more than 250 per 100 000 is more than 0 . 7 .
In a nation-wide community-based survey on snakebite we estimated there to be over 80000 bites , 30000 envenomings and 400 deaths per year in Sri Lanka . Our results are supported by a comprehensive methodology that included a representative , large , population-based sample and associated estimation techniques , and represents the most comprehensive survey of snakebite that has ever been undertaken in any country . Previous studies have attempted to estimate the national incidence of snakebite using hospital-based or local or regional ( sub-national ) data as highlighted in our estimate of the global burden of snakebite [1] . Such approaches are fraught with inaccuracies as hospital-based data are dependent on health seeking behaviour of the victims and generally underestimate incidence , while localized studies are almost always conducted in regions where snakebite is common , and tend to overestimate incidence [19] . Our previous work has shown that hospital data underestimate deaths due to snakebite by as much as 60% [4] . Incidence data may also depend on seasonal variations of bites . Our study demonstrates comprehensively the considerable geographical variation in snakebite incidence , the variation in the proportion of victims that are envenomed in different regions and the flaws in official data . Consequently , an accurate assessment of the burden of snakebite and envenoming can only be achieved by performing representative community surveys . Most of our results on the demography of bites are in agreement with the current literature . The highest rates of bites and envenoming were seen in the rural and agricultural north central and north eastern regions of the country . In keeping with other parts of the world , the highest disease burden due to venomous snakebite affects areas with the population groups that are most under-served in terms of healthcare and infrastructure . This re-emphasizes the need for equitable distribution of resources to address the problem of snakebite . Other ecological factors must also be taken into account to better understand these variations . Previous studies on snakebite show that rural males of working age are at high risk of snakebite due to high exposure levels associated with their lifestyle and occupation–mainly farming . In our study , males were also predominantly affected , and for both males and females the most susceptible were the economically active age groups . We have shown that the incidence of snakebite and envenoming gradually decreases with increasing population density . This may be due to more densely populated areas being less suitable as snake habitats . Snakebite incidence increased with increasing elevation up to 160 meters and thereafter dropped with increasing elevation , likely reflecting the facts that coastal areas are not generally suitable for snake habitats and that temperature declines with increasing altitude . Agricultural work has commonly been identified as a risk factor for snakebite . We assessed this by using the percentage of all workers undertaking agricultural work in each of the clusters . Snakebite incidence is dramatically lower in non-agricultural communities ( less than 9% involved in agriculture ) and snakebite incidence increased as the proportion of agricultural workers in a community increased . The incidence of snakebite is higher in both the intermediate and wet zones than in the dry climatic zone . However , the overall incidence of envenoming is higher in the dry zone . This is likely to reflect variation in species and again shows the importance of capturing data on the incidence of both snakebite and envenoming . Russell’s viper is the most widely distributed snake in Sri Lanka , and can be found up to an elevation of 1800 m . Saw-scaled vipers are largely confined to the arid dry zones of the country including Northern and Eastern Provinces extending up to eastern parts of the Southern Province . Cobras are also widely distributed in the country and are found up to 1500 m . Common Kraits are mainly found in the dry zone . Hump-nosed vipers are found all over the country , but mostly in the wet and intermediate zones [20][21][22][23] . Defining geographical areas by the level of risk of snakebite and envenoming is important for decision makers; allocation and distribution of antivenom , establishing snakebite management centres , and location of emergency treatment units and intensive care units all depend on assessing snakebite risk in a given location . Decision makers require thresholds to identify high risk areas for intervention . In this study , we drew cut-off points based on the national snakebite incidence rate for the country , which is about 400 per 100000 . High risk areas or hotspots and low risk populations ( cold spots ) were defined by adding or subtracting 100 cases per 100000 to the national rate . Similarly , cut-off points were determined for envenoming bites based on the national rate of 150 cases per 100000 . Hot and cold spots were determined by adding 100 cases per 100000 and subtracting 50 cases per 100000 , respectively , from the national rate . Such estimates can be further refined to improve decision making by quantifying the likelihoods of exceeding or not exceeding any pre-defined threshold of incidence at a given location . Mapping of estimated incidence may lead to some uncertainty about whether the true incidence exceeds a given cut off threshold , as precision of the estimates varies between locations . Although the point estimate maps and PCMs are qualitatively similar , quantitative differences are important in interpreting the maps and decision making . Thus PCMs provide additional information to identify confidently high risk and low risk areas with respect to any pre-defined incidence threshold , as indicated on a PCM by probabilities close to one or zero respectively . PCMs also identify areas of high uncertainty , i . e . map areas with probabilities close to 0 . 5 , indicating a need for additional sampling to draw firm conclusions . The methodology used in the present study can be applied to estimate snakebite incidence in other geographical locations . In the methodology , the model captures the complexity of the snakebite process of a human , snake and environment interaction through a combination of covariate adjustments and spatially correlated residual variation , representing explained and unexplained spatial variation , respectively . This flexibility allows the approach to be applied in , with re-estimation of the model parameters to take account of difference in the available covariate information and consequent re-balancing between explained and unexplained spatial variation . There are inevitably limitations to this study . The quality of the household data depended upon memory of an event and is therefore subject to recall bias . However , the main outcome of interest , a snakebite , is highly memorable and we think it unlikely that this affects our estimates although the possibility of the incidence of envenoming being increased due to inappropriate classification of envenomed bites is acknowledged . Our sampling strategy was carefully designed to make it representative of Sri Lanka . However , the use of the electoral register to identify the first household in any cluster does mean that there is a chance that the small population in slums may have been under-sampled . As slums are relatively uncommon in Sri Lanka except in big cities , this is unlikely to have affected our estimates . Urbanization , which is highly correlated to several of the district-level variables , could also have been a confounder . Finally , cluster ( i . e . GN ) level income statistics were not available at the Census and Statistics Department of Sri Lanka . We therefore used district mean income to estimate cluster level income . This approach means that variability in income within a district may have led to some inaccuracies in the cluster level income estimates resulting in some residual confounding . In conclusion we have , for the first time , been able to provide robust community based incidence rates of snakebite and envenoming at a national level . We also developed estimated incidence maps and probability contour maps of within-country spatial variation , which can inform local healthcare decision making . The methodology we have used is replicable , as the required software is open-source . It also addresses the methodological limitations of the many epidemiological studies on snakebite that base their results on data from hospitals or from localized or time-limited surveys .
|
Snakebite is a neglected tropical disease which mainly affects the rural poor in tropical countries . There is little reliable data on snakebite , which makes it difficult to estimate the true disease burden . Hospital statistics underestimate numbers of snakebites because a significant proportion of victims in tropical countries seek traditional treatments . On the other hand , time limited or localized surveys may be inaccurate as they may underestimate or overestimate numbers depending on when and where they are performed . To get a truer picture of the situation in Sri Lanka , where snakebites are an important cause of hospital admission , we undertook an island-wide community survey to determine the number of bites , envenomings and deaths due to snakebite in the previous 12 months . We found that there were more than 80 , 000 bites , 30 , 000 envenomings and 400 deaths due to snakebite , much more than claimed by official statistics . There was variation in numbers of bites and envenomings in different parts of the country and , using the data from our survey , we were able develop snakebite risk maps to identify snakebite hotspots and cold spots in the country . These maps would be useful for healthcare decision makers to allocate resources to manage snakebite in the country . We used free and open source software and replicable methods , which we believe can be adopted to other regions where snakebite is a public health problem .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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2016
|
Mapping the Risk of Snakebite in Sri Lanka - A National Survey with Geospatial Analysis
|
Oculopharyngeal muscular dystrophy ( OPMD ) , a late-onset disorder characterized by progressive degeneration of specific muscles , results from the extension of a polyalanine tract in poly ( A ) binding protein nuclear 1 ( PABPN1 ) . While the roles of PABPN1 in nuclear polyadenylation and regulation of alternative poly ( A ) site choice are established , the molecular mechanisms behind OPMD remain undetermined . Here , we show , using Drosophila and mouse models , that OPMD pathogenesis depends on affected poly ( A ) tail lengths of specific mRNAs . We identify a set of mRNAs encoding mitochondrial proteins that are down-regulated starting at the earliest stages of OPMD progression . The down-regulation of these mRNAs correlates with their shortened poly ( A ) tails and partial rescue of their levels when deadenylation is genetically reduced improves muscle function . Genetic analysis of candidate genes encoding RNA binding proteins using the Drosophila OPMD model uncovers a potential role of a number of them . We focus on the deadenylation regulator Smaug and show that it is expressed in adult muscles and specifically binds to the down-regulated mRNAs . In addition , the first step of the cleavage and polyadenylation reaction , mRNA cleavage , is affected in muscles expressing alanine-expanded PABPN1 . We propose that impaired cleavage during nuclear cleavage/polyadenylation is an early defect in OPMD . This defect followed by active deadenylation of specific mRNAs , involving Smaug and the CCR4-NOT deadenylation complex , leads to their destabilization and mitochondrial dysfunction . These results broaden our understanding of the role of mRNA regulation in pathologies and might help to understand the molecular mechanisms underlying neurodegenerative disorders that involve mitochondrial dysfunction .
Many neurodegenerative disorders are due to expansions of trinucleotide repeats in the associated genes . In many cases , the pathology is thought to involve protein misfolding and accumulation in insoluble aggregates [1] . However , more recent data have also implicated RNA toxicity and RNA granules in several neurodegenerative diseases [2 , 3] . RNA repeats can induce the formation of RNA aggregates and interact with RNA binding proteins , thus interfering with RNA metabolism . Oculopharyngeal muscular dystrophy ( OPMD ) is another triplet expansion disease which results from short expansions of a GCN repeat in the gene encoding poly ( A ) binding protein nuclear 1 ( PABPN1 ) [4] . OPMD is an autosomal dominant muscular dystrophy , which has a late onset and is characterised by progressive weakness and degeneration of specific muscles [5 , 6] . Triplet expansion in PABPN1 leads to extension of a polyalanine tract from 10 alanines in the normal protein to a maximum of 17 alanines at the N-terminus of the protein . Nuclear aggregates in muscle fibres are a pathological hallmark of OPMD [7] . These aggregates contain mutant insoluble PABPN1 , ubiquitin , subunits of the proteasome , as well as poly ( A ) RNA [8] . Polyalanine expansions in PABPN1 are thought to induce misfolding and formation of aggregates , which are targeted to the ubiquitin-proteasome degradation pathway [9 , 10] . However , it is still unknown whether these nuclear aggregates have a pathological function , a protective role , or are a consequence of a cellular defence mechanism . Despite recent progress in OPMD pathophysiology showing important deregulation of the ubiquitin-proteasome system in the disease [9] and a role of apoptosis [11] , the molecular mechanisms leading to muscle dysfunction remain undetermined . PABPN1 plays a role in nuclear polyadenylation , an mRNA processing reaction leading to the formation of the poly ( A ) tail at the 3' end of mRNAs [12] . PABPN1 binds to nascent poly ( A ) tails during this reaction and acts in stimulating poly ( A ) polymerase ( the enzyme that synthesizes the poly ( A ) tail ) and controlling poly ( A ) tail length [13–15] . Consistent with this function , in vivo data using mutants of Pabp2 , the PABPN1 homologue in Drosophila [16] , and knock-down of PABPN1 in cultured mouse myoblasts [17] have shown shorter mRNA poly ( A ) tail lengths upon depletion of PABPN1 . Other functions of PABPN1 have been described more recently in i ) a nuclear surveillance mechanism leading to hyperadenylation and decay of RNAs retained in the nucleus [18] , ii ) polyadenylation and turnover of long non-coding RNAs [19] , and iii ) regulation of poly ( A ) site usage whereby PABPN1 prevents the utilization of proximal weak poly ( A ) sites [20] . Any of these functions might be relevant to OPMD , and indeed a general shift in the utilization of proximal poly ( A ) sites was described in a mouse model of OPMD and correlated with some upregulation of the shorter form of mRNAs generated following this shift [20 , 21] . However , whether and how this upregulation might underlie OPMD was not addressed . Here we use a Drosophila model of OPMD to investigate the molecular defects leading to OPMD . This model is generated by the expression of alanine expanded mammalian PABPN1 ( PABPN1-17ala ) specifically in muscles; it reproduces the disease characteristics , namely progressive muscle weakness and degeneration resulting in wing position defects , and formation of nuclear aggregates containing mutant PABPN1 in affected muscles [22 , 23] . Using complementary transcriptomic and genetic approaches we show that an early defect during OPMD progression is the down-regulation of mRNAs encoding mitochondrial proteins , which depends on their active deadenylation and leads to mitochondrial dysfunction . We find that the cleavage step during the nuclear cleavage/polyadenylation reaction is affected in the Drosophila model of OPMD . However , this defect is general and the specific mRNA down-regulation depends on active deadenylation involving the CCR4-NOT deadenylation complex and Smaug ( Smg ) , an RNA binding protein known to recruit the CCR4-NOT complex to specific mRNAs [24 , 25] . Reducing the dosage of genes involved in deadenylation partially rescues the levels of mRNAs encoding mitochondrial proteins leading to improvement of muscle function . Importantly , these early defects are conserved in a mouse model of OPMD and mitochondrial protein levels are also decreased in muscle biopsies from OPMD patients . Down-regulated mRNAs involved in mitochondrial function are enriched in Smg recognition elements ( SREs ) in both Drosophila and mouse . We propose a model in which the first molecular defect in OPMD concerns PABPN1 nuclear function in cleavage/polyadenylation . Some mRNAs are specifically sensitive to this defect because they are actively deadenylated by Smg and the CCR4-NOT deadenylation complex in the cytoplasm . A subset of these mRNAs encodes mitochondrial proteins and the molecular defect results in a deficit of mitochondrial activity , which in turn affects muscle function .
To gain insight into the molecular and physiological defects in OPMD we performed a transcriptomic analysis in Drosophila muscles expressing PABPN1-17ala . Using microarrays , thorax gene expression was compared between control flies ( Mhc-Gal4/+ ) and flies expressing PABPN1-17ala in thoracic muscles ( UAS-PABPN1-17ala/+; Mhc-Gal4/+ ) , at three time points ( days 2 , 6 and 11 ) [26] . We used two-way ANOVA with genotype and time as the first and second variables , respectively , to identify deregulated genes . Up- and down-regulated genes were found at all time points after expression of PABPN1-17ala ( Fig . 1A ) [26] . We reported the identification of the ubiquitin-proteasome system as a prominent pathway deregulated in OPMD [9] . Importantly , this pathway was identified using the comparison of transcriptomic analyses from the Drosophila and mouse models of OPMD and from patient biopsies , demonstrating the relevance of the Drosophila and mouse models . In Drosophila muscles expressing PABPN1-17ala , genes involved in the ubiquitin-proteasome system were mostly up-regulated at day 6 [9] . Here we focused on deregulated genes at the earliest stage , with the aim of identifying early defects during OPMD progression . At day 2 , the most prominent deregulated pathway corresponded to mitochondrial function ( see below ) , and genes involved in this pathway were down-regulated . In total , 289 genes were found to be down-regulated at day 2 , among which 191 genes were down-regulated at the three time points ( Fig . 1B , S1 Table ) . Gene ontology ( GO ) term enrichment was analysed using FlyMine ( http//www . flymine . org ) [27] with a p-value <0 . 05 ( Bonferroni corrected ) . Among annotated genes , the term "mitochondrion" in "cellular component" was identified with the strongest p-value ( 1 . 34E-46 at day 2 , 1 . 85E-41 at day 6 and 2 . 78E-19 at day 11 ) . Up to 53% of annotated genes were annotated with this term ( Fig . 1C ) . In particular , a large proportion of nuclear genes involved in oxidative phosphorylation ( subunits of the respiratory chain complexes ) were found to be down-regulated in Drosophila muscles expressing PABPN1-17ala ( Fig . 1D ) . We used RT-qPCR to validate gene down-regulation observed with microarrays . Nineteen genes were analysed , among which 16 ( 84% validation ) were found to be significantly down-regulated in muscles expressing PABPN1-17ala ( Fig . 1E , S1A , B Fig ) . In addition , five additional genes encoding subunits of the respiratory chain complexes ( Ucrh , RFeSP , Oscp , CG1746 and ATPsyn-b ) were analysed using RT-qPCR and found to be down-regulated ( S1A Fig ) , although they were not detected to be affected using microarrays , indicating the underestimation of the number of deregulated genes . Four other genes ( RpS6 , RpL32 , Vha16-1 and CG1031 ) , which are not involved in mitochondrial function and were not deregulated in microarrays , served as negative controls and were found to be unaffected using RT-qPCR ( S1C Fig ) . In summary , the major pathway down-regulated in Drosophila muscles expressing PABPN1-17ala corresponded to nuclear genes encoding mitochondrial proteins . This down-regulation started at the earliest time point ( day 2 ) , before the onset of muscle degeneration [23] , indicating that it is a early defect , that is maintained at later time points . Because down-regulation of mitochondrial components is prominent at the earliest time point , we checked whether mitochondrial biogenesis or mass were affected in muscles expressing PABPN1-17ala . Mitochondrial abundance was analysed by quantifying mitochondrial DNA using qPCR . Mitochondrial DNA levels normalized to nuclear DNA were unaffected in Drosophila muscles expressing PABPN1-17ala , suggesting that mitochondrial mass was similar to that in control muscles ( Fig . 2A ) . Mitochondria generate energy from nutrients through oxidative phosphorylation using the combined action of five enzyme complexes . We assessed the activity of four of these complexes in Drosophila muscles , as well as that of citrate synthase which correlates with mitochondrial mass [28] . The activity of citrate synthase was only slightly decreased ( 83% , 80% and 91% of the control muscle activity at day 2 , 6 and 11 , respectively ) , consistent with mitochondrial DNA levels being unaffected in muscles expressing PABPN1-17ala . In contrast , the activities of the four mitochondrial respiratory chain complexes ( complex I: NADH dehydrogenase; complex II: succinate dehydrogenase; complex III: cytochrome bc1; and complex IV: cytochrome c oxidase ) were significantly decreased in muscles expressing PABPN1-17ala ( Fig . 2B ) . These results indicate a mitochondrial dysfunction in the OPMD Drosophila model . As another assay to confirm this defect , we used the GstD1-GFP transgene as a marker of oxidative stress [29] . Mitochondrial dysfunction leads to oxidative stress [30] which in turn activates the expression of the detoxification enzyme GstD1 . Expression of the GstD1-GFP transgene was specifically induced in muscles expressing PABPN1-17ala , starting at day 2 ( S2 Fig ) . Both the generation of oxidative stress and the defect in energy production resulting from decreased mitochondrial respiratory chain activity could participate in the dysfunction of muscles . To functionally address whether mitochondrial activity defects play a role in the dysfunction of muscles expressing PABPN1-17ala , we tested if OPMD phenotypes of defective wing posture could be rescued by increasing the expression of genes involved in mitochondrial function . Mitochondrial biogenesis and activity are controlled by cellular pathways allowing crosstalk between mitochondria and the cell nucleus . The transcription factors nuclear respiratory factor-1 and -2 ( NRF-1 and NRF-2 ) and oestrogen-related receptor-α ( ERRα ) , as well as the co-activator PPARγ coactivator 1 ( PGC-1 ) are known to co-regulate a large number of genes involved in mitochondrial function , including those encoding subunits of the respiratory chain complexes [31–33] . NRF-1 , NRF-2 and PGC-1 genes are conserved in Drosophila ( erect wing ( ewg ) , delg and spargel , respectively ) , as well as their function in the control of mitochondrial mass and activity [34–36] . A potential role of Drosophila ERR ( dERR ) in mitochondrial function has also been proposed during adult stages [37] . We first checked that the reduced respiratory chain complex activities did not result from decreased expression of these transcription activators in Drosophila muscles expressing PABPN1-17ala , using RT-qPCR . The levels of ewg , delg and dERR mRNAs were unaffected in these muscles and spargel expression was found to be increased ( Fig . 2C ) . While overexpression of spargel or delg in muscles was not able to rescue wing posture defects , overexpression of ewg or dERR significantly reduced these defects ( Fig . 2D ) . Together , these results show a deficit in mitochondrial respiratory chain activity in Drosophila muscles expressing PABPN1-17ala and strongly suggest that this deficit has a key role in muscle defects since overexpression of general regulators of mitochondrial biogenesis and function improved muscle function . We have shown previously that the RNA binding activity of PABPN1 plays a role in OPMD pathogenesis suggesting that the disease process involves mRNA metabolism [23] . To test this hypothesis , we performed a small screen using heterozygous mutants of genes encoding RNA binding proteins and proteins involved in poly ( A ) tail length regulation ( polyadenylation and deadenylation ) . We generated a new transgene Act88F-PABPN1-17ala which allows constitutive expression of PABPN1-17ala in adult indirect flight muscles [38] . Expression of this transgene led to 40 to 50% of flies showing abnormal wing posture , thus allowing to screen for a decrease or an enhancement of this phenotype ( Fig . 3A , B ) . The CCR4-NOT deadenylation complex is composed of eight subunits in Drosophila , including two deadenylases CCR4 and POP2 , and is involved in shortening mRNA poly ( A ) tails [39–41] . Strikingly , we found that all available mutations in the complex subunits decreased the number of Act88F-PABPN1-17ala/+ flies with wing position defects ( Fig . 3A , B ) . In contrast , mutants of the hiiragi gene which encodes the nuclear poly ( A ) polymerase involved in polyadenylation [42 , 43] enhanced the wing position defects ( Fig . 3B ) . Reduced dosage of Pabp2 ( Drosophila PABPN1 ) decreased the number of flies with abnormal wing posture , suggesting that part of these phenotypes resulted from a gain-of-function of PABPN1 . Several suppressors encoded RNA binding proteins indicating their potential implication in OPMD ( Fig . 3B ) . This is consistent with the important role of mRNA regulation in OPMD and suggests an involvement of multiple RNA-dependent pathways . Among suppressors , pumilio ( pum ) and smg encode translational repressors that directly interact with the CCR4-NOT deadenylation complex [24 , 25 , 44 , 45] . Deadenylation is the first step of mRNA destabilization , we therefore measured poly ( A ) tail lengths of a number of mRNAs that were down-regulated in PABPN1-17ala-expressing muscles , namely mRNAs encoding subunits of the mitochondrial respiratory chain complexes , using Poly ( A ) test assays ( PAT assays ) . These mRNAs had shorter poly ( A ) tails in muscles expressing PABPN1-17ala starting at day 2 ( Fig . 3C , S3 Fig ) . In contrast , poly ( A ) tail lengths of control mRNAs encoding myofibril-specific or ribosomal proteins ( Actin 88F ( Act88F ) , Troponin C at 41C ( TpnC41C ) and Sop ) were unaffected in muscles expressing PABPN1-17ala , consistent with their unchanged levels in microarrays ( Fig . 3D , S3 Fig ) . These genetic data indicate that the regulation of mRNA poly ( A ) tail length plays an essential role in OPMD pathogenesis in the Drosophila model; specific mRNAs have shorter poly ( A ) tail lengths , which leads to their destabilization . PABPN1 is mostly nuclear and involved in polyadenylation and in the prevention of weak proximal poly ( A ) site utilization in cases of several tandem poly ( A ) sites . This last function indicates a role of PABPN1 during the cleavage step of the cleavage/polyadenylation reaction at weak poly ( A ) sites , and we asked whether cleavage might be generally impaired in OPMD . We analysed pre-mRNA cleavage at poly ( A ) sites by quantifying the levels of uncleaved pre-mRNA using RT-qPCR ( Fig . 4A ) . We found that the cleavage at poly ( A ) sites was less efficient in muscles expressing PABPN1-17ala than in control muscles ( Fig . 4B ) . This defect was not restricted to genes that were down-regulated in muscles expressing PABPN1-17ala ( i . e . genes encoding mitochondrial proteins ) but also occurred in genes encoding either ribosomal ( RpS6 , RpL32 ) or muscle specific ( Myosin heavy chain ( Mhc ) , Act88F ) proteins , that were not down-regulated . A general defect in pre-mRNA cleavage during the cleavage/polyadenylation reaction had not been associated previously with PABPN1 loss-of-function , we therefore tested whether this step of the reaction was affected in Pabp2 mutants . The null allele Pabp255 is lethal at first instar larval stage [16] , we used first instar Pabp255/Df ( 2R ) CA53 larvae before they died to quantify the levels of uncleaved pre-mRNA by RT-qPCR . Similarly to what was found in muscles expressing PABPN1-17ala , we observed a decreased efficiency in the cleavage of several pre-mRNAs ( Fig . 4C ) , suggesting that PABP2 plays a general role in the cleavage step of the cleavage/polyadenylation reaction . These results reveal that in the OPMD Drosophila model , the first defect is nuclear and corresponds to a decreased efficiency of cleavage at poly ( A ) sites . This defect does not systematically lead to reduced steady-state levels of mature mRNAs . The cleavage defect in PABPN1-17ala-expressing muscles appears to be general , yet the poly ( A ) tail shortening and destabilization occur on specific mRNAs . This indicates that the specificity of mRNA destabilization would not depend on the first defect in pre-mRNA cleavage , but on a downstream process . This process might correspond to deadenylation which can be activated on specific mRNAs through the recruitment of the CCR4-NOT deadenylation complex to these mRNAs by specific RNA binding proteins . In this model , OPMD would result from an altered function of PABPN1 leading to a reduced efficiency of nuclear cleavage/polyadenylation , then followed by normal active deadenylation of specific mRNAs . The reduced efficiency in nuclear cleavage would only affect the steady-state levels of mRNAs that are actively deadenylated . To test this model , we analysed the potential rescue of the levels of mRNAs that were decreased in Drosophila muscles expressing PABPN1-17ala , by twin heterozygous mutation ( twin encodes the CCR4 deadenylase ) . Among the 20 mRNAs that we analysed using RT-qPCR , 18 showed higher expression levels in muscles expressing PABPN1-17ala in the presence of the twin mutant ( Fig . 5A , S4A , B Fig ) . The CCR4-NOT deadenylation complex itself has no specificity for particular mRNAs . The specificity instead depends on RNA binding proteins which interact with pools of mRNAs and recruit the deadenylation complex through direct protein interactions . Smg and Pum that were identified as suppressors of wing posture defects ( Fig . 3B ) are such RNA binding proteins . We tested the rescue of mRNA levels by RT-qPCR in muscles expressing PABPN1-17ala , in the presence of pum or smg heterozygous mutations . No rescue was observed with the pum mutant ( Act88F-PABPN1-17ala/pum3 ) ( n = 19 mRNAs ) , suggesting that the phenotypic rescue of wing posture with this mutant did not involve the stabilization of these mRNAs , and might potentially involve their localization or translational regulation . Indeed , Puf3p , a yeast Pum homologue specifically binds to mRNAs encoding mitochondrial proteins and regulate their deadenylation or localization to mitochondria , coupled to translation [46–48] . In contrast , the levels of 14 mRNAs out of 20 analysed were increased in the presence of the heterozygous smg1 mutation ( Fig . 5A , S4A , B Fig ) . This suggests that Smg plays a role in the specific deadenylation and destabilization of mRNAs encoding mitochondrial proteins . We checked that the phenotypic rescue with twin and smg mutants did not involve the reduction of PABPN1-17ala levels ( S4C , D Fig ) . We analysed Smg expression in adult muscles . Smg is expressed in early embryos where it is cytoplasmic and accumulates in discrete foci that have been linked to deadenylation and/or translational repression [25 , 49] , and it was recently shown to be present in larval muscles [50] . Using immunostaining and western blots , we validated the presence of Smg in cytoplasmic foci in adult thoracic muscles ( Fig . 5B , C ) . The specificity of the antibody was verified using a smg mutant background . In addition , Smg was able to co-precipitate the CCR4 deadenylase in adult muscles ( Fig . 5D ) . The co-precipitation was maintained in the presence of RNase A , indicating that Smg and CCR4 could form a complex independently of RNA . In contrast , PABP2 which accumulates in the nucleus was not co-precipitated with Smg ( Fig . 5D ) . We then performed Smg immunoprecipitation experiments in muscles and quantified mRNA enrichment using RT-qPCR , to address whether Smg could be in complex with mRNAs down-regulated in muscles expressing PABPN1-17ala . A number of these mRNAs encoding mitochondrial proteins were found to be enriched in Smg immunoprecipitations ( Fig . 5E , S4E Fig ) . Smg binds to stem-loop structures , the SREs in which the consensus motif in the loop is CNGGN0-4 [51] . We analyzed potential SRE enrichment in genes down-regulated in muscles expressing PABPN1-17ala that were annotated with the term "mitochondrion" ( 98 genes , S2 Table ) , by calculating SRE scores in their mRNAs [51] . SRE sequences were enriched in these mRNAs compared to in control mRNAs ( Fig . 5F ) . These results suggest a direct association of mRNAs encoding mitochondrial proteins with Smg , leading to their CCR4-mediated deadenylation and destabilization . The formation of nuclear PABPN1 aggregates is a hallmark of OPMD , although the presence of nuclear aggregates and muscle defects can be uncoupled in animal models [23 , 52] . Hitherto , components that were identified as decreasing muscle degeneration in the Drosophila model also reduced PABPN1 aggregation , since these components either directly interacted with PABPN1 ( anti-PABPN1 intrabody ) , or with protein aggregation [22 , 26] . We asked whether the rescue of PABPN1-17ala-induced phenotypes by affecting poly ( A ) tail length regulation might interfere with PABPN1 aggregate formation . Nuclear aggregates have been monitored previously in UAS-PABPN1-17ala/+; Mhc-Gal4/+ Drosophila muscles [22 , 23] , we therefore checked that a twin heterozygous mutant decreased the wing posture defects in such flies ( Fig . 6A ) . PABPN1 nuclear aggregates were then quantified and their surface was measured in thoracic muscles of flies expressing PABPN1-17ala , in the presence or absence of twin heterozygous mutation . Strikingly , although the surface of the aggregates was not significantly different in both conditions , the number of nuclei containing an aggregate increased in the presence of twin heterozygous mutant ( Fig . 6B , C ) . Therefore , in contrast to previously described conditions of rescued muscle function in PABPN1-17ala-expressing muscles , here improvement of muscle function did not correlate with reduced PABPN1 aggregation . These results are consistent with other data reporting the dissociation between the presence of PABPN1 nuclear aggregates and muscle defects , and suggest that PABPN1 aggregates are not always causative of muscle defects . To extend our study to a mammalian model , quadriceps gene expression using microarrays was compared between control mouse ( FvB ) and A17 . 1 mouse which expresses PABPN1-17ala in skeletal muscle [53] , at three time points ( T1 , 6 weeks; T2 , 18 weeks; and T3 , 26 weeks ) [54] . Up- and down-regulated genes were found at all time points ( Fig . 7A ) , with the ubiquitin-proteasome system being higly deregulated [9] . Annotation clustering enrichment analysis using DAVID [55] revealed that down-regulated genes common to all three time points were mostly enriched in genes encoding mitochondrial proteins ( GO:0005739 "mitochondrion" , Fold enrichment 14 . 8 , p-value 5 . 88E-23 ) , and we identified several nuclear genes involved in oxidative phosphorylation that were down-regulated , starting at the earliest time point ( Fig . 7B , C , S3 Table ) . RT-qPCR confirmed the down-regulation observed with microarrays at T1 ( Fig . 7D ) . These data obtained on pre-symptomatic muscles , for which no muscle weakness was evidenced [53] , further confirmed the down-regulation of mRNAs encoding mitochondrial proteins as an early defect in OPMD . Using ePAT ( extension PAT ) assays , we found that the down-regulation of these mRNAs correlated with the accumulation of shorter poly ( A ) tails ( Fig . 7E ) . SREs are conserved from yeast to mammals [56 , 57] . We searched for the presence of potential SREs in the genes down-regulated at T1 that were annotated with the term "mitochondrion" ( 407 genes , S4 Table ) [51] . SRE scores were higher in these down-regulated mRNAs than in control mRNAs ( Fig . 5F ) indicating an enrichment of SREs in mRNAs down-regulated in muscles from the A17 . 1 mouse . In order to validate the role of SREs in the regulation of mRNAs that were down-regulated in PABPN1-17ala expressing muscles , we selected Ndufa10 mRNA which contains a potential SRE in its 3'UTR ( S5A Fig ) . We took advantage of the HEK293T human cell line which we found expressing SAMD4A , the human homologue of Smg , using RT-PCR , western blot and immunostaining ( S5B , C Fig ) . Reporter constructs containing Ndufa10 3'UTR either with the potential SRE or with a mutant form of this element were used for transfection , and mRNA levels produced from these constructs were quantified using RT-qPCR . Mutation of the SRE resulted in higher levels of mRNA ( S5A Fig ) , consistent with the role of the SRE in mRNA destabilization . We conclude that the down-regulation of mRNAs encoding mitochondrial proteins in pre-symptomatic muscles expressing PABPN1-17ala is conserved in mouse . This down-regulation correlates with accumulation of shorter poly ( A ) tail lengths of these mRNAs and with their enrichment in SREs . To further validate a defect in mitochondrial components in OPMD patients , we used a proteomic approach on control and OPMD patient sternocleidomastoid muscle biopsies . This muscle , which is clinically unaffected [58] was used as a surrogate for pre-symptomatic samples . Strikingly , among the 70 proteins that were found significantly deregulated , 49 were down-regulated and 78% of them were mitochondrial proteins ( n = 38 ) ( Fig . 8A , B , S5 Table ) . Moreover , 53% ( n = 20 ) and 39% ( n = 15 ) of these proteins were orthologous to mitochondrial proteins encoded by down-regulated mRNAs in the Drosophila and mouse models , respectively . We verified by RT-qPCR that the corresponding mRNAs were down-regulated in OPMD patient biopsies ( Fig . 8C ) , whereas the amount of mitochondrial DNA remained unchanged ( Fig . 8D ) . These results confirm the molecular data obtained in both animal models , showing the down-regulation of mRNAs encoding mitochondrial proteins as an early defect in OPMD . They further show the down-regulation of mitochondrial proteins and are consistent with mitochondrial dysfunction playing an important role in early stages of OPMD progression .
The molecular defects underlying OPMD pathology remain largely undetermined , although recent advances have implicated apoptosis [11] and a general deregulation of the ubiquitin-proteasome system [9] . However , these are downstream events in the pathogenesis . Here , we further investigate the molecular mechanisms involved by analysing early defects in the disease . We show that specific mRNAs encoding proteins involved in mitochondrial activity are present at lower levels in pre-symptomatic OPMD muscles; this reduced expression results from the shortening of their poly ( A ) tails which leads to their destabilization . Poly ( A ) tail length regulation plays a key role in OPMD since muscle function is improved when deadenylation is decreased using mutants . We further show that nuclear cleavage/polyadenylation of pre-mRNAs is inefficient in PABPN1-17ala-expressing muscles ( Fig . 9 ) . This defect occurs both on genes which are and on those which are not down-regulated , indicating that it does not per se systematically lead to reduced steady-state mRNA levels . The decreased levels of specific mRNAs result from their active deadenylation , itself dependent , at least in part , on the specific interaction of these mRNAs with the Smg RNA binding protein and the recruitment by Smg of the CCR4-NOT deadenylation complex ( Fig . 9 ) . In addition , our genetic data revealing the potential involvement of other RNA binding proteins suggest that OPMD pathogenesis is complex and probably involves additional mechanisms of RNA regulation . The function of PABPN1 during cleavage/polyadenylation has been documented . Nuclear polyadenylation occurs in two steps: first , cleavage of the pre-mRNA at the poly ( A ) site , which is co-transcriptional , and second , polyadenylation which potentially occurs after dissociation of the RNA from the RNA polymerase II . PABPN1 was shown to be involved in the second step , polyadenylation , for the control of poly ( A ) tail lengths [14 , 15] . More recent data have also implicated PABPN1 in the cleavage step for the regulation of weak poly ( A ) sites [20] . Here we show impaired cleavage at poly ( A ) sites in the Pabp2 loss-of-function mutant , revealing a more general role of PABP2/PABPN1 in this step of the reaction . In the regulation of weak poly ( A ) sites , PABPN1 binds to non-canonical polyadenylation signals and prevents the binding of CPSF ( Cleavage and polyadenylation specificity factor ) required for cleavage [20] . A general function of PABPN1 in cleavage would require other interactions , for example with proteins required for cleavage , such as the poly ( A ) polymerase known to associate with PABPN1 [14] . Although a global shift to proximal poly ( A ) sites has been reported in the mouse model of OPMD [20 , 21] , the down-regulation and poly ( A ) tail shortening of specific mRNAs that we functionally show to participate in OPMD pathogenesis are independent of alternative poly ( A ) site utilization . The molecular defects observed in PABPN1-17ala-expressing muscles , reduction of mRNA poly ( A ) tail length and decreased efficiency of cleavage at poly ( A ) sites are similar to those observed in Pabp2 loss-of-function mutants ( [16] , this study ) . This suggests that part of the defects in OPMD could result from partial PABPN1 loss-of-function . However , the genetic suppression of wing posture phenotypes by reducing the dosage of Pabp2 does not favour a simple loss-of-function model . It has been proposed for polyglutamine diseases that the pathogenesis could result from both the gain-of-function and the loss-of-function of the same protein [59] . The protein responsible for the disease would exist in two different conformations with two different yet normal functions . Extension of the polyglutamine tract would favour one conformer resulting in increased amounts of this conformer and the partial loss-of-function of the other conformer; the pathology would result from both these effects . In this model , the mutant protein would have the same function as the normal protein but would have the ability to alter the balance between both protein forms . Several properties of PABPN1 are consistent with this model for OPMD . We have shown previously that the normal function of PABPN1 and more specifically its RNA binding activity is required for OPMD-like defects in the Drosophila model [23] . In addition , PABPN1-17ala half-live was reported to be longer than that of PABPN1 in cell models , leading to higher accumulation of PABPN1-17ala and protein aggregation [60] . Thus , expansion of the polyalanine tract results in protein "overexpression" which contributes to the pathology . Given this data , overepression of the normal protein might be expected to induce similar defects as expression of the mutant protein , as it is the case in Drosophila models for other disorders [61] . Consistent with this , we previously reported that PABPN1 expression in Drosophila muscles induced wing posture defects , although at lower levels than PABPN1-17ala expression [23] . Finally , normal PABPN1 is also known to form oligomers during nuclear polyadenylation and can form nuclear aggregates that recruit ubiquitin and proteasomes under specific physiological conditions [52 , 62] . Because the presence of nuclear aggregates and muscle defects can to some extent be uncoupled , we have previously proposed that nuclear aggregates are not always pathological [23] . This is consistent with results concerning polyglutamine diseases where aggregates can have a protective role [63] . We find that the improvement of muscle function when deadenylation is genetically reduced correlates with an increased number of PABPN1 aggregates , again strengthening the notion that the aggregates are not always causative of muscle defects . In that case , muscle protection that results from the reduction of molecular defects could allow the formation of more PABPN1 aggregates . Thus , these aggregates might not always be pathological , in particular during early stages of the disease , although they might become so at later stages , when their increased size could interfere with nuclear function . A major conclusion from our study is that the specificity of the defect in OPMD does not depend per se on PABPN1 defect in pre-mRNA cleavage , but on Smg-dependent regulation occurring in the cytoplasm . Because of the shift to proximal poly ( A ) sites that correlated with mRNA up-regulation , described in the OPMD mouse model [20] , we asked whether a similar mechanism could lead to increased Smg levels in Drosophila muscles expressing PABPN1-17ala and underlie increased deadenylation . However , the same poly ( A ) site was used in normal and PABPN1-17ala-expressing muscles , and we failed to detect major deregulation of smg mRNA and protein levels in PABPN1-17ala-expressing muscles ( S6A-C Fig ) . We propose that normal Smg-dependent deadenylation , following inefficient pre-mRNA cleavage , could lead to the reduced levels of specific mRNAs that we observe ( Fig . 9 ) . In addition , other processes such as mRNP remodelling could contribute to enhanced mRNA decay in the course of the disease progression . Indeed , Smg forms cytoplasmic foci which are distinct , but related to other cytoplasmic RNA granules such as processing ( P ) bodies or stress granules , in which mRNAs are degraded or translationally repressed , and the regulation of which affects mRNA regulation [25 , 64] . A recent study also revealed the implication of Smg/SAMD4A in Myotonic Dystrophy Type 1 ( DM1 ) . In that case , Smg mechanism of action appeared to be different , since overexpression of Smg decreased DM1 muscle defects by reducing unproductive CUGBP1-eIF2α translational complexes [50] . Mitochondrial dysfunction has been shown to play a major role in most neurodegenerative diseases including Parkinson's , Alzheimer's , Huntington's and other polyglutamine diseases [65] . More recent data have uncovered that aside mitochondrial function in energy production , mitochondrial dynamics including trafficking and quality control is instrumental in pathogenesis [65–67] . Mitochondria also have a key role in muscle function . Drosophila mutants of pink1 and parkin , mutations of which cause Parkinson's disease in man , lead to mitochondrial dysfunction and flight muscle degeneration [68 , 69] . We show that mitochondrial dysfunction is also an important component of OPMD: Muscle function is improved when mitochondrial biogenesis and activity are genetically increased; in addition , mitochondrial proteins are down-regulated in OPMD muscle biopsies from patients . We identify the molecular defects leading to early mitochondrial dysfunction in OPMD: mRNAs encoding mitochondrial proteins are down-regulated due to their Smg-dependent deadenylation . Therefore , our data reveal Smg as a regulator of mRNAs involved in mitochondrial function . This finding might have important implications on the role of Smg in several neurodegenerative diseases that involve mitochondrial dysfunction and/or RNA toxicity .
Experimental animal studies were conducted under approval of both the RHUL Animal Research Ethics Committee , and the UK Home Office , and with a UK Home Office license ( PPL 70/7008 ) under the UK Animals ( Scientific Procedures ) Act 1986 . Animal were euthanized by an approved schedule 1 procedure under these statutory regulations . All human muscle biopsies were obtained during surgical procedure after informed consent in accordance with the French legislation on ethical rules . Total RNA was prepared from 10 Drosophila thoraxes , mouse quadriceps , human muscle frozen biopsies or HEK293T cells , using Trizol ( Invitrogen ) as recommended by the manufacturer . DNA was digested using TURBO DNase ( Ambion ) or DNase RNase free ( Qiagen ) . Total RNA concentration was determined with nanodrop ND-1000 spectrophotometer . For RT-qPCR , 0 . 1–1μg of total RNA was reverse transcribed with SuperScript III ( Invitrogen ) . Random hexamers ( Roche ) were used for reverse transcription following Smg immunoprecipitations and for pre-mRNA cleavage anlysis . Oligo-d ( T ) 12-18 primers ( Invitrogen ) were used in RT-qPCR comparing mRNA levels in Drosophila thoraxes of different genotypes; we verified that utilization of random hexamers for these RT-qPCR reproduced the deregulation observed with oligo-d ( T ) 12-18 primers ( S1B Fig ) . A mix of oligo-d ( T ) 12-18 primers and random hexamers was used for reverse transcription performed on mouse and human RNAs . RNA levels were calculated using the LightCycler 480 SYBR Green I Master ( Roche ) on the LightCycler 480 Instrument ( Roche ) , and normalized with Drosophila sop and/or Cpr100A mRNAs , mouse Rplp0 and human B2M . sop and Rplp0 encode ribosomal proteins , β2-microglobulin ( B2M ) encodes a component of MHC class I molecules , and Cpr100A encodes a cuticular protein present in thorax cuticle but not expressed in muscles . Poly ( A ) test ( PAT ) assays were performed with 1μg of total RNA using either regular PAT [70] ( Fig . 3C ) , or ePAT [71] ( Fig . 7E , S3 , S6 Fig ) methods . Briefly , for the PAT reaction , mRNA poly ( A ) tails were coated with oligo-d ( T ) 12-18 primers which were then ligated; this reaction was followed by annealing of the d ( T ) -anchor primer to the overhanging remaining As at 12°C and its subsequent ligation , then by reverse transcription from this ligated primer , and PCR using d ( T ) -anchor and a gene specific primer [70] . For ePAT , the d ( T ) -anchor primer was annealed to mRNA poly ( A ) tails at 25°C and used as template for mRNA extension with Klenow polymerase ( see S6A Fig , ePAT ) ; this reaction was then switched to 55°C to dissociate annealings that had not been extended by Klenow polymerase , and followed by reverse transcription and PCR using d ( T ) -anchor and a gene specific primer [71] . PCR fragments were visualized on 2% agarose gel . RNase H digestion was performed on 3μg RNA with 5 Units RNase H ( Biolabs ) in the presence or not of 1μg oligo-d ( T ) 12-18 . Mitochondrial DNA ( mtDNA ) was extracted using a standard DNA extraction method . mtDNA was isolated from 5 thoraxes per genotype for Drosophila , and from 100 5μm-thick cryosections for human muscle biopsies . Total DNA concentration was quantified with the nanodrop ND-1000 spectrophotometer and 0 . 4 ng of total DNA was used for qPCR . Drosophila mtDNA content was quantified using mt:CoI , mt:CoII , and mt:cyt-b genes , and normalized with RpL32 genomic DNA . mtDNA content in human muscle biopsies was quantified using the MT-RNR1 gene and normalized using B2M nuclear genomic DNA . Primers used are indicated in S1 Text . Enzymatic activities were measured from homogenates of 10 thoraxes prepared at 4°C in 700 μl of phosphate buffer ( 50 mM; pH 7 ) . Enzymatic activities for each complex were measured from five independent homogenates per genotype . Activities of complexes I , II , II+III and IV , as well as citrate synthase activity were determined spectrophotometrically from the supernatant fraction as described previously [72] . Protein concentrations were measured using the Bio-Rad protein assay kit ( Bio-Rad ) . Anti-Smg antibody was raised in rabbit against amino acids 571 to 771 of the Smg protein ( SAM domain ) . Briefly , this fragment was expressed in E . coli as a His6-SUMO fusion protein . After metal affinity chromatography , the N-terminal SUMO domain was cleaved with ULP protease , the two protein fragments were separated by a second metal affinity column , and the SAM domain of Smg was finally purified by Superdex75 gel filtration . The antibody was produced at Eurogentec , using four injections of 100 μg of Smg SAM domain . Protein extracts were obtained from 5 or 10 thoraxes per genotype . Western blots were performed as described [73] . Immunostaining of thoracic muscles were performed as described previously [23] . Antibodies used for western blots , immunostaining and Smg immunoprecipitation procedures are indicated in Supporting Materials and Methods . SRE scores were determined as reported [51] using 98 Drosophila and 407 mouse genes down-regulated in OPMD muscles and annotated with the term "mitochondrion" . Control gene lists were generated by random selection within Drosophila genes found not to be enriched in Smg immunoprecipitations , with a fold change ≤1 [51] ( 98 genes , 20 times ) , and all mouse genes ( Mus musculus , Ensembl ) ( 407 genes , 10 times ) , respectively . Genes present in the tested lists were removed from the control lists . SRE scores were determined for all potential transcripts of each gene and the highest score only was considered per gene .
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Oculopharyngeal muscular dystrophy is a genetic disease characterized by progressive degeneration of specific muscles , leading to ptosis ( eyelid drooping ) , dysphagia ( swallowing difficulties ) and proximal limb weakness . The disease results from mutations in a nuclear protein called poly ( A ) binding protein nuclear 1 that is involved in polyadenylation of messenger RNAs ( mRNAs ) and poly ( A ) site selection . To address the molecular mechanisms involved in the disease , we have used two animal models ( Drosophila and mouse ) that recapitulate the features of this disorder . We show that oculopharyngeal muscular dystrophy pathogenesis depends on defects in poly ( A ) tail length regulation of specific mRNAs . Because poly ( A ) tails play an essential role in mRNA stability , these defects result in accelerated decay of these mRNAs . The affected mRNAs encode mitochondrial proteins , and mitochondrial activity is impaired in diseased muscles . These findings have important implications for the development of potential therapies for oculopharyngeal muscular dystrophy , and might be relevant to decipher the molecular mechanisms underlying other disorders that involve mitochondrial dysfunction .
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[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
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Mitochondrial Dysfunction Reveals the Role of mRNA Poly(A) Tail Regulation in Oculopharyngeal Muscular Dystrophy Pathogenesis
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Staphylococcus aureus is a major pathogen that colonizes about 20% of the human population . Intriguingly , this Gram-positive bacterium can survive and thrive under a wide range of different conditions , both inside and outside the human body . Here , we investigated the transcriptional adaptation of S . aureus HG001 , a derivative of strain NCTC 8325 , across experimental conditions ranging from optimal growth in vitro to intracellular growth in host cells . These data establish an extensive repertoire of transcription units and non-coding RNAs , a classification of 1412 promoters according to their dependence on the RNA polymerase sigma factors SigA or SigB , and allow identification of new potential targets for several known transcription factors . In particular , this study revealed a relatively low abundance of antisense RNAs in S . aureus , where they overlap only 6% of the coding genes , and only 19 antisense RNAs not co-transcribed with other genes were found . Promoter analysis and comparison with Bacillus subtilis links the small number of antisense RNAs to a less profound impact of alternative sigma factors in S . aureus . Furthermore , we revealed that Rho-dependent transcription termination suppresses pervasive antisense transcription , presumably originating from abundant spurious transcription initiation in this A+T-rich genome , which would otherwise affect expression of the overlapped genes . In summary , our study provides genome-wide information on transcriptional regulation and non-coding RNAs in S . aureus as well as new insights into the biological function of Rho and the implications of spurious transcription in bacteria .
The Gram-positive bacterium Staphylococcus aureus causes human infections that range from superficial skin infections to life-threatening diseases such as pneumonia , endocarditis , osteomyelitis , bacteremia and sepsis [1] . This major human pathogen is also a common component of skin and mucosal flora and many clinical cases arise from auto-infection [2] . In the healthy population the most important niche of the bacterium seems to be the anterior nares , with a proportion of approximately 20% permanent carriers [3] . S . aureus´ host range is not limited to humans; it also infects many animals [4] and frequently causes food-borne disease due to its presence on raw meat [5] . A growing concern is the emergence of antibiotic-resistant strains , such as methicillin-resistant S . aureus ( MRSA ) [6 , 7] . The versatile nature of S . aureus relies on a wide range of virulence factors , whose expression is coordinated by a complex gene regulatory network . They facilitate the escape from host immune responses and adaptation to diverse environmental conditions ( reviewed in [8 , 9] ) . Physiological adaptation of a bacterium is coordinated largely at the transcriptional level where molecules such as RNA polymerase sigma factors , transcription factors , and regulatory RNAs , are involved in a variety of mechanisms to modulate mRNA synthesis , processing and degradation . Genome-wide transcriptome studies analyzing bacterial transcription globally and in a quantitative manner across various environmental conditions have provided deep insights into the bacterial transcriptome architecture [10–13] . In particular , by revealing the repertoire of non-coding RNAs , they raised the interest in the regulatory roles of small non-coding RNAs and antisense RNAs [14 , 15] . A tiling array transcriptome study of the Gram-positive model bacterium Bacillus subtilis exposed to a wide range of nutritional and environmental conditions established one of the most comprehensive repertoires of transcription units in a prokaryote [13] . It also evaluated the global contribution of a bacterium’s alternative sigma factors to transcriptional regulation and proposed the hypothesis that a large proportion of B . subtilis antisense RNAs could be attributed to transcription initiated by alternative sigma factors and to imperfect control of transcription termination . This raised the possibility that many antisense transcripts may not have a functional role but are spurious transcripts generated by imperfect transcription termination and unintended transcription initiation , the latter being presumably less deleterious and more frequent when linked to alternative condition-dependent sigma factors [13] . In line with this hypothesis , other studies also proposed a possible preponderant role of transcriptional noise in antisense transcription based on the weak conservation of promoters associated with these RNAs between Escherichia coli and Salmonella enterica [16] and in another group of the Gammaproteobacteria [17] . However , the extent of spurious transcription in bacterial genomes and its implications remain a matter of debate [18 , 19] . The availability of large-scale transcriptome data for a particular organism has also proven a very useful resource , complementing sequence-based genome annotation , for the respective research community . Indeed , the information on the genetic regulatory network of an organism provided by the characterization of the wild-type global transcriptome across a wide range of conditions is complementary to more classical studies analyzing particular mutants . The greatest asset of such an approach is its unbiased nature , which does not focus on preselected regulatory circuits and conditions . Simultaneously , it allows comprehensive and precise mapping of all transcriptome parts such as transcription units , non-coding RNA species , and transcription start sites . Taking the aforementioned B . subtilis data set as an example , the approach provides at least three useful pieces of information that jointly contribute to the discrimination between direct and indirect regulatory effects . First , the observed co-expression patterns can complement results obtained in more targeted experiments [20] . Second , the data facilitate detection of new regulatory RNA molecules [21] . Third , the detailed information on transcription units and transcription start sites facilitates the search for potential regulator binding sites [22] . This is particularly useful for the genome-wide identification of sigma factor regulons , since the bipartite degenerate motifs recognized by the sigma factors lie directly upstream of the transcription start sites . An unsupervised algorithm to identify and map these motifs by combining information from the DNA sequences and the condition-dependent activities of the detected promoters was developed recently [13] . Like B . subtilis , S . aureus is a low G+C Gram-positive bacterium but has a smaller genome ( ~2 . 8 Mbp ) than B . subtilis ( ~4 . 2Mbp ) and a markedly different partitioning of its promoter space since only three alternative sigma factors are encoded by its genome . In contrast , the B . subtilis genome encodes 17 alternative sigma factors , 14 of which are known to be activated in response to environmental conditions or during developmental processes ( http://www . subtiwiki . uni-goettingen . de;[23] ) . In S . aureus , aside from SigB which is the major and by far the most investigated alternative sigma factor , SigH and SigS have been described [24 , 25] . Several transcriptomic and proteomic studies have mapped the SigB regulon and revealed that both structure and function of this regulon seem to differ between B . subtilis and S . aureus [26–31] . In S . aureus , SigB is a member of a complex network of regulators controlling expression of multiple virulence factors [32] . The role of SigB during infection was analyzed in vivo using different S . aureus strains and infection models [33–37] , and a common theme seems to emerge in which SigB may contribute to host cell invasion and intracellular persistence of S . aureus [38–41] . Along with transcription initiation , transcription termination is an essential determinant of transcriptome architecture . Two pathways of transcription termination are known of which several aspects remain incompletely understood [42] . Intrinsic termination , universal to all bacteria , depends directly on the properties of the transcribed RNA sequence and does not require factors outside the elongation complex . The second pathway involves the protein Rho and coexists with intrinsic termination in the vast majority of bacteria [43] . Rho is an ATP-dependent helicase/translocase that loads onto the nascent RNA , moves 5’-3’ faster than the RNA polymerase , and provokes termination after hitting the elongation complex [44] . Unlike in E . coli , Rho is dispensable in B . subtilis and S . aureus [45 , 46] and many intrinsic transcription terminators are identified in their genomes [47 , 48] . In the present study we have analyzed the condition-dependent transcriptome of S . aureus HG001 by strand-specific tiling array hybridizations . This strain was derived from S . aureus NCTC 8325 , a model strain widely used in genetic and regulatory studies , but in HG001 , in contrast to its parent , the SigB-activating phosphatase RsbU is active [49] . The investigated experimental conditions ranged from optimal in vitro growth to interaction with host cells . The data thus obtained were analyzed in silico , including the systematic mapping of transcription units , annotation of non-coding RNAs , the classification of promoters according to their dependency on SigA and SigB , and the prediction of potentially new transcription factor target sites . In particular , a Fur-dependent sRNA postulated to represent the S . aureus functional analog of FsrA/RyhB was identified . Our findings contribute to a better understanding of the pathogenicity of this organism , in particular the complex regulation of genes encoding virulence factors and the adaptation of S . aureus to infection-mimicking conditions . Antisense RNAs were of particular interest because of the small number of alternative sigma factors present in S . aureus . This class of RNAs was indeed found to be relatively rare in S . aureus , overlapping only 6% of the annotated coding genes . Global analysis of the role of Rho-dependent termination in S . aureus revealed a remarkable overall increase in antisense transcription in the absence of Rho , which had an impact on expression of overlapping genes . Nonetheless , the lack of Rho triggered only slight changes to the growth behavior compared to the respective wild-type strain .
The transcriptome of S . aureus HG001 [49] was analyzed using 156 RNA samples taken under 44 different experimental conditions . Specifically , cells were grown in rich medium ( TSB ) , minimal medium ( CDM ) , cell culture media ( RPMI , pMEM ) , and in human plasma ( plasma ) ( Figure A in S1 Data ) . Samples were taken during exponential growth phase ( exp ) as well as 2 hours ( t2 ) and 4 hours ( t4 ) after entry into stationary phase . In addition , S . aureus was grown in the presence of the cationic antimicrobial peptide colistin ( colist ) and sub-inhibitory concentrations of the following clinically most relevant antibiotics: flucloxacillin ( fluc ) , vancomycin ( vanc ) , ciprofloxacin ( cipro ) , clindamycin ( clind ) , erythromycin ( ery ) , linezolid ( line ) , and trimethoprim-sulfamethoxazole ( T/Smx ) . Cell culture infection experiments were performed with the human bronchial epithelial cell line S9 and the human monocyte cell line THP-1 . Staphylococci internalized by eukaryotic host cells were isolated from samples taken 2/ 2 . 5 hours ( intTHP1-2h and intS9-2h ) and 6/ 6 . 5 hours ( intTHP1-6h and intS9-6h ) post infection . The following additional samples were taken: i ) non-adherent bacteria at multiplicity of infection ( MOI ) of 25 or 50 retrieved from the supernatant of S9 cells after 1 hour of infection ( nonad25-1h and nonad50-1h ) ; ii ) bacteria after 1 , 2 . 5 , and 6 . 5 hours of incubation in the infection medium at 37°C and 5% CO2 without agitation ( CO2-1h , CO2-2h and CO2-6h ) ; iii ) bacteria after 2 . 5 hours of anaerobic incubation in pMEM medium at 37°C ( anaer-2h ) ; and iv ) bacteria grown in RPMI medium with fetal calf serum ( FCS ) ( RPMI/FCS ) , the pre-culture condition for the THP-1 experiments . The S . aureus Expression Data Browser at http://genome . jouy . inra . fr/aeb/ provides the condition-dependent transcription profiles , mapping of transcription units and the new annotation of transcribed segments along the chromosome . Transcription profiles for selected genomic regions are presented in Fig 1 . For each annotated coding sequence ( CDS ) and newly discovered RNA feature ( see next section ) expression values for all samples were calculated ( S1 Table ) . Using a stringent signal threshold of 5-fold higher than the chromosome median [13] , a high proportion ( 2524/2836; 89% ) of annotated CDSs was expressed under at least one biological condition . Of these , 110 CDSs ( 3 . 9% of all CDSs ) were found to be always highly expressed , i . e . rank in the 30% most highly expressed CDSs under all the conditions tested ( S2 Table ) . To elucidate the main physiological adaptations caused by the biological conditions of our study , we conducted a Principal Component Analysis ( PCA ) . This approach allowed assessing the general relationships between the 156 RNA samples in terms of expression profiles composed of aggregated values for all annotated genes and newly discovered RNA features ( Fig 2A , Text E in S1 Data ) . The percentage of total variance captured by the successive axes revealed a major first axis ( 48 . 9% ) followed by minor axes of smoothly decreasing importance such that 67 . 3% of the total variance is captured with 3 axes , but 13 axes are needed to reach 90% . To account for most of the complexity of our data set ( 91 . 6% of the total variance ) , we examined axes 1 to 15 ( Fig 2A , Figure B in S1 Data ) . The first PCA axis separates the conditions predominantly according to the growth phase . While transition to stationary phase is certainly associated with massive changes in gene expression , the strong impact of the growth phase on total data variability was also expected from the study design , which included many samples from exponential and stationary phase . The interpretation of the other axes was based on how the position of the samples on an axis correlated with the expression of each gene and which genes contributed most to the definition of the axis ( correlations and loadings in S3 Table ) . We also compared how well the position on the axes summarized the whole expression profile of a given RNA sample through root mean squared errors ( rmse ) ( Figure B in S1 Data ) . Genes coding for several amino acid biosynthetic pathways displayed strong negative correlation coefficients with position on axis 2 , suggesting that it reflects amino acid availability . Strikingly , the RPMI stationary phase samples ( “RPMI-t4” ) were characterized by very low positions on this axis . Indeed , time-resolved measurements of extracellular metabolites of S . aureus strains during growth in RPMI medium revealed that amino acids are largely taken up during the exponential growth phase [50] . In the case of axis 3 , positive correlation with genes induced in response to anaerobiosis ( srrA ) and negative correlation with genes induced by oxidative stress ( sufS , mecA2 ) was observed , so that this axis might reflect the difference between aerobic and anaerobic conditions . This interpretation is supported by the position of the anaerobic growth condition ( anaer-2h ) on the axis 3 . S . aureus grown in the presence of sub-inhibitory concentrations of several clinically relevant antibiotics exhibited overall minor gene expression changes ( S4 Table ) . In addition to the PCA representation we displayed the expression profiles of selected reference genes for limitations in amino acids , iron or oxygen and of 47 virulence factors comprising adhesins , immunomodulatory proteins , toxins , and secreted enzymes [51 , 52] ( Fig 2B ) . Of note , PCA and expression profiles of reference genes clearly showed that the eukaryotic cell culture medium RPMI resembles the conditions S . aureus is faced with in human plasma ( plasma-exp and plasma-t4 ) , as illustrated by high expression levels of iron-regulated genes during growth in both conditions . The virulence factor genes showed a great diversity of expression profiles and all of them were expressed under at least one of the growth conditions ( Fig 2B , S1 Fig ) . After internalization by human THP-1 macrophages or S9 bronchial epithelial cells ( intTHP1 and intS9 ) high expression of genes involved in amino acid or iron acquisition and of many virulence-associated genes were observed ( S4 Table ) . Overall , the variance in the data set reflects environmental conditions encountered by S . aureus during colonization and infection such as changing amino acid , iron or oxygen availability . In each of the 156 tiling array profiles , we mapped the transcribed regions ( TRs ) as well as the positions of abrupt signal increases and decreases ( called up-shifts and down-shifts ) . The 1523 RNA 5’-ends ( S5 Table ) derived from the high-confidence up-shift positions are indicative of promoter sequences [13] . Downstream of these putative promoters , we delineated 1418 transcription units ( TUs ) . According to this list of TUs , approximately one-fifth ( 22% ) of the previously annotated CDSs can be transcribed from more than one promoter under the conditions tested ( S6 Table ) . The analysis also identified 1261 high-confidence signal down-shift sites ( S7 Table ) corresponding to the RNA 3’-ends , which were further examined in connection with dissecting the role of Rho ( see below ) . The TRs outside of annotated CDSs and RNA genes were assigned to 1192 RNA segments ( S1 to S1192 ) according to their structural relationship with neighboring genes ( Text F in S1 Data ) . Our classification illustrated in Fig 1 indicates in particular the positions within TUs: 5’ of the coding region ( 5’UTR ) , intergenic ( intra , inter ) , or 3’ of the coding region ( 3’UTR , 3’PT , 3’NT ) . Substantial complexity arises from incomplete transcription termination: the suffixes PT and NT indicate 3’UTRs following partial termination ( PT ) and 3’UTRs associated with lack of a termination site and slow decrease in signal intensity ( NT ) ; segments referred to as “inter” result from continuation of transcription into a downstream region located between two TUs . For the RNA features transcribed from their own promoter ( independently of annotated genes ) , two types of segments ( Indep , Indep-NT ) are also distinguished depending on the presence of a defined termination site . The complete results are available in S6 Table and summarized in Table 1 . A comparison of the expression levels of the different categories of RNA segments is shown in Figure C in S1 Data . Our study identified nearly all ( 48/50 ) of the ( predicted ) non-coding RNAs of S . aureus NCTC 8325 from the Rfam database [53] , including the generic RNAs 6S RNA , 4 . 5S RNA , tmRNA , RNase P , 33 cis-acting 5’-UTRs , and 11 small regulatory RNAs ( sRNAs ) including RNAIII [54] and SprD [55] . In addition , a multitude of non-coding RNAs of S . aureus has been predicted and/or experimentally identified by different global approaches , mostly for S . aureus N315 [56–62] . The RNA-seq based study by Beaume et al . [62] confirmed almost all non-coding RNAs from earlier studies [63] . We therefore referred to previously known non-coding RNAs of S . aureus by mapping the 186 intergenic transcripts , including 25 antisense RNAs ( ASRNAs ) , of N315 reported by Beaume et al . [62] onto the NCTC 8325 genome ( Text G in S1 Data ) . For 112 of 132 uniquely mapping transcripts our study detected a counterpart in the NCTC 8325 transcriptome ( S6 Table ) . The remaining 20 transcripts were not detected because their expression levels were either below the threshold value defining transcribed regions or these transcripts were absent from S . aureus NCTC 8325 , at least under the conditions tested . The 22 Indep or Indep-NT segments ( Table B in S1 Data ) which are not antisense RNAs or associated with predicted new CDSs and do not represent a cis-acting 5’-regulatory region ( Table C in S1 Data ) can be regarded as potential trans-encoded small regulatory RNAs ( sRNAs ) . Of these , three are generic RNAs ( tmRNA , 6S RNA and 4 . 5S RNA ) and 11 correspond to intergenic transcripts of N315 [62] classified as bona fide sRNAs . Searching against all experimentally confirmed sRNAs of S . aureus [63] ( Text H in S1 Data ) revealed that seven potential sRNAs ( S35 , S204 , S414 , S736 , S774 , S808 , and S1077 ) were not identified by previous studies . Two of them ( S736 and S808 ) exhibited high expression under all conditions and S1077 specifically during growth in RPMI medium; the expression of the other four genes was lower ( Figure D in S1 Data ) . Interestingly , expression of S414 reached its highest level during growth of S . aureus in human plasma , and S414 and S774 appeared further down-regulated in the stationary phase . Expression of these seven potential sRNAs was also examined by Northern blot analysis . For six of them ( i . e . S35 , S204 , S736 , S774 , S808 , and S1077 ) , the presence of a transcript with the predicted size was confirmed for exponentially growing and stationary phase cells in three cultivation media ( TSB , RPMI , pMEM; Figure E in S1 Data ) . The remaining sRNA , S414 , exhibited very low expression levels under all conditions tested in our study except for growth in human plasma . The identification of these new sRNA candidates will likely facilitate the identification of new components of the regulatory network of S . aureus since recent studies revealed important roles of sRNAs in the regulation of metabolism and virulence ( reviewed in [64] ) . ASRNAs accounted for 145 of the 1192 RNA features identified by our study ( Table 1 , S6 Table ) and occurred at a rate of 51 per Mbp . With respect to the coding genes , 5 . 6% ( 159/2836 ) of all GenBank annotated genes were overlapped by ASRNAs under the set of growth conditions applied and these genes showed a trend towards lower expression levels compared to all genes ( Figure C in S1 Data ) . A relatively small fraction ( 13% , 19/145 ) of the ASRNAs belonged to the group of RNA features exhibiting their own promoter , independent of annotated genes ( categories Indep and Indep-NT ) . In B . subtilis , using similar criteria to define ASRNAs but with a higher number of different biological conditions , the rate of ASRNAs was 100 per Mbp , the proportion of overlapped genes reached 13% , and RNAs classified as Indep and Indep-NT accounted for 21% ( 88/423 ) of the ASRNAs [13] . ASRNAs appeared thus less frequent and less often initiated from their own promoter in S . aureus than in B . subtilis . In previous transcriptomic and proteomic studies [26–31] , the assignment of genes to the SigB regulon was based on the comparison of expression levels in SigB-proficient strains versus strains lacking ( active ) SigB , which entails that not all of the proposed target genes are directly influenced by SigB . In addition , some regulon members might not be expressed in the particular growth conditions considered in these studies . By using an approach of promoter classification for genome-wide de novo identification of sigma factor regulons [13] , a binding site for SigA or SigB could be assigned to most ( 1412 , 93% ) of the 1523 S . aureus up-shifts identified in our study ( Fig 3 , detailed information including position and sequence of the sigma factor binding sites is reported in S5 Table ) . With respect to the other two alternative sigma factors of S . aureus , SigH and SigS , no potential binding sites could be assigned . This was not unexpected since the sigH gene is cryptic in the NCTC 8325 strain under standard conditions [65] and target genes of SigS have not yet been identified [25] suggesting that the S . aureus SigS regulon may be particularly small and/or active only in a narrow range of physiological conditions . A total of 145 promoters were classified as SigB-dependent . Their average activity profile is shown in Fig 2C . It appears that induction ratios of SigB-controlled genes in S . aureus are rather moderate ( ~10-fold ) when compared to B . subtilis ( ~60-fold ) [13] , mainly due to higher basal activity . The conditions of SigB activation seem also much less specific since the average activity of the SigB promoters is higher than the average activity of SigA promoters in 49% of our samples ( 9% in B . subtilis ) . Furthermore , unlike in B . subtilis , the predicted SigB promoters form distinct clusters in the promoter tree summarizing the pairwise correlations of promoter activities ( Fig 3 ) , which underscores a substantial diversity of activity profiles . While , in agreement with former studies [66 , 30] , the general pattern is an induction of SigB promoters in stationary samples ( cluster B7 ) , some SigB promoters are more specific for RPMI medium ( cluster B10 ) and others are not induced in this medium ( cluster B8 ) ( Figure F in S1 Data ) . Analysis of the promoter sequences of the three main SigB-related clusters showed characteristic features for the smaller clusters B8 and B10 , namely a lesser degree of conservation of the -35 region ( B8 ) or -10 region ( B10 ) and occurrence of a conserved AA motif upstream of the -10 region ( B8 and B10 ) ( Text I and Figure G in S1 Data ) . On average , activity was highest during stationary phase in TSB and CDM , but also occurred in the other growth media except for human plasma and not always associated with stationary phase , such as in CDM exponential phase samples ( Fig 2C ) . A recent proteome study reported the activation of SigB following internalization of S . aureus by S9 cells [40] . In our data we see a weak induction at the early time point after internalization ( 2 and 2 . 5 hours , respectively , post-infection ) by S9 epithelial cells and THP-1 macrophages which disappeared at the second time point ( 6 or 6 . 5 hours post-infection ) . It is also interesting to note that , in the promoter correlation tree , we find promoters predicted as SigA-dependent even in the clusters most enriched in SigB promoters ( B7 , B8 , B10 ) , pointing to the potential indirect regulation of these genes by regulators downstream of SigB . Alternatively , this observation might also suggest that similar expression profiles can be generated by different regulatory mechanisms . Based on the repertoire of transcription units defined by our study , 249 annotated protein-coding genes were found to be preceded by a SigB binding site , out of which 163 ( 65% ) were considered as SigB-regulated by ( one of ) the previous studies ( Table D in S1 Data ) . Thus , our study led to the discovery of 86 new SigB-controlled genes in S . aureus , which are involved in diverse biological functions . Among the predicted SigB regulon members were also the known SigB-dependent sRNA RsaA ( S210/S211 ) [58] involved in virulence factor regulation through repression of the transcription factor MgrA [67] and a newly identified Indep-NT ASRNA ( S22 ) that covers SAOUHSC_00056 encoding a putative AraC family regulator . Considering the ASRNAs , 12% ( 18/145 ) were identified as transcribed from SigB-dependent promoters , and the percentage dropped to 5% ( 1/19 ) for ASRNAs belonging to categories Indep and Indep-NT . In contrast , 75% ( 109/145 ) of the ASRNAs were identified as transcribed from SigA-dependent promoters . The remaining fraction consisted of ASRNAs that lacked an identified promoter . Interestingly , the proportion of ASRNAs identified as SigB-dependent in S . aureus is clearly lower than the total contribution of alternative sigma factors to antisense transcription in B . subtilis . In this organism 50% ( 213/423 ) of the ASRNAs were predicted to be transcribed by one of the alternative sigma factors and the percentage raised to 68% ( 60/88 ) for the ASRNAs classified as Indep or Indep-NT . Many of the ASRNAs in B . subtilis are transcribed from sporulation sigma factors that do not have counterparts in S . aureus . However , even SigB-generated ASRNAs occurred at lower rates in S . aureus than in B . subtilis ( 6 . 7 Mbp-1 versus 12 Mbp-1 ) , and this was much more pronounced for the subset of ASRNAs belonging to the categories Indep and Indep-NT ( 0 . 35 Mbp-1 in S . aureus vs . 3 . 8 Mbp-1 in B . subtilis ) . In contrast , SigA-dependent ASRNAs tended to occur at similar rates in the two organisms with 39 Mbp-1 in S . aureus vs . 57 Mbp-1 in B . subtilis and 5 . 7 Mbp-1 vs . 4 . 7 Mbp-1 for the categories Indep and Indep-NT . The comparatively low frequency of ASRNAs in S . aureus appears thus as the combined outcome of the small number of alternative sigma factors and of the small contribution of SigB to antisense transcription in this organism . Coordinated regulation of promoter activities is summarized in the promoter correlation tree and the associated clustering: 1242 up-shifts ( 82% ) belonged to 16 activity clusters with ≥15 members defined by a cutoff on average Pearson correlation set to 0 . 6 ( Fig 3 ) . The largest cluster ( B1 ) alone gathered 46% of all the up-shifts . We used the known information on transcription factor ( TF ) regulons to better understand the contribution of TFs other than SigB to the regulation underlying these correlations . In particular we relied on the experimentally identified and manually curated inferred binding sites of 47 TFs from the RegPrecise database [68] for the identification of additional potential TF binding sites ( TFBSs ) . This analysis allowed identification of 623 known or predicted TFBSs associated to a total of 470 up-shifts ( S8 and S9 Tables ) . These sites were unevenly distributed in the correlation tree ( Fig 3 ) . In particular , SigA-dependent promoters outside the largest activity cluster ( B1 ) were markedly more frequently associated with identified TFBSs ( 46% ) than SigA-dependent promoters inside this cluster ( 23% ) or SigB-dependent promoters ( 19% ) . Furthermore , each of the four smaller clusters of SigA-dependent promoters exhibiting the highest within-cluster correlation ( indicative of a low diversity of expression profiles ) was found associated with a particular TF: B3 ( 50 promoters ) with the master regulator of carbon catabolite repression CcpA , B5 ( 45 promoters ) with the global nutritional regulator of stationary phase adaptation and virulence CodY , B14 ( 32 promoters ) with the ferric-uptake regulator Fur , and B25 ( 21 promoters ) with the redox-sensing transcriptional repressor Rex . Average activity profiles for these four groups of promoters are shown in Figure F in S1 Data . For a number of regulons the MAST search allowed new predictions with strongly correlated expression profiles , in particular for Fur , Rex , CodY , and CcpA ( Fig 3 ) . For the Rex repressor involved in anaerobic gene regulation , 9 promoters were newly identified , of which 2 clustered with the 14 known Rex-controlled promoters in B25 . The potential new Rex targets associated with these promoters are two predicted membrane proteins of unknown function ( SAOUHSC_00146 and SAOUHSC_01133 ) . As a second example we looked at the Fur regulon for which 9 promoters with newly predicted binding sites were found in cluster B14 together with the majority of known Fur-dependent promoters . Fur is a global regulator of iron homeostasis , which generally represses genes for siderophore biosynthesis and iron transport under iron-sufficient conditions; in S . aureus , several iron uptake systems are known to be controlled by Fur [69 , 70] . Correspondingly , of 21 annotated genes associated with the 9 newly predicted Fur-regulated promoters in cluster B14 , 10 genes are implicated in iron/trace metal transport ( fhuD1 , opp-1 operon , mntABC ) or iron release from heme ( isdI ) . Of these , the mntABC operon encoding a manganese transporter is a potential new member of the S . aureus Fur regulon . For the other genes , Fur-dependent regulation has already been reported but with different localization of the Fur box ( Text J in S1 Data ) . TFBS prediction also revealed a potentially Fur-dependent non-coding RNA ( S596 ) with a size of ~180 nt that was also confirmed by Northern blot analysis ( Figure E in S1 Data ) located on the opposite strand of a short annotated CDS ( SAOUHSC_01422 , 66 amino acids ) of unknown function ( Figure H in S1 Data ) . Of note , annotation of SAOUHSC_01422 might be incorrect since short CDSs are notoriously difficult to identify . Indeed , an amino-acid level similarity search with blastp retrieves significant hits only with other hypothetical proteins of S . aureus and a few other Staphylococcus species . According to the SHOW CDS prediction software [71] the confidence probability associated with this putative CDS is also very low ( value of 0 . 18 ) . For these reasons we assume that S596 may be a trans-encoded sRNA rather than a cis-encoded ASRNA . Indeed , the occurrence and role of Fur-dependent sRNAs was reported for several bacterial species ( reviewed in [72] ) . Target prediction for S596 using CopraRNA [73] revealed enrichment of genes encoding iron-containing proteins and of genes with functions in cofactor metabolism . Potential targets of this sRNA also included arlRS encoding a virulence-associated two-component system ( Table E in S1 Data ) . Specific sequence elements , typically encoding a hairpin structure followed by a U-rich tract , direct dissociation of the RNA polymerase from the DNA template at intrinsic termination sites . Applying a 30 bp distance cut-off , these elements were searched using the TransTermHP software [48] . They were found for 67% of the 1261 identified high-confidence down-shifts ( Figure I in S1 Data , S7 Table ) suggesting that intrinsic , also known as Rho-independent , termination determines the 3’-end of a majority of the TUs with defined termination sites in S . aureus . Most down-shift sites were also found associated with predicted intrinsic terminators in B . subtilis , where the transcription termination factor Rho was shown to be involved in termination of a particular class of TUs lacking a defined 3’-end . These TUs were characterized by slowly decreasing expression , apparently due to the lack of an efficient intrinsic terminator ( categories 3’PT and 3’NT comprising 3’-extended mRNAs , and category Indep-NT ) [13] , and they often overlapped the antisense strand of annotated genes . In S . aureus , only 19 TUs lacked a defined termination site ( 3’NT and Indep-NT , Table 1 ) , which is strikingly less than the 120 TUs found in B . subtilis ( 6 . 7 per Mbp-1 vs . 28 . 5 Mbp-1 ) . The 3’PT and AS segments were also about twice less frequent than in B . subtilis ( 26 vs . 78 , 9 . 2 vs . 18 . 4 Mbp-1 for 3’PT; 145 vs . 423 , 51 . 4 vs . 100 . 3 Mbp-1 for AS ) . Intrigued by the very limited impact of rho-deletion on the growth of S . aureus [46] and by the low abundance of TUs that we could anticipate being targets of Rho-dependent termination , we decided to examine the role of Rho in this organism by comparatively profiling the transcriptomes of the wild-type and its isogenic rho-deletion mutant . Chromosomal regions with Rho-dependent changes in transcript levels were mapped by comparing the normalized tiling array transcription profiles of the Δrho mutant and the parental strain HG001 harvested during exponential growth and four hours after entry into stationary phase in TSB and RPMI medium . In both media , growth of the S . aureus Δrho mutant was almost identical to that of the parental strain , except reaching a slightly lower final OD ( Figure J in S1 Data ) . The Expression Data Browser at http://genome . jouy . inra . fr/aeb/ also provides the condition-dependent transcription profiles of the Δrho mutant . As anticipated , when examining the TUs belonging to the 3’NT and Indep-NT classes , it was observed that most of them ( 12/19 ) possessed 3’-extensions in the Δrho mutant relative to the parental strain ( Fig 4A . 1 ) , supporting the assumption that termination of this class of TUs depends on Rho as previously shown for B . subtilis . Of the remaining 7 TUs , 3 were not expressed in wild-type cells under the selected growth conditions and one exhibited higher expression levels in the mutant thus not allowing conclusions on the contribution of read-through to the observed 3’-extension . Nevertheless , extension of TUs lacking an intrinsic terminator ( 3’NT and Indep-NT ) accounted for only a very small fraction of the increase in transcript levels detected in absence of Rho and we therefore decided to analyze all chromosomal regions where normalized transcript levels were 4-fold higher in the Δrho mutant than in the parental strain in at least one of the four conditions ( Text D in S1 Data ) ( Table 2 and S10 Table ) . These individual regions were up to 38 Kbp long . Globally , the fraction of the chromosome up-regulated was largest during exponential growth ( RPMI-exp: 1 . 51 Mbp; TSB-exp: 0 . 91 Mbp ) and much smaller during stationary phase ( RPMI-t4: 0 . 54 Mbp; TSB-t4: 0 . 16 Mbp ) . Despite these differences in magnitude , the regions subjected to up-regulation were remarkably consistent between conditions: out of the 1 . 65 Mb ( distributed in 416 regions ) identified in at least one of the four conditions , as much as 92% ( 1 . 51 Mb in 358 regions ) were upregulated in RPMI-exp ( Table 2 ) . Importantly and expectedly , the predominant effect of Rho deficiency was clearly up-regulation of transcript levels; using similar criteria as for up-regulation we detected only 0 . 16 Mbp ( in 195 regions ) exhibiting down-regulation . We also noticed that the magnitude of the effect of the absence of Rho tended to be consistent with the expression level of rho in the S . aureus wild-type , which is higher during exponential growth than in stationary phase , particularly in TSB medium ( Figure K in S1 Data ) . Indeed , the expression level of rho probably reflects its importance that may itself well be a direct function of the global transcriptional activity . It was expected that most of the up-regulated regions in the Δrho mutant would result from extensions beyond the transcript 3’-ends due to read-through of Rho-dependent terminators . However , our analysis ( Text D in S1 Data ) revealed that the number of up-regulated regions due to read-throughs was indeed rather limited ( S7 and S10 Tables ) . For instance , in the condition of exponential growth in RPMI , where the effect of Rho deletion was most pronounced , only 59 out of the 358 up-regulated regions were linked to read-through transcription ( 53 ) or lack of an intrinsic terminator ( 6 ) ( Table 2 ) . Together , in the three conditions with the strongest effect of Rho deletion , we detected only 60 termination sites at which read-through transcription can be assumed to contribute significantly to higher downstream transcript levels in the mutant . Complete read-through occurred at only three termination sites . In most cases only a limited level of read-through in the absence of Rho was observed ( Fig 4A . 4 & 4A . 5 ) . Of note , these partial read-throughs were also observed at sites where intrinsic terminators are predicted . Besides read-through transcription or lack of an intrinsic terminator , another source of up-regulated regions in the Δrho mutant was the higher expression of coding genes sometimes followed by ( often long ) downstream extensions ( Fig 4A . 6 ) . These altered expression levels are likely to be indirect regulatory effects caused by Rho deficiency . Altogether , 180 genes were strongly ( more than 4-fold ) up-regulated in the mutant in at least one of the four growth conditions ( S11 Table ) . The highest number of up-regulated genes ( 148 ) was observed during exponential growth in RPMI , but no more than 45 of the 358 up-regulated regions could be considered as caused by the higher expression of coding genes ( Table 2 ) . Taken together , read-through transcription ( including extensions of TUs lacking a defined 3’-end in the wild-type ) or higher expression of coding genes could not account for more than one third of the up-regulated regions ( Table 2 ) . The largest group of Rho-dependent transcripts was indeed formed by antisense transcripts only detectable in the absence of Rho that could not be linked to the TUs identified in the wild-type ( Fig 4A . 2 & 4A . 3 ) . Globally , of the 1 . 65 Mbp covered by the 416 regions up-regulated in the Δrho mutant , only 11% corresponded to annotated genes or RNA segments detected in the wild-type , whereas 76% mapped to the antisense strand of annotated genes ( Table 2 ) . As much as 52% of the 2 . 37 Mbp of annotated genes was overlapped on the antisense strand . Often , long genomic regions were covered by antisense transcripts in the Δrho mutant as , for example , the complete prophages phi11 and phi12 that are each approximately 40 kbp long . In these regions , the increase in antisense transcript levels in the Δrho mutant was most pronounced during exponential growth in RPMI and TSB , conditions of low prophage gene expression . Antisense transcripts only detectable in the Δrho mutant correspond presumably to very short and/or unstable transcripts in the wild-type , which might be terminated with the help of Rho shortly after initiation from promoters that are thus normally cryptic . However , Rho inactivation did not induce additional strong defined up-shift sites comparable to typical promoters , as indicated by visual inspection of the transcription profiles and a systematic search for up-shifts in the mutant with the criteria applied for the initial mapping of the wild-type promoters . Instead , the patterns of transcription in the Δrho mutant seem shaped by pervasive low-level promoter activity . This raised the interesting question whether the action of Rho and/or this pervasive promoter activity is really more pronounced on the antisense strand or simply masked by the higher levels of normal transcriptional activity on the sense strand . During exponential growth in RPMI , where antisense up-regulation was the strongest , the median log2-ratio between the Δrho mutant and the wild-type was -0 . 13 ( no global up-regulation ) for the 292 annotated genes ( sense level ) with log2 expression signal ≤8 in the wild-type , as compared to 1 . 11 ( global up-regulation ) for the 2453 antisense transcripts of annotated genes with log2 expression signal ≤8 . Therefore , the absence of Rho seems to impact less on sense strands than antisense strands even after accounting for the potential masking effect of the coding transcripts ( Figure L in S1 Data ) . S . aureus has a genome markedly more A+T-rich ( 67 . 2% ) than B . subtilis ( 56 . 5% ) and E . coli ( 49 . 2% ) . We therefore wanted to examine to what extent different genome compositions may lead to a different rate of random occurrence of the TATAAT hexamer that corresponds to the canonical core of the -10 box for the housekeeping sigma factor ( SigA in S . aureus and B . subtilis , Sig70 in E . coli ) in the three genomes ( GenBank: CP000253 , AL009126 . 3 , U00096 . 3 ) . The TATAAT hexamer was indeed much more frequent ( 0 . 905 Kbp-1 ) in the antisense strand of protein-coding genes in the S . aureus genome than in the B . subtilis ( 0 . 332 Kbp-1 ) or E . coli genome ( 0 . 091 Kbp-1 ) . In each of these three genomes the TATAAT hexamer was also less frequent on the sense strand than on the antisense strand ( e . g . , 0 . 905 Kbp-1 vs . 0 . 479 Kbp-1 in S . aureus ) . This possibly reflects , at least partly , the fact that the hexamer TATAAT cannot start at the second position of a codon within a gene since it contains the TAA stop codon . The extent of differential abundances of the TATAAT hexamer between and within genomes seems thus consistent with the idea that nucleotide composition may contribute to shape the patterns of pervasive transcription initiation counteracted by Rho . Antisense transcription can change the expression of the overlapped genes . Therefore , we investigated the effect of elevated antisense transcription on sense transcript levels under Rho-deficient conditions . Indeed , of the 167 annotated genes most down-regulated ( log2-ratio≤-1 , q-value≤0 . 05 ) in the Δrho mutant during exponential growth in RPMI medium ( S11 Table ) , 153 ( 92% ) were overlapped by an up-regulated region on the opposite strand . Strikingly , down-regulation was detected mostly at loci where the level of antisense transcription is high compared to the sense level . In fact , the antisense strands reached higher levels than sense strands in the Δrho mutant for 73% of the 167 most down-regulated genes ( Fig 4B ) , and in most cases ( 59% of 167 ) the antisense levels in the mutant appeared even higher than the sense levels in the wild-type ( see medians in Fig 4B ) . We also analyzed more globally the levels of sense and antisense transcripts of all annotated genes in the wild-type and the Δrho mutant . Indeed , antisense transcription increased predominantly in the regions of low sense expression leading to a strong negative correlation between sense and antisense expression ( Pearson correlation coefficient r = -0 . 73 ) that was much weaker in the wild-type ( r = -0 . 30 ) , but also statistically significant ( p-value<10−15 ) ( Fig 4B ) . In particular the most highly expressed genes showed the lowest levels of antisense transcription in the Δrho mutant . This observation suggests that down-regulation of sense expression by antisense expression is mirrored by down-regulation of antisense by sense expression , the impact of which increases with the sense expression level . In principle , the increased transcript levels observed outside of annotated genes in the Δrho mutant based on the tiling array signals may originate from long RNA molecules or from overlapping small molecules resulting from degradation of longer transcripts [74] . To discriminate between these two hypotheses , we performed Northern blot analyses for six antisense-generating transcribed regions that appeared longer or only present in the Δrho mutant , mainly as a result of read-through transcription at TU ends . For all six antisense transcripts , the analysis confirmed the presence of large-size RNA molecules that were specific for the mutant samples ( Fig 5 , Figure M in S1 Data ) . In three cases , the size of the detected band suggested the presence of an intact transcript covering the complete region identified to be upregulated in the Δrho mutant . In a fourth case ( 3’PT transcript S931 ) , the obtained size matched the position of a marked drop in the tiling array signal . For a ~9 Kb long transcribed region downstream of S234 and a ~11 Kb long region downstream of S596 , Northern blot analysis detected transcripts with different sizes , all larger than 2 Kb . The example in Fig 5 shows the analysis of a read-through transcript downstream of SAOUHSC_00975 that faces a tricistronic TU ( SAOUHSC_00972 to SAOUHSC_00974 ) on the opposite strand using probes with specificity for SAOUHSC_00975 and for the antisense strand of SAOUHSC_00974 , i . e . the 3’-extension detected in the absence of Rho . With the first probe , the SAOUHSC_00975 mRNA with a size of ~0 . 5 Kb ( not expressed in stationary phase TSB samples in agreement with the tiling data ) and the longer read-through transcript with a size of ~2 . 5 Kb appearing in the Δrho mutant were detected . The second probe , specific to the antisense region , showed only the longer transcript .
Using a genomic tiling array approach , the transcriptome of S . aureus HG001 was systematically analyzed under a broad range of experimental conditions to allow for an extensive mapping of TUs , annotation of non-coding RNAs and further insights into the transcriptional regulatory network of S . aureus . Almost 90% of the annotated genes were expressed in at least one growth condition but only 110 CDSs ( 3 . 9% ) were always found to be highly expressed ( S2 Table ) , which is indicative of the richness of our data set . The 110 always highly expressed CDSs encompass genes encoding ribosomal proteins and translation factors ( 18 genes ) , enzymes of central carbon metabolism ( 14 ) , proteins involved in cell division and cell wall metabolism ( 10 ) , RNA polymerase subunits ( rpoA , rpoB , rpoC , sigB ) , and half ( 55/110 ) belong to the set of 351 genes of S . aureus NCTC 8325 identified as essential for survival and growth in vitro [75] ( S2 Table ) . They also comprise transcriptional regulators ( perR , rex , icaR ) , and proteins involved in oxidative stress management ( katA , ahpC , ahpF ) whose generally high expression might provide a molecular basis for the rather high level of oxidative stress resistance of S . aureus , a reflection of the frequent encounter of oxidative stress in the interaction with its host/ natural environments . The data established a detailed description of the transcriptional architecture of the bacterium . In particular , new RNA segments were classified according to their position in the transcript relative to neighbor genes and transcript ends . Most of the 3’-ends were associated with a predicted intrinsic terminator . Transcription units were delineated and their promoters assigned to sigma factor regulons . SigA or SigB binding sites could be assigned to 1412 of the 1523 transcription signal up-shifts detected , which led to the identification of 145 SigB-dependent promoters . In B . subtilis , 2935 promoters were classified according to their dependence on different sigma factors [13] and 170 ( 6% versus 10% in S . aureus ) were assigned to SigB , which controls the general stress regulon . A relatively small fraction ( about 12% ) of the genes supposed to be controlled by SigB in S . aureus [29–31] have homologous counterparts in the B . subtilis SigB regulon . Besides roughly 30% of genes with unknown function , the S . aureus SigB regulon contains genes involved in cell envelope composition , membrane transport processes , intermediary metabolism , and virulence . Our study identified 86 new protein-coding genes in the SigB regulon that are of particular interest for further investigation . Activation of SigB involves the same primary partner switching mechanism in S . aureus and B . subtilis where SigB is released from its inhibitory complex with the anti-sigma factor RsbW by the competitive binding of the unphosphorylated form of the antagonist protein RsbV to RsbW [76] . However , the two regulatory cascades leading to RsbV dephosphorylation in conditions of energy stress ( via phosphatase RsbP ) or environmental stress ( via phosphatase RsbU ) in B . subtilis are not conserved in S . aureus whose genome encodes neither RsbP nor the stressosome that controls the activity of RsbU [77] . How and if the activity of SigB is regulated in S . aureus is still not well understood . RsbU may be constitutively active making SigB activity sensitive to the availability of core RNA polymerase [78] . Our data show fundamental differences in the expression patterns of SigB-dependent TUs in S . aureus compared to B . subtilis . Unlike in B . subtilis , the induction of SigB-dependent promoters in S . aureus is not restricted to a narrow range of stress conditions but is instead generally associated with the stationary phase and perhaps a general redistribution of RNA-polymerase activity . Indeed , the average expression level downstream of SigB-dependent promoters was higher than for SigA-dependent promoters in half of the conditions of our study . In addition , the S . aureus SigB regulon exhibits a substantial basal activity in non-induced conditions not seen in B . subtilis where SigB-dependent promoters are strictly turned off in the absence of stress . It was also interesting to note that while genes of the SigB regulon grouped in a single specific expression cluster in B . subtilis , this was not the case in S . aureus where SigB-regulated genes exhibited a substantial diversity of expression patterns , some of which very similar to genes transcribed from SigA-dependent promoters . Altogether , these differences are certainly associated with distinct physiological roles of SigB in the two species as also suggested by the widely different gene content . In addition to searching for so far unknown SigB controlled genes and new insights into the regulatory role of SigB , we exploited our tiling array data set with respect to the prediction of new transcription factor target genes including the iron-responsive regulator Fur . This analysis identified an sRNA ( S596 ) supposed to be controlled by the Fur repressor , which is apparently a functional analog of FsrA/RyhB . It is predicted to repress , amongst others , the expression of genes encoding iron-sulfur-cluster containing proteins ( citB , fdhA , addB , ilvD , and miaB ) and heme biosynthesis enzymes ( ctaA and hemE ) as well as of tricarboxylic acid ( TCA ) cycle genes citZ ( encoding citrate synthase ) and sdhCA ( encoding succinate dehydrogenase subunits ) . Iron-responsive sRNAs exist in many bacteria including B . subtilis [79] and typically mediate an iron-sparing response including the down-regulation of TCA cycle genes as first described for E . coli RyhB [80] . In S . aureus , Fur-mediated regulation was also shown to involve changes in the levels of central carbon metabolism proteins; three TCA cycle enzymes ( aconitase CitB , succinate dehydrogenase subunit SdhA , and fumarase CitG ) were observed in lower amounts under conditions of iron starvation [81] . In addition , iron-responsive sRNAs are involved in regulatory processes beyond iron homeostasis , particularly in the regulation of virulence-associated genes in Gram-negative pathogenic bacteria ( reviewed in [72] ) . Our data highlight the diversity of expression patterns for virulence related genes across conditions . This observation reflects the functional heterogeneity of this pool of genes that encompasses biological functions such as cell adhesion , toxin production , and escape of the immune system . However , for the proteins classified as virulence factors , which often have multiple roles in pathogenesis , the knowledge of the exact function and regulation of their encoding genes is not always complete . Indeed , a complex regulatory network mediates the adaptation of S . aureus to the host during colonization and infection . In particular , expression of virulence factor genes is tightly controlled by multiple regulatory systems involving two-component systems ( SaeRS , Agr , ArlRS , LytRS , SrrAB ) , transcription factors ( SarA family regulators , Rot , MgrA , CodY ) , the alternative sigma factor SigB and sRNAs ( RNAIII , SprD , RsaA ) [82 , 64] . Within this regulatory network , the SaeRS system controls the expression of numerous genes , such as those encoding adhesins and toxins [83 , 84] and its impact on virulence gene expression during in vivo infection has recently been characterized [85] . The host signals known to activate the SaeRS system include H2O2 and sub-inhibitory concentrations of α-defensins [86] . The global view on the condition-dependent expression of virulence related genes pointed to interesting observations . A noticeably high number of virulence factor genes ( 37/47 ) , in particular SaeRS-dependent genes , were upregulated after internalization by human THP-1 macrophages and S9 bronchial epithelial cells , including eap , fnbA and fnbB ( Fig 2B , S4 Table ) . Extracellular adherence protein ( Eap ) and fibronectin-binding proteins ( FnbA , FnbB ) are major determinants facilitating invasion of host cells [87] . The eap gene was among the genes most highly expressed in internalized staphylococci . Several genes involved in evasion of host immune responses , in particular complement-mediated phagocytosis [88] , were most highly expressed during growth of S . aureus in human plasma: spa encoding the immunoglobulin binding Protein A and four SaeRS-dependent genes ( efb , sbi , chp , and scn ) . The Extracellular fibrinogen-binding protein ( Efb ) interacts with complement protein C3b and attracts fibrinogen to the surface of S . aureus , thus masking C3b and opsonizing antibodies from recognition by phagocytic receptors [89] . It was shown to block phagocytosis in plasma and in human whole blood . The secreted proteins Sbi , CHIPS , and SCIN are also required for survival of S . aureus in human blood [90 , 91] . The finding that efb , sbi , chp , and scn showed a partially different expression pattern compared to other SaeRS-dependent genes reflects the expression of virulence factors in adaptation to the host environment , suggesting the involvement of additional regulators . A recent cell culture infection study revealed the intracellular replication of S . aureus HG001 inside eukaryotic cells , using the human lung epithelial cell lines A549 and S9 and the kidney cell line HEK 293 [92] . In agreement with this result , overall gene expression patterns observed in the present study suggest that the physiological state of S . aureus internalized by human THP-1 macrophages or S9 bronchial epithelial cells ( analyzed up to 6 . 5 hours after infection ) is comparable to growing rather than stationary phase cells . More specifically , our data revealed that S . aureus is challenged with reduced amino acid availability and iron limitation upon internalization by these eukaryotic cells . Furthermore , the PCA results ( rmse and correlation coefficients for axis 7 , see Figure B in S1 Data and S3 Table ) pointed to the upregulation of transporter genes as already observed during internalization of S . aureus by A549 cells [93] , in particular for glycerol , glucose-6-phosphate and phosphate ( the latter specifically after internalization by S9 cells ) . From the expression of reference genes ( moderate level of induction of ldh1 , Fig 2B ) it also appears that S . aureus cells are faced with reduced oxygen availability upon internalization by THP-1 macrophages . In line with this observation , the proteome study by Surmann et al . [92] reported elevated levels of fermentation enzymes and the CydAB terminal oxidase in S . aureus HG001 internalized by eukaryotic cells . These responses indicative of a microaerobic environment inside host cells were , however , different among bacteria internalized by different cell lines; protein levels were significantly less increased during adaptation to S9 cells as compared to A549 and HEK cells . Previous studies suggested that antibiotics at sub-lethal concentrations can drive the development of resistant phenotypes [94] . In this context , it is interesting that the wide range of clinically relevant antibiotics that we tested ( clindamycin , erythromycin , linezolid , TMP-SMX , vancomycin , ciprofloxacin , and flucloxacillin ) evoked only very few significant transcriptional responses at sub-inhibitory levels ( S4 Table ) . In fact , the norA gene , which confers low-level resistance to fluoroquinolones [95 , 96] was even found to be down-regulated by ciprofloxacin . The latter is in line with previous findings where S . aureus was challenged with a lethal dose of ciprofloxacin [97] . Furthermore , none of the tested antibiotics caused enhanced transcription of genes for known drug efflux pumps of S . aureus , including norA , norB , norC , mepA , mdeA , sepA , sdrM and lmrS . These transporters were previously found to be upregulated in response to antibiotic challenges , and some were shown to play a role in drug resistance [98] . Nevertheless , the fluoroquinolone ciprofloxacin and the β-lactam antibiotic flucloxacillin did induce some changes in gene expression ( Figure N in S1 Data , S4 Table ) . Of note , the DNA-gyrase inhibitor ciprofloxacin induced transcription of various phage-encoded genes , which is consistent with previous observations where S . aureus was challenged with lethal concentrations of this antibiotic [97 , 99] . In contrast , in response to sub-inhibitory concentrations of flucloxacillin , phage 11 genes were down-regulated during stationary phase , and under the same condition , the transcription of several metabolic operons was significantly increased . In the presence of a sub-lethal ciprofloxacin dose , all structural genes of phage 11 were highly induced during exponential growth , which suggests the activation of this lysogenic phage . In addition , part of the genes of phage 12 and of the hlb-converting phage 13 was induced under this condition . The induction of phages is apparently linked to the DNA damage-induced SOS response [99] , since increased transcription of recA and lexA was also observed . In E . coli , activated RecA promotes the autoproteolysis of LexA , resulting in derepression of DNA-repair functions and inactivation of the phage lambda repressor cI [100] . Our findings show for the first time that also sub-inhibitory concentrations of this antibiotic trigger the SOS response , leading to prophage induction . In fact , because phages are effective facilitators of horizontal gene transfer [101–103] , induction of prophages via the SOS response might be one of the mechanism by which sub-lethal doses of antibiotics contribute to the evolution of resistances [94] . ASRNAs are less frequent and less often initiated from their own promoter ( categories Indep and Indep-NT ) in S . aureus than in B . subtilis where many ASRNAs were highly expressed only under specific conditions , such as sporulation or physical stresses . A detailed analysis of the composition of the two ASRNA repertoires revealed the origin of the difference: The smaller contribution of alternative sigma factors is the reason for the lower amount of ASRNAs and in particular ASRNAs belonging to the Indep and Indep-NT categories . Importantly , the lower number of ASRNAs detected in S . aureus cannot be interpreted as only a simple consequence of the higher number of alternative sigma factors in B . subtilis or the larger number of experimental conditions tested . Indeed , although the SigB regulon was expressed at high level in many of our experimental conditions , the rate of SigB-dependent ASRNAs per Mbp was markedly lower in S . aureus than in B . subtilis , whereas the rate of SigA-dependent ASRNAs was quite comparable . Consequently , the small number of 19 “independent” ASRNAs in S . aureus can be considered consistent with our initial interpretation that many B . subtilis ASRNAs may be byproducts of an extensive use of alternative sigma factors for condition-specific promoter recognition prone to generate spurious ( non-functional ) transcripts without major negative impact on fitness [13] . This potential source of ASRNAs is in fact largely absent in S . aureus where SigB and SigH ( which is not active in the strain used [65] ) are the only relevant alternative sigma factors and control of SigB activity appears less stringent than in B . subtilis . The global , i . e . genome-wide , cellular function of Rho has been almost exclusively studied in E . coli [104–106] in which it accounts for 20–50% of the termination sites [105] and has also been found involved in distinct regulatory mechanisms [107 , 108] . In S . aureus , we identified only 19 TUs with heterogeneous and often antisense 3’-extensions due to the complete absence of a defined termination site . Our results confirmed the Rho-dependence of this particular class of TUs already identified in B . subtilis [13] . Beyond these , a very limited number of TUs exhibited Rho-dependent termination resulting in read-through transcription and extensions beyond the transcript 3’-ends in the absence of Rho . Termination of protein-coding genes in S . aureus is therefore mostly independent of Rho . Nevertheless , a massive up-regulation of expression on the antisense strand of the protein-coding genes was found in an isogenic mutant deficient for the termination factor Rho , which substantiates the role of Rho in suppressing pervasive antisense transcription initiation . Previous studies in B . subtilis and E . coli had already revealed that Rho plays a major role in suppressing or limiting antisense transcription but Rho-dependent transcripts initiated from promoters undetected in control conditions represented only a limited number of loci [105 , 13] . Indeed , in these studies Rho was shown to predominantly act on a subset of TUs possessing Rho-dependent terminators . Furthermore , in B . subtilis , where Rho is also dispensable [45] , the impact of Rho deletion appeared comparatively limited to a much smaller number of loci ( 93 chromosomal regions comprising 367 genes expressed only in absence of Rho ) and resulted mainly from 3’-extensions of TUs with respect to the parental strain [13] . In E . coli , where rho is an essential gene , Rho-dependent transcripts were mapped by treatment with the Rho inhibitor bicyclomycin . Antisense transcription suppressed by Rho was identified for 1555 genes ( 34% of all genes ) and was shown to arise mostly ( ~60% ) from continuation of transcription at the end of genes into oppositely oriented downstream genes , but a substantial fraction ( ~40% ) was also generated by transcription from antisense promoters within genes , i . e . by extension of bona fide antisense RNAs [105] . The pattern of antisense transcription observed in S . aureus in absence of Rho is therefore very different from what was reported from E . coli and B . subtilis . Our comparison of the frequency of canonical promoter -10 box hexamer TATAAT between S . aureus , B . subtilis and E . coli suggests that pervasive antisense transcription from cryptic low level promoters may be directly linked to the higher A+T composition of the S . aureus genome . The precise mode of action of Rho has not been studied in Gram-positive bacteria , but what is known from Gram-negative bacteria suggests that Rho is particularly well suited to terminate transcription of ASRNAs since the absence of ribosomes may facilitate its loading and contact with the elongation complex . Interestingly , pervasive transcription initiation certainly also occurs on the sense strand [17] and probably also leads to untranslated transcripts . Nevertheless , we showed that rho deletion had less impact on the expression of the sense strand . The higher abundance of the TATAAT hexamer on the antisense strand could at least partly explain why Rho-dependent termination seems to target mostly antisense transcripts in S . aureus . In our experiments , considerably elevated antisense transcription was not associated with a strong growth inhibitory effect . In general , antisense transcription can have deleterious effects by changing the expression of the overlapped genes and by diverting cellular resources . With regard to the first aspect , a role in regulating the expression of their opposite genes has been established for a number of individual ASRNAs and can involve different mechanisms: transcription interference , transcription attenuation , modulation of mRNA degradation and ribosome binding ( for review , see [15 , 109] ) . Peters et al . [105] reported for E . coli that the increase in antisense transcription caused by the inhibition of Rho did not affect sense transcription . In contrast , our study revealed an effect of elevated antisense transcription on sense transcript levels in Rho-deficient conditions in S . aureus . Moreover , the mutant antisense levels of down-regulated genes were found to be mostly higher than the sense levels detected in the wild-type ( Fig 4 ) . This observation would be in line with a stoichiometric mechanism of destabilization of the sense transcripts by pairing with their antisense transcripts and degradation of the double-stranded products [74] . We also noticed that the most highly expressed genes showed the lowest level of antisense transcription . This second observation could result from the same mechanism , i . e . low level of antisense caused by degradation of the antisense after pairing with the sense transcript . Importantly , these results disclosing the context in which antisense transcription impacts on sense transcription directly suggest an explanation for the observation that rho deletion has no clear effect on the growth rate despite its role in control of pervasive antisense transcription: The genes whose expression tends to be higher ( in particular housekeeping genes ) are less impacted by antisense transcription . Our results obtained on wild-type and Rho-deficient S . aureus and the direct comparison to those obtained with the same technology on B . subtilis reveal additional pieces of information on the biological interpretation of pervasive antisense transcripts . Indeed , the data tend to indicate that the pattern of pervasive antisense transcription may be a simple by-product of genome and transcriptome characteristics such as: A+T-composition , multiplicity of promoter motifs recognized by sigma factors , and balance between the evolutionary forces of mutation , drift and negative selection whose stringency is presumably lower for condition-dependent promoters . From such a perspective , pervasive antisense transcription would not be the product of an evolution for a biological function either at the individual level ( e . g . cis-regulation of sense gene ) or at the global level . Furthermore , the data also disambiguate the notions of biological effect and biological function , since we show that pervasive transcription although certainly spurious would have an effect on sense transcription if not suppressed by specific mechanisms such as Rho-dependent termination . In the context of S . aureus research , the present study has provided a detailed inventory of transcription units and non-coding RNAs of S . aureus HG001 , along with a classification of SigA- and SigB-dependent promoters , and targets for major transcription factors . It is anticipated that this compendium , which can be queried through an online genome browser , will serve as a major lead for future studies on this important pathogen’s very diverse lifestyles inside and around the human host .
S . aureus was grown with shaking at 37°C in the various cultivation media and in human plasma . Samples were collected by centrifugation with half volume of killing buffer ( 20 mM Tris pH 7 . 5 , 5 mM MgCl2 , 20 mM NaN3 ) . Pellets were frozen in liquid nitrogen and stored at -80°C until RNA preparation . The details of the medium compositions are provided in the supplemental material ( Text A in S1 Data ) . Briefly , CDM ( chemically defined medium ) contains inorganic salts , glucose , citrate , FeCl3 , trace elements , vitamins and 2 mM of all 20 proteinogenic amino acids [110] . The cell culture media RPMI 1640 and MEM are synthetic media commonly used for the cultivation of eukaryotic cells that are also used for the pre-cultivation of bacteria in infection studies . The adapted cell culture medium pMEM supporting growth of S . aureus consists of HEPES-buffered MEM and contains amino acids in concentrations of ≥ 2 mM , except for asparagine ( 0 . 1 mM ) and methionine ( 1 mM ) [111] . Sub-inhibitory antibiotic concentrations were as follows: flucloxacillin 0 . 02 μg/mL , vancomycin 0 . 63 μg/mL , ciprofloxacin 0 . 10 μg/mL , clindamycin 0 . 01 μg/mL , erythromycin 0 . 05 μg/mL , linezolid 0 . 10 μg/mL , and trimethoprim-sulfamethoxazole 0 . 75 μg/mL . In these experiments , S . aureus was pre-cultured in TSB till early-exponential phase ( OD600 of 0 . 5 ) , after which the culture was diluted 10-fold using TSB supplemented with the respective antibiotics . For the experiments with S9 cells ( details in Text A & B in S1 Data ) , exponentially growing bacteria were diluted with MEM supplemented with 4% FCS thereby adjusting a MOI of 25 . After adding the bacteria to the host cell layer , cell culture plates were incubated for 1 hour at 37°C and 5% CO2 in a humidified incubator . During this time bacteria were internalized by the S9 cells . After 1 hour of infection , lysostaphin was added to kill remaining extracellular bacteria . After 1 . 5 and 5 . 5 hours of incubation ( 2 . 5 and 6 . 5 hours post infection ) samples were taken and internalized staphylococci were isolated for RNA preparation . For the experiments with THP-1 cells , bacteria were pre-grown in RPMI medium with FCS , added to the host cells and incubated at 37°C and 5% CO2 in a humidified incubator . The Δrho mutant was constructed according to the procedure described by Arnaud et al . [112] ( Text C in S1 Data ) . Total RNA was prepared by acid-phenol extraction after mechanical cell disruption as described previously [13] . The tiling array used in this study contains 383 , 452 probes covering both strands of the S . aureus NCTC 8325 genome with a tiling step of 18 nucleotides [113] . Synthesis and hybridization of labeled cDNA were carried out at Roche NimbleGen ( Madison , WI ) using the strand-specific method described before [114] . All experiments were performed in triplicate with RNA isolated from independent cultures . Tiling array data have been deposited in the NCBI’s Gene Expression Omnibus ( GEO ) database ( accession numbers GSE70040-43 ) . Northern blot analysis was carried out as described previously [115] . The digoxigenin-labeled RNA probes were synthesized by in vitro transcription ( IVT ) with T7 RNA polymerase and gene-specific PCR products as template . Primer sequences are listed in Table A in S1 Data . 5 μg of total RNA per lane were separated on 1 . 2% agarose gels . Chemiluminescence signals were detected using a ChemoCam Imager ( Intas Science Image Instruments , Göttingen , Germany ) . For sRNA analysis 2% agarose gels were used and fluorescent detection of biotin labeled probes was performed with the Odyssey CLx Imager according to the instructions of the manufacturer ( LI-COR Biosciences , Lincoln , NE , USA ) . Detection of new transcribed segments , 5’-ends ( signal up-shifts ) , 3’-ends ( signal down-shifts ) , delineation of TUs , and computation of gene expression values , were performed exactly as described for B . subtilis [13]; the main steps of these analyses are summarized below . For each hybridization , the log2 of the raw signal intensity along the genome was analyzed with HMMtiling [116] to obtain a smoothed trajectory and the positions of predicted breakpoints , accounting for random noise and differences in probe affinity as characterized by hybridization of genomic DNA [117] . The repertoires of up-shifts and down-shifts corresponding to probable transcript 5’-ends and 3’-ends were established by combining high-confidence breakpoints ( credibility cut-off 0 . 99 ) from the different hybridizations . The precision in the mapping of up-shifts was determined previously [13] by a comparison of the up-shift positions detected in B . subtilis with transcription start sites mapped by a differential RNA-seq approach [118] , which revealed that the resolution is within the range of the tiling step with a tendency to have up-shifts slightly upstream ( median of 12 bp in B . subtilis ) of the actual transcription start site . New transcripts ( i . e . unannotated in GenBank: CP000253 ) were detected where the lower boundary of the 95% equal-tailed credibility interval for the smoothed trajectory reached 10-fold the chromosome median . These segments were further split according to breakpoints to avoid aggregation of regions with different transcription levels and extended on their 5’ and 3’ extremities according to a more permissive expression cut-off ( 5-fold the chromosome median ) to avoid over-segmentation in regions with expression levels close to the 10-fold cut-off . Promoter activity was measured as the smoothed signal downstream the position of the corresponding up-shift and a promoter tree was built by hierarchical clustering based on estimated pairwise correlation coefficients . Downstream each up-shift , a transcription unit ( TU ) was defined as the maximum continuous region where the expression level remains at least 5-fold higher than the chromosome median before dropping below this level or encountering another up-shift in at least one RNA sample . Aggregated log2-scale expression values for annotated genes and newly detected segments were obtained as the median of the smoothed signal for probes lying entirely within the considered region . For most analyses gene-level values were quantile-normalized to make them more comparable between hybridizations . A detailed description of the methods used to analyze the Δrho-mutant data is available in Text D in S1 Data . These included probe-level normalization and differential expression analysis to detect up-regulated and down-regulated regions . Briefly , normalization of whole-genome transcription profiles was performed by fitting a quantile-normalization transformation on the aggregated expression values computed for the repertoire of expression segments and applying this transformation on the smoothed probe-level data genome-wide . Contiguous probes exhibiting up- or down-regulation at the specified fold-change and false discovery rate cut-offs were reported as differentially expressed regions . The classification of promoters based on the presence of sigma factor binding site motifs around the up-shifts ( -60bp , +40bp ) was performed with the software ‘treemm’ [13] that also takes into account expression profiles across hybridizations . This analysis allowed positioning of the sigma factor binding sites with bp-level resolution . Other transcription factor binding sites ( TFBS ) were searched with MAST v4 . 9 . 0 [119] using position weight matrices built from known binding sites . For this purpose , we retrieved from the RegPrecise database v2 . 1 [68] the manually curated binding sites across Staphylococcaceae for the transcription factors listed for S . aureus N315 . For WalR and GraR , not present in RegPrecise , we used the binding sites listed in [113 , 120 , 121] . The resulting position weight matrices were used as queries in MAST searches against the database of the sequences around the up-shifts ( -100bp , +50bp; E-value cut-off 1 ) . In keeping with the orientations of binding sites listed for S . aureus in RegPrecise we considered only the occurrences with the same orientation as the up-shifts , except for WalR for which we took both strands into account . We compared the position of signal down-shifts to predictions of intrinsic terminators available at http://transterm . cbcb . umd . edu/tt/ that were made from the sequence alone with the software TranstermHP [48] . The S . aureus Expression Data Browser at http://genome . jouy . inra . fr/aeb/ can be accessed through the study website http://genome . jouy . inra . fr/aeb/supplementary_data . html . The website also provides links to access the data sets deposited in GEO ( records GSE70040-43 ) .
|
The major human pathogen Staphylococcus aureus can survive under a wide range of conditions , both inside and outside the human body . The goal of this study was to determine how S . aureus adapts to such different conditions and , additionally , we wanted to identify general factors governing the staphylococcal transcriptome architecture . Therefore , we performed a precise analysis of all RNA transcripts of S . aureus across experimental conditions ranging from in vitro growth in different media to internalization by eukaryotic host cells . We systematically mapped all transcription units , annotated non-coding RNAs , and assigned promoters controlled by particular RNA polymerase sigma factors and transcription factors . By a comparison with data available for the related Gram-positive bacterium Bacillus subtilis , we made key observations concerning the abundance and origin of antisense RNAs . Intriguingly , these findings support the view that many antisense RNAs in a bacterium like B . subtilis could be byproducts of spurious promoter recognition by condition-specific alternative sigma factors . We also report that the transcription termination factor Rho prevents widespread antisense transcription , presumably caused by pervasive transcription initiation in the A+T-rich genome of S . aureus . Altogether our study presents new perspectives on the biological significance of antisense and pervasive transcription in bacteria .
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2016
|
Staphylococcus aureus Transcriptome Architecture: From Laboratory to Infection-Mimicking Conditions
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Neisseria meningitidis serogroup A is the main causative pathogen of meningitis epidemics in sub-Saharan Africa . In recent years , serogroup W135 has also been the cause of epidemics . Mass vaccination campaigns with polysaccharide vaccines are key elements in controlling these epidemics . Facing global vaccine shortage , we explored the use of fractional doses of a licensed A/C/Y/W135 polysaccharide meningococcal vaccine . We conducted a randomized , non-inferiority trial in 750 healthy volunteers 2–19 years old in Mbarara , Uganda , to compare the immune response of the full dose of the vaccine versus fractional doses ( 1/5 or 1/10 ) . Safety and tolerability data were collected for all subjects during the 4 weeks following the injection . Pre- and post-vaccination sera were analyzed by measuring serum bactericidal activity ( SBA ) with baby rabbit complement . A responder was defined as a subject with a ≥4-fold increase in SBA against a target strain from each serogroup and SBA titer ≥128 . For serogroup W135 , 94% and 97% of the vaccinees in the 1/5- and 1/10-dose arms , respectively , were responders , versus 94% in the full-dose arm; for serogroup A , 92% and 88% were responders , respectively , versus 95% . Non-inferiority was demonstrated between the full dose and both fractional doses in SBA seroresponse against serogroups W135 and Y , in total population analysis . Non-inferiority was shown between the full and 1/5 doses for serogroup A in the population non-immune prior to vaccination . Non-inferiority was not shown for any of the fractionate doses for serogroup C . Safety and tolerability data were favourable , as observed in other studies . While the advent of conjugate A vaccine is anticipated to largely contribute to control serogroup A outbreaks in Africa , the scale-up of its production will not cover the entire “Meningitis Belt” target population for at least the next 3 to 5 years . In view of the current shortage of meningococcal vaccines for Africa , the use of 1/5 fractional doses should be considered as an alternative in mass vaccination campaigns . ClinicalTrials . gov NCT00271479
Sub-Saharan African countries in the “Meningitis Belt , ” situated between Ethiopia and Senegal , face epidemics of meningococcal meningitis almost every year [1] . Following the current World Health Organization ( WHO ) recommendation , mass vaccination campaigns with polysaccharide meningococcal vaccine are implemented solely to control the spread of the epidemic [2] . Until recently , Neisseria meningitidis serogroup A has been the main organism causing those epidemics , while other serogroups play a minor epidemiological role . Following W135 outbreaks in Saudi Arabia in 2000 and 2001 , cases of N . meningitidis serogroup W135 were reported in Burkina Faso in 2001 , resulting in the first large W135 epidemic in that country in 2002 [3] , [4] . This outbreak raised serious concerns regarding the availability of a vaccine protecting against that serogroup , i . e . , a tetravalent A/C/Y/W135 polysaccharide vaccine ( PSV ) . Mass vaccination of the population in Burkina Faso with the tetravalent PSV was not possible because of the global shortage in supply , in addition to its cost . In 2003 , GlaxoSmithKline began producing a trivalent A/C/W135 polysaccharide vaccine for approximately USD1 . 50/dose , which was used in Burkina Faso in another epidemic the same year [5] . Since then however , availability and affordability of the tetravalent or trivalent polysaccharide vaccines remain uncertain every year . The production of the bivalent A/C polysaccharide vaccine has been considerably reduced since 2005 and the quantity of vaccines to be produced in the next 3 to 5 years is uncertain [6] , [7] . In case of simultaneous large outbreaks in different countries , the supply of meningococcal PSV for the coming meningitis seasons is unlikely to be sufficient to cover vaccination needs ( Perea W . , WHO , personal communication , March 2008 ) . Conjugate meningococcal vaccines , are not expected to be available and affordable in large quantities to cover the need for Africa over the next several years [7]–[9] . The current dose of the licensed tetravalent PSV developed in the 1970s contains 50 µg of each polysaccharide component . Studies in the 1970s and 1980s have shown that lower doses of polysaccharide were as effective as 50 µg in inducing bactericidal antibody levels that should be protective against disease in adults in the US [10]–[14] . To test if fractionate doses might also be protective in an African population and in younger age groups , we conducted a clinical vaccine trial in Uganda to evaluate the potential use of fractional doses of meningococcal tetravalent PSV to control disease outbreak caused by N . meningitidis . The study population selected for the trial was 2–19 years of age , i . e . , the population at highest risk of the disease and the primary target of mass vaccination campaigns in Africa during epidemics [15] .
The study design was a randomized , single-blind controlled trial . Three arms were defined in the trial: group 1 received a dose of 50 µg of each component of tetravalent PSV , i . e . , a full dose of the licensed vaccine; group 2 received a 1/5 volume of tetravalent PSV ( 10 µg of each component ) ; and group 3 received a 1/10 volume of tetravalent PSV ( 5 µg of each component ) . The study was conducted in the rural area of Kinoni , Rwampara County , Mbarara District , Uganda . This location was chosen on the basis of the following criteria: i , this area had not experienced recent epidemics of meningococcal meningitis; ii , the study population was considered to be stable; iii , the health subdistrict was considered a suitable site for this interventional study because it has a long-standing collaboration with Mbarara University , Department of Community Health . The recruitment of participants for the clinical trial was done on a voluntary basis . Volunteers aged 2–19 years old were recruited in proportions matching the Ugandan age distribution of the 2–19 years old extracted from the “2002/03 Uganda National Household Survey . ” Volunteers were residents of Mbarara district , living within a 15-km radius of the vaccination site , with no plans of moving from the area during the study period . Community awareness meetings were held with local leaders and field workers from the study team , who then went house to house to get a list of people who were willing to participate . Participants came to the study site on a planned date . Refusal rates were not recorded in order to avoid unnecessary pressure on the communities . This study aimed to demonstrate non-inferiority in the immune response of doses corresponding to 1/5 and/or 1/10 of the amount of the full dose of a licensed A/C/Y/W135 polysaccharide vaccine ( Menomune , Sanofi Aventis ) and to evaluate the tolerability of these vaccinations . The primary endpoint was the proportion of responders defined by immunogenicity criteria at four weeks after vaccination based on SBA titers . The secondary endpoint considered the IgG response ( Elisa ) . The sample size was calculated by choosing a one-sided 0 . 05 level of significance and power of 80% . Expecting equal proportions of responders in all groups given the vaccine being 80% , and assuming a non-inferiority margin of 10% , this gave a required sample size n of 198 persons in each group . Because the reference group ( full dose ) was used for two comparisons , a correction of ( ) was applied [16] , bringing that group to 280 . The calculations have been performed using nQuery Advisor . Following consent and a clinical examination , each subject was randomly allocated to one of the 3 dosage groups . The allocation schedule was computer-generated , using a block randomization method , stratified by age group ( 2 to 4; 5 to 9; 10 to 14 and 15 to 19 years ) . The researchers responsible for seeing the volunteers allocated the next available number on entry into the trial . The vaccination was given subcutaneously using low-volume syringes ( 0 . 5mL BD Micro-Fine insulin syringes ) , by the same nurse throughout the study , without participant knowledge of the dosage received . A single dose vaccine Menomune vial was used per volunteer , numbered with the study number and stored after vaccination . A full dose injection corresponded to 0 . 5ml of the vaccine , 1/5 of the dose corresponded to 0 . 1ml and 1/10 of the dose to 0 . 05ml . Volunteers were observed for 1 hour following vaccination for adverse events . Safety and tolerability data were collected for all volunteers during the 4 weeks following the injection . Safety data were collected during weekly interviews . The intensity of the adverse events was evaluated by clinicians , members of the study team and classified as “mild , ” “moderate , ” or “severe” using the Common Toxicity Criteria ( CTC ) grading ( http://ctep . cancer . gov/reporting/CTC-3 . html , US National Cancer Institute ) . Serum samples ( 10 mL of whole blood ) were collected from each volunteer immediately before vaccination and 4 weeks later , stored at −80°C from the trial to the laboratories . Assays were carried out blinded at the Norwegian Institute of Public Health ( NIPH ) . Immune responses to the different doses of the TPSV were analyzed in serum bactericidal assays ( SBA ) and enzyme-linked immunosorbent assays ( ELISA ) . SBA was performed against four target strains of the A , C , W135 , and Y serogroups: A: F8238 ( 4/21:P1 . 20 , 9 ) ; C: C11 ( 16:P1 . 7-1 , 1 ) ; W135: M01240070 ( NT:P1 . 18-1 , 3 ) ; and Y: M00242975 ( 2a:P1 . 5 , 2 ) . Heat-inactivated test sera were diluted 2-fold in microtiter plates ( starting at serum dilution of 1:4 ) and incubated for 60 min with bacteria and baby rabbit complement ( Pel-Freeze ) before plating onto agar plates [17] . Colony-forming units were counted ( Sorcerer colony counter , Perceptive Instruments ) , and bactericidal antibody titers were expressed as the reciprocal of the final serum dilution giving ≥50% killing compared with controls ( inactive complement/no test serum ) . External quality control of SBA measurements was performed by Manchester Health Protection Agency ( HPA ) by analyzing in parallel approximately 10% of samples taken before vaccination and four weeks later . IgG antibodies to each separate polysaccharide A , C , Y , and W135 were measured in ELISA as described by Carlone et al . [18] and modified according to Joseph et al . using the CDC 1992 standard ( NIBSC code 99/706 ) [19] . Tonsillo-pharyngeal samples were collected from the volunteers before vaccination and four weeks later . The technique and results of this carriage study are published elsewhere [20] . Volunteers found to be carriers of N . meningitidis of a homologous serogroup at any time between the vaccination and four weeks later were excluded from the analysis of response to that polysaccharide . For computational purposes , titers <4 were assigned a value of 2 . A subject with SBA titer ≥128 was defined as putatively protected [21] . The Modified Intention To Treat ( MITT ) population included all randomized and exposed subjects with a defined SBA titer before vaccination and four weeks later . The Per Protocol ( PP ) population excluded subjects from the MITT presenting protocol violation . Some immunogenicity measures were not planned and described in the statistical analysis of the protocol . For the benefit of the study , the scientific committee coordinating the trial suggested additional statistical analyses: i , the principal criteria to define a responder was reinforced , as not only a 4-fold or greater increase in antibody titer between pre- and post-immunization sera , but also an SBA titer ≥128 four weeks after vaccination; ii , we also considered an exploratory population of the MITT , namely the “non-immune population” before vaccination , defined as individuals with SBA titers <128 before vaccination , which is considered the threshold of non-immunity [21]–[25] . Baseline characteristics were summarized by treatment groups using descriptive statistics ( Geometric Mean Titer [GMT] and Geometric Mean Concentration [GMC ) ] were used for the analysis of the SBA titers and IgG concentrations ) . McNemar's test was used to compare matched pair titer data before vaccination and four weeks later . The proportion of adequate responses in each group was expressed as a percentage ( “response to vaccine rate” ) . A 95% confidence interval was calculated for the observed difference in response proportion ( full versus fractional dose ) , and if the upper limit was <10% , the fractional dose was considered non-inferior to the full dose . These analyses were performed on MITT , PP , and non-immune subsets of the MITT . We performed a logistic regression to look at the impact of age among responders by serogroup and by arm . Age was considered in two groups of interest ( ≤5 and >5 years of age ) knowing that in previous studies , eliciting an immune response under 5 was the most critical [11] , [26] . Data were double-entered using Epidata 3 . 0 ( The EpiData Association , Odense , Denmark ) . Statistical analyses were performed using STATA 9 ( College Station , Texas , USA ) . Written informed consent in the local language was obtained from the parents or guardians of every volunteer <18 years of age or by the volunteers themselves if >18 years . The study was approved by the Faculty Research and Ethics Committee of the Mbarara University of Science and Technology ( MUST ) , the MUST Institutional Review Board , the Uganda National Committee of Science and Technology , and the Regional Committee for Medical Research Ethics in Norway . The trial was registered at Clinicaltrials . gov ( NCT00271479 ) .
Between 5 July 2004 and 22 September 2004 , 763 volunteers from the Kinoni community in Mbarara , Uganda were screened ( Figure 1 ) . Among them , 750 volunteers were included , with 291 randomized to the full-dose vaccine arm , 225 to the 1/5-dose arm , and 234 to the 1/10-dose arm . The demographic and serological baseline characteristics of the population at inclusion before vaccination are displayed in Table 1 . For each serogroup , volunteers were not considered in the analyses if an SBA value was missing for either before vaccination or four weeks later . No differences were observed between arms for demographic and serological data . Natural immunity toward N . meningitidis serogroups A , C , Y , and W135 before vaccination in the study population was measured by the proportion of volunteers with SBA titers ≥128 before vaccination: 51 . 4% ( 382/743 ) for serogroup A; 22 . 6% ( 168/744 ) for serogroup W135; 6 . 2% ( 45/729 ) for serogroup C , and 2 . 3% ( 17/741 ) for serogroup Y . Protocol deviations leading to exclusion of population are described in Table 2 . The primary end point , i . e . proportions of responders per arm and per analyses are reported in Table 3 . For serogroup W135 , 94 . 4% ( 168/178 ) of the non-immune , vaccinated subjects in the 1/5-dose arm , and 97 . 2% ( 172/177 ) in the 1/10-dose arm , were responders , compared with 93 . 7% ( 207/221 ) in the full-dose arm . For serogroup A , 92 . 2% ( 94/102 ) and 88 . 3% ( 98/111 ) of non-immune vaccinees in the 1/5- and 1/10-dose arms , respectively , were responders , compared with 94 . 6% ( 140/148 ) in the full-dose arm . Non-inferiority was demonstrated for serogroups W135 and Y ( full dose versus each fractional dose in MITT analyses ) , but was statistically rejected for serogroups A and C ( Table 4 ) . When analyzing only the non-immune population , non-inferiority was also demonstrated for full versus 1/5 doses for serogroups A ( 2 . 4% [95% confidence interval , −3 . 9 to 8 . 8%] ) , W135 ( −0 . 7% [95% confidence interval , −5 . 4 to 3 . 9%] ) , and Y ( 2 . 6% [95% confidence interval , −4 . 1 to 9 . 3%] ) , but not for serogroup C ( 11 . 5% [95% confidence interval , 5 . 4 to 17 . 5%] ) ( Table 4 ) . When considering the response by age group ( logistic regression ) , children under 5 had a lower chance of positive response compared to older ones for serogroup W135 ( significant only for full dose arm ) , serogroup C ( significant for full dose and 1/5 dose arms ) and for serogroup Y ( significant for 1/10 dose arm ) ( Table 5 ) . For serogroup A , although not significant , fractional doses seem to elicit a better response in children under 5 . The secondary immunogenicity criterion based on ELISA data is reported on Figure 2 . For each serogroup and each dose of vaccine , the geometric means of IgG concentrations showed no difference between arms before vaccination but a significant difference four weeks later with full dose greater than both 1/5 and 1/10 doses . Statistically significant differences were observed between the vaccination and four weeks later for each dose and each serogroup ( p<0 . 0001 for all comparisons ) . A total of 158 volunteers reported at least one adverse event during the 4 weeks after vaccination ( 171 total adverse events , Table 6 ) . No significant statistical difference was observed among the three dose arms ( χ2 test , p = 0 . 42 ) . The most commonly reported adverse events were upper respiratory tract infections ( URTI ) ( 57% ) and malaria ( 20% ) . Five severe adverse events were recorded: one severe case of malaria , one severe episode of seizures , and 3 severe URTI , but these events were not considered to be related to the vaccination . Three adverse events considered “probably related” were reported and classified as mild ( 2 subjects with fever and 1 with headache ) . External quality control of the SBA titer measurements showed no significant difference with regard to responders for serogroup A ( McNemar pair matched test , p = 0 . 63 ) , serogroup C ( p = 0 . 06 ) , and serogroup Y ( p = 0 . 41 ) . For serogroup W135 , the difference was statistically significant ( p<0 . 001 ) .
SBA is the accepted correlate of protection for meningococcal disease . In the MITT analysis of this study , non-inferiority was demonstrated between full and 1/5 and 1/10 fractional doses of TPSV in SBA response against the meningococcal serogroups W135 and Y . Non-inferiority was only shown between the full and 1/5 doses for serogroup A in the pre-vaccination , non-immune population . Non-inferiority was rejected for serogroup C in all analyses . Safety and tolerability data were favourable , as observed with TPSV in other studies [27] , [28] . In analyzing the proportion of responders per serogroup , we observed a decline in response for serogroup A and C from the full versus 1/5 dose , and this decrease was accentuated versus the 1/10 dose . For serogroup A , which is the most important serogroup to protect against in sub-Saharan Africa , the response in the MITT analysis decreased from 86% to 77% . Several elements must be considered in the interpretation of these results . A notable proportion of volunteers ( 51 . 4% ) had high SBA titers against serogroup A prior to vaccination , presumably resulting from natural immunity . In demonstrating non-inferiority between the full and 1/5 dose groups in the non-immune population , the difference in responses occurred mainly in the naturally immune subgroup . These results suggest that the full dose may elicit higher increase in SBA titers for subjects with pre-vaccination SBA titers ≥128 compared with 1/5 of the dose . However , assuming that a post-vaccination SBA titer ≥128 is a proxy for vaccine efficacy , we believe that 1/5 of the dose induced an acceptable increase of SBA for non-immune populations , although it did not strictly meet the criteria we designed for the total population . When considering the response for children under five , overall fractional doses do not affect the chance of response compared to full dose . For serogroup A , the response could be possibly better in children under five with fractional doses , though the study was not powered to demonstrate this hypothesis . For all serogroups , the IgG concentrations decreased with fractional doses . However , the SBA titer/IgG ratios showed similar results between arms for all serogroups ( data not shown ) , indicating a higher proportion of bactericidal antibodies in fractional doses . This could be due to differences in antibody avidity , though this hypothesis would require further studies . In an epidemic response setting , the goal of a mass vaccination campaign is short term immunity-basically protection through to the end of the epidemic season . Therefore , longer duration of protection ( presumably predicted by higher titers ) is a less important issue . Licensed meningococcal polysaccharide vaccines are known to confer an immunity of short duration ( 2–3 years ) and are therefore not recommended in expanded vaccination programs [6] , [29] . But this characteristic may not impact the use of fractional dosing in a reactive mass vaccination campaign aimed at preventing further new cases during an ongoing epidemic . Study subjects in this trial were followed up to 2 years , and the duration of protection will be addressed later on . Several potential limitations of this study must be addressed . Tolerability data were excellent; however , the weekly visits between the vaccination and four weeks later may not have been optimal to capture adverse events often occurring in the first days after vaccination . HIV testing was not systematically performed . Considering the epidemiological indicators of HIV in the adult population aged 15–49 years ( HIV prevalence rate 6 . 7% [5 . 7–7 . 6] ) [30] , and the exclusion criteria of known or suspected cases in our study population , the impact of HIV is unlikely to be noticeable . Injections of fractional doses with “insulin syringes” were considered relatively simple to perform in the field for the 1/5 ( 0 . 1 mL ) dose , but the 1/10 ( 0 . 05 mL ) dose was more difficult to inject . Such difficulty may have hampered the delivery of the 1/10 fractional dose . This evaluation was based on the informal evaluation from the study team . Considering the absence of difficulties to inject 1/5 of the dose providing the use of appropriate syringes and training , health workers engaged in an outbreak response during an epidemic should not faced major problems to implement this vaccination . The unexpected high background rate of immunity to serogroup A in the study population has been a constraint to demonstrate the impact of the vaccination for this serogroup . Despite the fact that no large outbreak of meningococcal meningitis due to serogroup A had been declared in southern Uganda in the years prior to the study , it is likely that the strain was circulating in the region , following the outbreaks of serogroup A in neighbouring countries , Burundi and Rwanda in 2002 [31] . Quality control of the SBA titers showed satisfactory results for serogroups A , C , and Y . However , a discrepancy was found for the W135 serogroup . This discrepancy was found to be due to the use of a different strain between the two laboratories . Once repeated with same strain , there was no significant difference between the results of the two laboratories ( p = 0 . 31 ) . As the proportion of responders for serogroup W135 was the same in the two laboratories and the source of the discrepancy was identified , we believe that our overall results of serogroup W135 are validated . Baby rabbit complement was used in the SBA assays in accordance with international standard protocols to evaluate polysaccharide vaccines against meningococcal disease , but SBA with human complement might be more relevant to elucidate the immune response after disease and vaccination . Additional insight would be gained by assaying these sera in a human complement SBA assay , and such analyses are ongoing . The two prevailing serogroups that cause N . meningitidis epidemics in the African Meningitis Belt are A and W135 , and serogroups C and Y are not presently reported as the causal agent of meningitis epidemics in the region [6] . The WHO states that problems regarding the availability and affordability of protective meningococcal vaccines over the coming years need to be addressed urgently [6] . A risk-benefit analysis of the use of fractional doses should guide decision-makers . Similar strategies with other vaccines have already proved successful [32] . Assuming 90% , short-term protection by the licensed meningococcal polysaccharide vaccines , and a conservative protection of 80% using a reduced 1/5 dose , the same amount of resources invested in vaccine purchase would protect 4 . 4 times more subjects . Although the cost of immunization is not a primary interest of this strategy in the context of a global shortage , the use of a fractional dose would decrease the cost per person vaccinated by approximately half ( data not shown ) . While the advent of conjugate A vaccine will largely contribute to control serogroup A outbreaks in Africa , the scale-up of its production will not cover the entire “meningitis belt” target population over the next 3 to 5 years ( Laforce M . , Meningitis Vaccine Project , personal communication January 2008 ) . Considering the current shortage of meningococcal vaccines for Africa and the prevalence of serogroups A and W135 , the use of 1/5 fractional doses should be explored as an alternative strategy in mass vaccination campaigns .
|
Meningitis are infections of the lining of the brain and spinal cord and can cause high fever , blood poisoning , and brain damage , as well as result in death in up to 10% of cases . Epidemics of meningitis occur almost every year in parts of sub-Saharan Africa , throughout a high-burden area spanning Senegal to Ethiopia dubbed the “Meningitis Belt . ” Most epidemics in Africa are caused by Neisseria meningitidis ( mostly serogroup A and W135 ) . Mass vaccination campaigns attempt to control epidemics by administering meningococcal vaccines targeted against these serogroups , among others . However , global shortages of these vaccines are currently seen . We studied the use of fractional ( 1/5 and 1/10 ) doses of a licensed vaccine to assess its non-inferiority compared with the normal full dose . In a randomized trial in Uganda , we found that immune response and safety using a 1/5 dose were comparable to full dose for three serogroups ( A , Y , W135 ) , though not a fourth ( C ) . In light of current shortages of meningococcal vaccines and their importance in fighting meningitis epidemics around the world , we suggest fractional doses be taken under consideration in mass vaccination campaigns .
|
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2008
|
Immunogenicity of Fractional Doses of Tetravalent A/C/Y/W135 Meningococcal Polysaccharide Vaccine: Results from a Randomized Non-Inferiority Controlled Trial in Uganda
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Genetic disruption of the dystrophin complex produces muscular dystrophy characterized by a fragile muscle plasma membrane leading to excessive muscle degeneration . Two genetic modifiers of Duchenne Muscular Dystrophy implicate the transforming growth factor β ( TGFβ ) pathway , osteopontin encoded by the SPP1 gene and latent TGFβ binding protein 4 ( LTBP4 ) . We now evaluated the functional effect of these modifiers in the context of muscle injury and repair to elucidate their mechanisms of action . We found that excess osteopontin exacerbated sarcolemmal injury , and correspondingly , that loss of osteopontin reduced injury extent both in isolated myofibers and in muscle in vivo . We found that ablation of osteopontin was associated with reduced expression of TGFβ and TGFβ-associated pathways . We identified that increased TGFβ resulted in reduced expression of Anxa1 and Anxa6 , genes encoding key components of the muscle sarcolemma resealing process . Genetic manipulation of Ltbp4 in dystrophic muscle also directly modulated sarcolemmal resealing , and Ltbp4 alleles acted in concert with Anxa6 , a distinct modifier of muscular dystrophy . These data provide a model in which a feed forward loop of TGFβ and osteopontin directly impacts the capacity of muscle to recover from injury , and identifies an intersection of genetic modifiers on muscular dystrophy .
Muscular dystrophies are inherited diseases that cause progressive muscle wasting [1] . Many muscular dystrophies are caused by mutations in genes encoding for components of the dystrophin glycoprotein complex , which anchors the actin cytoskeleton of myofibers to their cell membrane , the sarcolemma . Loss of function mutations in the DMD gene cause Duchenne muscular dystrophy ( DMD ) , while mutations in the SGCG gene , which encodes the dystrophin associated protein γ-sarcoglycan , cause limb-girdle muscular dystrophy type 2C ( LGMD 2C ) [2 , 3] . Disruption of the dystrophin complex results in loss of membrane integrity , leading to chronic injury and necrosis of myofibers [4] . Detrimental remodeling , with replacement by fibrofatty tissue , leads to ongoing , progressive impairment of muscle function [1] . This pathological process begins with disruption of the sarcolemma , and mechanisms to enhance sarcolemmal repair may provide insight in possible therapeutic targets for treating muscular dystrophy . Disease progression in the muscular dystrophies is variable even in the presence of the same primary mutation , suggesting that secondary genetic variants , or genetic modifiers , can considerably impact the outcome of muscle wasting [5] . The effect of modifiers is evident in murine models of muscular dystrophy , where the same genetic mutation results in significantly different outcomes dependent on the genetic background of the mouse strain [6] . Dystrophin deficiency is modeled in mice by the mdx mutation , a premature stop codon in exon 23 of the dystrophin gene , while γ-sarcoglycan deficiency is modeled by mice lacking exon 2 of the Sgcg gene [3 , 7] . mdx and Sgcg mutations have been shown to cause muscular dystrophy with strain-dependent variable pathology , which is severe in the DBA/2J genetic background , intermediate in the C57/Bl6-Bl10 strains , and more mild in the 129T2/SvEmsJ ( 129T2 ) background [6 , 8 , 9] . Identification of genetic modifiers and their mechanisms of action is a useful approach to refine prognosis and potentially discover novel therapeutic targets . Several candidate modifiers act as extracellular agonists of signaling cascades , including osteopontin , encoded by the SPP1 gene , and latent TGFβ binding protein 4 ( LTBP4 ) . Osteopontin is a secreted glycoprotein that signals through integrin and CD44 receptors [10] . SPP1 expression is highly upregulated in affected muscles of humans and animals with muscular dystrophy [11–19] . Genetic loss of Spp1 in mdx mice correlates with greater strength , less fibrosis and milder pathology , as compared to control mdx littermates [13] . Moreover , Spp1 ablation has been linked to a shift in macrophage polarization towards a regenerative phenotype in mdx muscles [20] . In humans with DMD , a single nucleotide polymorphism ( SNP ) in the SPP1 promoter ( GG/TG ) correlates with increased grip strength and later loss of ambulation compared to patients with the more prevalent SNP ( TT ) , especially in DMD individuals who are steroid treated [19 , 21 , 22] . Some genetic cohort studies have not shown this same effect [23 , 24] . The manner in which the SPP1 SNP affects osteopontin expression with disease progression is complex , and it is unclear in which SPP1-expressing cell type ( s ) this modifier SNP acts . Ltbp4 was identified as genetic modifier of several pathologic traits in the Sgcg mouse model , including sarcolemmal damage and fibrosis [25] . Latent TGFβ binding protein ( LTBP4 ) is an extracellular protein that binds TGFβ , releasing it upon proteolysis of its hinge region [26] . The LTBP4 modifier also correlates with differential outcomes in humans with muscular dystrophy [21 , 23 , 24] . In mice , the “risk” Ltbp4 allele encodes a shorter hinge region that is more susceptible to proteolysis , and this risk allele is found in the DBA/2J strain correlating with more severe muscular dystrophy . In contrast , most mouse strains including 129T2 and C57 substrains have the protective Ltbp4 allele encoding a longer hinge region that is more resistant to proteolytic cleavage . Overexpression of the protective Ltbp4 allele in the mdx mouse reduces fibrosis and promotes muscle growth [26] . However , the specific molecular effects of protective and deleterious Ltbp4 alleles on sarcolemmal resealing and repair are still unknown . Intriguingly , it has been shown that the Spp1 promoter is susceptible to TGFβ-driven transcriptional activation [27 , 28] . In mesenchymal cells , osteopontin signaling activates Tgfb1 transcription via the myeloid zinc finger 1 ( MZF1 ) transcriptional factor [29 , 30] . These data support a potential interaction between these two modifiers , Spp1 and Ltbp4 , in muscular dystrophy . Examining the combinatorial effects of genetic modifiers requires a large population , which is challenging for a rare human disorder like DMD . Here we asked whether genetic manipulation of osteopontin and Ltbp4 impacts sarcolemmal resealing and repair . To specifically address this question , we relied on optimized conditions of sarcolemmal micro-injury , and real-time detection of sarcolemmal damage and repair cap formation in isolated live myofibers [31 , 32] . Laser-mediated injury results in larger sarcolemmal damage in dystrophic myofibers than in wildtype myofibers using age- and background-matched conditions [33] . We found that both osteopontin and Ltbp4 modify sarcolemmal repair in wildtype and dystrophic myofibers . Furthermore , we documented how osteopontin and the deleterious Ltbp4 isoform converge in a feed-forward TGFβ signaling loop that correlated with transcriptional repression of annexin genes and impaired sarcolemmal repair . In addition , we dissected the relative impact of the different alleles of Ltbp4 and a third modifier Anxa6 on resealing and repair of injured sarcolemma in background-strain matched conditions . These results indicate that osteopontin and LTBP4 regulate a TGFβ signaling loop to modify sarcolemmal repair in normal and dystrophic muscle .
To gain insight in the role of osteopontin ( OPN ) in myofiber repair , we assessed the effect of recombinant osteopontin ( rOPN ) on sarcolemmal repair of isolated myofibers [32] . We tested the repair capacity after laser-mediated sarcolemmal injury and quantified two parameters in real time: ( i ) accumulation of the FM4-64 dye at the injury site , marking the extent of damage; ( ii ) formation of the repair complex monitoring GFP-tagged annexin A1 ( ANXA1-GFP ) protein [31] . DBA/2J wildtype ( WT ) mice were injected intramuscularly with 10μg rOPN at 1 , 3 and 5 days after electroporation with the plasmid encoding ANXA1-GFP . The activity of injected rOPN was confirmed by monitoring expression of Mmp2 and Mzf1 , factors known to be downstream of OPN [30 , 34] . Mmp2 and Mzf1 were increased 48 hours after rOPN injection while vehicle injection did not stimulate this response ( S1A Fig ) . Seven days after electroporation , live myofibers from treated and vehicle injected control muscles were subjected to laser injury . FM4-64 accumulation , which marks the area of injury , was greater in rOPN injected muscle at 240 seconds after laser injury , as compared to vehicle-treated myofibers ( Fig 1A ) . Moreover , the onset of the annexin A1 repair cap formation was significantly slower in rOPN-injected muscle than control myofibers , resulting in a significantly smaller annexin A1 cap size at end-point ( Fig 1B ) . Thus , intramuscular injection of DBA/2J WT muscle with rOPN exacerbated sarcolemmal injury and slowed formation of the annexin-containing repair complex . Genetic ablation of Spp1 in mdx mice results in decreased fibrosis and muscle pathophysiology in mdx mice [13] . We asked whether Spp1 loss had a measurable effect on sarcolemmal repair of mdx myofibers . To this end , we compared myofibers from 20 week-old mdx ( Spp1+/+; control animals ) and age-matched Spp1-deficient mdx ( mdx/Spp1-/- ) littermates for the extent of sarcolemmal damage after laser injury . Myofibers from both mice groups were electroporated with the ANXA1-GFP-encoding plasmid prior to harvest and laser-injury assay . Spp1-deficient dystrophic myofibers showed significantly reduced FM4-64 accumulation at the injury site over time , and a reduction of injury area at end-point when compared to control myofibers ( Fig 2A ) . We monitored annexin A1 repair cap appearance at the site of injury and observed faster rate of cap appearance in mdx/Spp1-/- compared to mdx control myofibers , resulting in a larger cap size at analysis end-point ( Fig 2B ) . Furthermore , expression levels of endogenous Anxa1 and Anxa6 , encoding the repair cap proteins annexins A1 and A6 , were significantly upregulated in muscle of mdx/Spp1-/- mice , as compared to littermate control animals ( S2A Fig ) . Moreover , improved sarcolemmal repair in isolated fibers was also reflected in in vivo findings in muscle . Spp1 deficiency correlated with lower levels of fibrosis , quantified as hydroxyproline content , in both quadriceps and diaphragm muscles , as well as with reduced levels of circulating creatine kinase , a marker of striated muscle damage ( S2B and S2C Fig ) , consistent with previous characterization of mdx/Spp1-/- mice [13] [20] . In addition to Spp1’s role in dystrophic muscle remodeling , osteopontin exacerbates injury in toxin-injured wildtype muscles [35] . To assess Spp1’s role in chronic and acute injury of dystrophic muscle , the tibialis anterior ( TA ) muscles of mdx and mdx/Spp1-/- mice were injected with cardiotoxin along the muscle axis , immediately after systemic delivery of Evans Blue Dye ( EBD ) . Each mouse received cardiotoxin in one muscle , while the contralateral remained uninjected . After three hours , muscles were harvested and injury extent was quantified as EBD-positive myofibers per muscle using serial cross-sections . There were fewer EBD-positive myofibers in mdx/Spp1-/- muscles than in mdx muscles , both under basal conditions and after toxin-induced injury ( Fig 3A and 3B ) . Thus , these data suggest that sarcolemmal repair is enhanced and muscle injury is reduced after genetic ablation of osteopontin . The Spp1 promoter is responsive to TGFβ signaling , and the TGFβ1 ligand increases Spp1 levels [27 , 28] . We therefore asked whether TGFβ signaling was altered in mdx/Spp1-/- muscles . To this end , we compared mdx/Spp1-/- and control mdx muscles for expression levels of TGFβ pathway genes and for enrichment of myonuclei positive for phosphorylated SMAD3 ( pSMAD3 ) , a known effector of active TGFβ signaling [36] . Quantitative PCR ( qPCR ) analysis of TA muscles showed that ligands , receptors and downstream factors of the TGFβ pathway , including transcriptional repressors Slug and Snail [37 , 38] , were significantly downregulated in mdx/Spp1-/- mice as compared to mdx ( Fig 4A ) . Immunofluorescence microscopy ( IFM ) of quadriceps and diaphragm muscles showed that the relative ratio of pSMAD3+ myonuclei was significantly reduced in both muscles of mdx/Spp1-/- mice compared to mdx control animals ( Fig 4B ) . Thus , genetic loss of Spp1 correlated with decreased TGFβ signaling in multiple mdx muscles . In non-muscle mesenchymal cells , OPN has been shown to stimulate TGFβ1 upregulation via integrin signaling and the transcriptional factor Mzf1 [29 , 30] . We hypothesized a feed-forward model , in which OPN sustains TGFβ signaling in muscle and its downstream transcriptional factors Slug and Snail , which bind E-box DNA elements of target genes ( Fig 5A ) [39] . Through sequence alignment , we identified a predicted E-box element ( GTCGAC motif ) [39] upstream of the transcriptional start site of Anxa1 ( -7382bp ) and Anxa6 genes ( -3504bp ) ( Fig 5B ) . We tested this pathway in C2C12 myoblasts as well as in the myofiber fraction from mdx muscles using qPCR and chromatin immunoprecipitation ( ChIP ) . C2C12 cells were exposed to 1μg/ml rOPN , and after 48 hours of rOPN treatment , both Anxa1 and Anxa6 were downregulated , while Slug and Snail were upregulated , as compared to vehicle-treated cells . These responses were reversed when C2C12 cells were co-treated with rOPN along with 10μM SB431542 , a chemical compound specifically inhibiting TGFβ signaling activation ( Fig 5C ) [40] . ChIP-qPCR analysis showed that occupancy of Anxa1 and Anxa6 E-box elements by the SLUG/SNAIL transcriptional complex was increased after rOPN treatment , but decreased in the presence of TGFβ inhibitor ( Fig 5D ) . In the myofiber fractions from mdx/Spp1-/- muscle where Anxa1 and Anxa6 expression were increased , these promoters had reduced occupancy of the E-box elements when compared to myofibers from mdx littermates ( Fig 5E ) . When C2C12 cells were co-treated with rOPN and 10μM PF573228 , a chemical inhibitor of the OPN-driven signaling leading to Mzf1-Tgfb1 axis activation [41] , there was blunting of rOPN-associated upregulation of Mzf1 , Tgfb1 , Slug , and Snail ( Fig 5F ) . Consistent with this , SLUG/SNAIL occupancy of Anxa1/6 E-box elements reverted to vehicle-like levels when cells were co-treated with rOPN and PF573228 ( Fig 5G ) . Finally , expression of Mzf1 was significantly lower in Spp1-deficient hindlimb and respiratory muscles than in control mdx muscles ( Fig 5H ) . Thus , excess OPN is associated with repression of Anxa1 and Anxa6 , and increased occupancy of their putative E-box elements by the transcriptional repressor complex SLUG/SNAIL . Repression by SLUG/SNAIL was associated with increased Mzf1 and Tgfb1 levels . Moreover , OPN-associated events were reversed in the presence of a chemical TGFβ inhibitor and were blunted by a chemical inhibitor of OPN signaling , thus supporting the hypothesis of a feed-forward circuitry that involves osteopontin and TGFβ pathways suppressing Anxa1 and Anxa6 and impairing sarcolemmal repair . In Sgcg ( γ-sarcoglycan ) or DMD ( mdx ) mice , the DBA/2J background exacerbates the dystrophic phenotype [6 , 9] . We sought to determine whether the difference in global outcomes associated with those genetic backgrounds was correlated with the efficiency of sarcolemma repair . To exclude effects associated with dystrophic remodeling , we tested WT mice from 129T2 and DBA/2J background using laser-induced sarcolemmal injury . DBA/2J myofibers showed more severe sarcolemmal damage than 129T2 myofibers ( Fig 6A ) . Annexin A1 cap formation , seen as ANXA1-GFP , appeared more slowly in DBA/2J than in 129T2 myofibers and resulted in smaller cap size at end-point ( Fig 6B ) . Although many genetic loci contribute to the DBA/2J background effect , DBA/2J mice feature the Ltbp4 risk allele , which is estimated to contribute to at least 40% of the variance of the muscular dystrophy phenotype in Sgcg mice [42] . RNA sequencing of WT and Sgcg muscle from the severe DBA/2J background was associated with a marked increase in Spp1 expression compared expression in the 129T2 background ( S3 Fig ) . We monitored gene expression changes relevant to the TGFβ pathway three days after cardiotoxin-mediated injury to the TA muscles of age-matched 129T2 or DBA/2J in order to assess the effect of genetic background . After muscle injury , the DBA/2J background was associated with increased expression of Tgfb1 , Slug , Snail , Spp1 , and Mzf1 compared to injured 129T2 muscle ( Fig 6C ) . Thus , the DBA/2J genetic background associated with increased sarcolemmal damage , and higher levels of osteopontin and TGFβ pathway genes . Muscle specific overexpression of the protective Ltbp4 allele ( L4mild ) in mdx mice reduces fibrosis and increases muscle size [43] . Conversely , expression of the risk human LTBP4 allele ( hL4severe ) exacerbates dystrophic remodeling in mdx mice [44] . We tested sarcolemmal damage and repair cap formation in myofibers from transgenic age-matched mdx mice overexpressing either the L4mild ( mdx/L4mild ) , or the hL4severe isoform ( mdx/hL4severe ) at 20 weeks of age . After laser-mediated sarcolemmal injury , the extent of sarcolemmal injury was smaller in myofibers of mdx/L4mild mice than from mdx control animals . Conversely , sarcolemmal damage was increased in mdx/hL4severe myofibers as compared to control muscles ( Fig 7A ) . Repair cap formation , monitored through GFP-labelled annexin A1 ( ANXA1-GFP ) , appeared faster in mdx/L4mild and slower in mdx/hL4severe myofibers than in mdx control myofibers . These trends associated with a bigger cap size in mdx/L4mild and a smaller cap size in mdx/hL4severe , when compared to mdx repair caps at end-point ( Fig 7B ) . Thus , the protective isoform with less TGFβ release associated with reduced sarcolemmal damage and faster cap formation , while the proteolysis-prone , risk allele with higher TGFβ release associated with increased damage and delayed repair cap assembly . Anxa6 , was also identified as a modifier of muscular dystrophy by its action on sarcolemmal repair itself [45] , and the DBA/2J background harbors the risk allele for Anxa6 . In order to discriminate the effects elicited by the Anxa6 and Ltbp4 genetic modifiers on sarcolemmal repair , we generated WT mice in the 129T2 background strain carrying the four homozygous combinations of mild and severe isoforms of Anxa6 and Ltbp4 ( A6mild/L4mild; A6severe/L4mild; A6mild/L4severe; A6severe/L4severe ) . We assessed sarcolemmal damage and annexin A1 cap formation after laser injury in myofibers from age-matched mice from the four cohorts . Muscles homozygous for either A6severe or L4severe had increased sarcolemmal damage , when compared to A6mild/L4mild myofibers . Moreover , the effect of the two severe isoforms appeared additive on the sarcolemmal damage phenotype , as A6severe/L4severe myofibers presented the highest levels of FM4-64 accumulation across the groups ( Fig 8A ) . Repair cap formation was also regulated by the additive effects of the severe isoforms . The A6severe isoform associated with smaller cap size at end-point , while the L4severe isoform associated with a delay in initial onset of formation , when compared to the A6mild/L4mild genotype . Similarly , the A6severe/L4severe correlated with onset delay and smaller size of the ANXA1 repair cap at end-point ( Fig 8B ) . Thus , the polymorphism affecting LTBP4 function modifies sarcolemmal damage and repair cap formation in WT myofibers , and its effects are additive with respect to the Anxa6 polymorphism . We next subjected mice from all four allele combinations to intra-muscular injury with cardiotoxin , targeting both TA and gastrocnemius muscles . To quantify the number of injured myofibers , mice were intra-peritoneally injected with EBD immediately before intramuscular toxin injection . Three hours after dye delivery , the number of dye-positive myofibers in injured muscles was comparably higher in mice with one severe allele , and the highest in mice with both severe alleles , with respect to A6mild/L4mild mice ( Fig 9A ) . Seven days after injury , the injury area at muscle mid-point and fibrotic scarring followed similar trends , as quantified by histologic analyses ( Fig 9B and 9C ) . Serum creatine kinase ( CK ) at 24 hours after injury was higher in the presence of either A6severe , or L4severe alleles , and the highest in mice with both severe alleles , as compared to A6mild/L4mild mice ( Fig 9D ) . Seven days after injury , muscle tissue was analyzed for gene expression trends . Transcriptional levels of Slug and Snail were significantly upregulated in the presence of the L4severe allele regardless of the A6 allele status . Expression of Anxa1 and Anxa6 was also downregulated in the presence of L4severe isoforms ( Fig 9E ) . Thus , Anxa6 and Ltbp4 isoforms modify the extent of damage in acute muscle injury in an additive fashion , and the severe isoform of Ltbp4 , characteristic of the DBA/2J genetic background , correlated with upregulation of Slug and Snail , and downregulation of Anxa1 and Anxa6 .
Genetic modifiers of muscular dystrophy influence outcome through multiple pathways . However , their combinatorial effects , and specifically whether they are additive , synergistic or even opposing in action is challenging to address at a human population level in a rare disorder . Here we utilized a surrogate endpoint , sarcolemmal repair , to begin to assess how osteopontin and LTBP4 modify myofiber repair through a convergent TGFβ pathway circuitry . Furthermore , we showed that upregulated OPN/TGFβ results in transcriptional repression of annexin genes , and this provides one possible means by which the OPN/TGFβ pathway contributes to impaired sarcolemmal resealing . Given the broad gene expression effects of the OPN/TGFβ pathway , we expect that multiple genes mediate the in vivo effect in muscular dystrophy . In vivo , in the absence of osteopontin , mdx muscle had fewer disrupted myofibers , which likely reflected this feed forward loop altering sarcolemmal stability , repair , and even muscle regeneration . Osteopontin and TGFβ signaling constitute a common marker of dystrophic muscle when compared to healthy controls [11–19 , 46–49] . Conversely , genetic manipulation to stifle both cascades reduces dystrophic pathology [13 , 36 , 43 , 50] . To date , these signaling pathways have been mainly associated with activation and tissue remodeling by immune cell infiltrates and resident fibroblasts [10 , 51] . These results indicate that osteopontin and TGFβ pathways act synergistically to directly influence the ability of myofibers to repair after sarcolemmal injury . There is an expected crosstalk among myofibers , fibroblasts , and immune cells during both acute and chronic injury , which further modifies dystrophic features . We found that the presence of either osteopontin or the deleterious form of Ltbp4 resulted in annexin gene repression and increased sarcolemmal damage . A limitation of the sarcolemmal repair assays used for this study is the use of electroporation to express GFP-tagged annexins in the presence of native annexins . To address this , we relied on electroporation of the same construct ( ANXA1-GFP ) in all different genetic contexts , and the results observed in the sarcolemmal repair assay paralleled the results seen when examining muscle injury in vivo , in both dystrophic and WT settings . Importantly , sarcolemmal repair assays were conducted in the presence of Ca2+ , as annexin repair cap formation is known to be Ca2+-dependent [32] . Further analyses in Ca2+-free settings , in combination with finer characterization of membrane composition , may discriminate Spp1- and Ltbp4-dependent effects on repair capacity and membrane mechanical stability , as recently investigated for the repair protein MG53 [52] . In both genetic settings , either Spp1 ablation or the deleterious Ltbp4 alleles , transcriptional regulation of Anxa1 and Anxa6 inversely correlated with expression levels of Slug/Snail and occupancy of the TGFβ-related SLUG/SNAIL repressive complex on the E-box elements upstream of Anxa1 and Anxa6 . These findings corroborate the hypothesis that both genetic modifiers contribute to a self-reinforcing , TGFβ-reliant loop in muscle , consistent with traditional observations of a feed-forward regulation of TGFβ signaling [37 , 38] . The deleterious VTTT haplotype in the LTBP4 gene correlated with more rapid disease progression in DMD patients , while the rs28357094 polymorphism in the SPP1 promoter has been reported as a disease determinant in some studies , but not in others [19 , 21 , 22 , 24 , 53] . However , it is still unclear whether the combination of deleterious polymorphisms at both loci significantly associates with worsened disease outcome . Given the rare nature of DMD , assembling sufficient cohorts for these genetic studies in humans may not be possible . Genome-wide screening for disease traits identified both Ltbp4 and Anxa6 as sarcolemmal damage modifying genes . The DBA/2J mouse strain carries both risk alleles and produces enhanced muscular dystrophy pathology in mice [25 , 45] . Anxa6 alleles regulate annexin repair cap size . However , LTBP4 content determines the efficiency of cap formation after injury , with the deleterious Ltbp4 alleles associated with delayed cap formation . These detrimental effects were additive in the presence of both alleles , and translated in additive effects on the in vivo response to muscle injury . In addition to the transcriptional regulation of annexin genes , it is possible that LTBP4-mediated TGFβ overload impacts sarcolemmal repair through post-transcriptional regulation and/or protein interactions . Ltbp4 genotype also appears to be a modifier of the extent of injury , which may reflect enhanced stability of the myofiber prior to injury . The protective LTBP4 allele in humans has been associated with delayed loss of ambulation in humans with DMD , and this effect was greater in the presence of glucocorticoid steroid regimen in those study cohorts [24] . Interestingly , steroid-associated additive beneficial effects were also reported for the SPP1 polymorphism in DMD patients [21] . We recently reported that glucocorticoid steroids , such as prednisone and deflazacort , improve sarcolemmal repair and annexin cap formation in normal and dystrophic muscle [54] . It has been suggested that glucocorticoid steroids act in muscular dystrophy by synchronizing an asynchronous repair milieu in muscular dystrophy [55] . These data suggest that genetic modifiers beyond SPP1/OPN may contribute to this disorganized repair process and support the development of agents to resynchronize this process . In summary , we now show that both osteopontin and LTBP4 directly modify sarcolemmal repair in myofibers of normal and dystrophic muscles . In the model , excess osteopontin and deleterious LTBP4 converge to sustain TGFβ-mediated gene expression changes , including the repression of annexins , and likely , many other repair genes . These findings indicate a direct role of those genetic modifiers in myofiber damage regulation and support their consideration for novel therapeutic avenues for treating dystrophic muscle .
Mice were housed in a specific pathogen free facility in accordance with Institutional Animal Care and Use Committee ( IACUC ) regulations . Euthanasia was performed through carbon dioxide or anesthetic gas inhalation followed by cervical dislocation and removal of the heart . All methods using living animals in this study were performed in ethical accordance with the American Veterinary Medical Association ( AVMA ) and under protocols fully approved by both the Institutional Animal Care and Use Committee ( IACUC ) at Northwestern University Feinberg School of Medicine ( protocol number ISO00000911 ) . Consistent with the approvals stipulated by these protocols , all efforts were made to minimize suffering . mdx and mdx/Spp1-/- littermates from a mixed BL/6-BL/10 background were previously described [13] . 129T2/SvEmsJ ( 129T2 ) and DBA/2J WT inbred mice were purchased from the Jackson Laboratory ( Bar Harbor , ME; Stock # 002065 and 000671 , respectively ) . Anxa6 and Ltbp4 alleles from DBA/2J background were bred on the 129T2 background by means of initial 129T2 x DBA/2J breeding , followed by seven generations of mating the compound heterozygotes with 129T2 mice . All mice used for experiments with DBA/2J Anxa6 and Ltbp4 alleles were conducted on littermates obtained from mating pairs of compound heterozygotes from the 129T2 background . Mdx mice bearing the BAC-hLTBP4 transgene or the HSA::Ltbp4129 transgene were previously described [43 , 44] . Both mdx transgenic lines were generated and bred on a mixed BL/6-BL/10 genetic background; the control cohort of mice for the experiments was created by pooling transgene-deficient littermates from both transgenic lines . Both females and males were used in 129T2 and DBA/2J mice experiments , while only males in experiments with mdx mice . Age of mice at the time of experiment was 8 weeks , unless otherwise specified . Mice were maintained on a 12 hour light/dark cycle and fed ad libitum . The plasmid encoding human annexin A1 with a carboxy-terminal GFP was obtained from Origene ( Rockville , MD; Cat# RG201569 ) . Myofibers from the flexor digitorum brevis ( FDB ) muscles were electroporated in vivo , as previously described in [56] with modifications described in [31] . Briefly , the footpad was injected with 10μl of hyaluronidase ( 8units ) ( Cat #H4272 , Sigma , St . Louis , MO ) . After 2 hours , the footpad was injected with 20μl of 2μg/μl endotoxin-free plasmid . Electroporation was conducted with following parameters: 20 pulses , 20 ms in duration/each , at 1Hz , at 100 V/cm . Recovery was allowed for seven days after electroporation to avoid electroporation-induced damage and to allow plasmid expression [57] . Individual myofibers were then explanted and isolated as previously detailed [31] . Live myofibers were ablated with a laser as described [31 , 32 , 45] . Briefly , myofibers were dissociated in PBS supplemented with 0 . 2% BSA and 4mg/ml collagenase type II ( Cat # 17101 , Life Technologies , Grand Island , NY ) at 37 degrees in 10% CO2 . Muscle was triturated ( 20–30 pipetting motions through edge-cut 1000μl filter tip ) after 60 and 120 minutes . Fibers were then seeded on MatTek dishes ( Cat # P35G-1 . 5-14-C , MatTek , Ashland MA ) in Ringers solution and , after 30 minutes , prepared for imaging by adding FM 4–64 dye ( T-13320 , Molecular Probes , Grand Island , NY ) to a final concentration of 2 . 5μm . Laser ablation and subsequent real-time imaging were performed at room temperature using a Nikon A1R laser scanning confocal equipped with GaSP detectors through a 60x Apo lambda 1 . 4 NA objective driven by Nikon Elements AR software . A single pixel set as 120 nm ( 0 . 0144 μm2 ) was ablated using the 405 nm laser at 100% power for up to 5 seconds . Images were acquired as follows: one image prior to damage ( 0 seconds; reference for relative fluorescence analyses ) , one image right after laser injury ( bleach point ) , 10 images every 2 seconds after injury , and then one image every 10 seconds for up to 240 seconds after injury . Quality control for myofibers selected for laser ablation relied on following parameters . Only myofibers adherent to the MatTek dish from end to end and not contracting during imaging were used . Imaged fibers were required to have intact sarcomeres and unruptured sarcolemma . The region of the myofiber selected for laser injury was required to be linear without visible deformation or peripheral nuclei . ANXA1-GFP fluorescence within the myofiber body at time 0 was required to be between 200 and 2000 relative light units ( RLUs ) , as per ImageJ analyses . Relative fluorescence from an 85μm2 circular region encompassing the lesion area and ANXA1 cap diameter ( perpendicular to myofiber axis ) over time were calculated from images acquired as described above ( FM4-64 and ANXA1 images acquired simultaneously ) , normalizing values to the pre-injury intensity . This method allows inter-group comparisons and reduces variability . Prism Graphpad was used to calculate averages , and values were normalized to the pre-bleach intensity ( F/F0 ) . All measurements were from n = 4 or 5 mice per group ( depending on experiment ) , with ≥10 myofibers per mouse ( total 40–50 per genotype or condition ) . Data analysis was conducted blinded to genotype/treatment group . Stack rendering of time course image sequences was conducted by using the “3D project” built-in feature of Image J with default parameters ( Projection method: Brightest Point; Slice spacing: 1 . 00μm ) . Stacks were then tilted by 10° in order to show extent of sarcolemmal damage or repair cap formation over time . rOPN was purchased as lyophilized powder ( Cat #441-OP; R&D Systems , Minneapolis , MN ) , resuspended as per manufacturer’s instructions , and stored at -80°C . Treatment of FDB myofibers with rOPN was conducted injecting the footpad with 10μg rOPN in 10μl PBS at 1 , 3 , and 5 days after electroporation . Laser injury was conducted seven days after electroporation . SB431542 and PF573228 ( Cat # S4317 and PZ0117 , respectively; Sigma-Aldrich; St . Louis , MO ) were resuspended in DMSO ( Cat #D2650; Sigma-Aldrich; St . Louis , MO ) and stored at -20°C . C2C12 myoblasts ( ATCC #CRL-1772; Manassas , VA; all experiments performed at passages 5–15 after ATCC batch thawing ) were cultured in DMEM supplemented with 10% FBS ( Cat #2442 ( lot #14E332; Sigma , St . Louis , MO ) 1% P/S ( Cat #15070; Thermo Fisher Scientific , Waltham , MA ) . On treatment start day , myoblasts at ~40% confluence were treated with different protein/compound combinations , or with equal amounts of vehicle , as diluted supplement in growth medium . Myoblasts were harvested for qPCR of ChIP-qPCR analyses 48 hours after treatment onset . Chemical compounds were used at a final concentration of 10μM , while rOPN was diluted to a final concentration of 1μg/ml [40 , 58] . Effectiveness of dosing in cells and muscles was tested in pilot experiments by means of qPCR analysis of Slug , Snail , and Mzf1 mRNA at 24 hours after treatment onset . Eight independent replicates of C2C12 treatment groups were used for analyses . Analysis was conducted blinded to treatment group . Cardiotoxin injury was performed by injecting 20μl of a 10μM cardiotoxin ( Cat #TXL1376-1; Accurate Chemical & Scientific Corporation , Westbury , NY ) solution in PBS in target muscles in sedated animals ( 3% isoflurane , 0 . 8 l/min O2 ) . Cardiotoxin was injected bilaterally in both tibialis anterior and gastrocnemius muscles . Cardiotoxin was released in the center of the muscle through the whole major axis , in order to have a homogenous area of injury at the center of the muscle . EBD staining ( 10mg/ml in PBS , sterile filtered; cat #E2129; Sigma-Aldrich; St . Louis , MO ) was injected in a dedicated cohort of toxin-injured mice intra-peritoneally immediately before toxin-injury . Muscles were collected for fluorescence microscopic analysis 3 hours after toxin-injury . Serum was analyzed as previously reported [59] from animals 24 hours after toxin injury . Serum creatine kinase was analyzed in triplicates for each mouse using the EnzyChrom Creatine Kinase Assay ( Cat # ECPK-100; BioAssay Systems , Hayward , CA ) following manufacturer’s instructions . Synergy HTX multi-mode plate reader ( BioTek® , Winooski , VT ) was used to collect data , expressed as U/ml . Analysis was conducted blinded to treatment group . Explanted muscles were fixed in 10% formaldehyde ( Cat #245–684; Fisher Scientific , Waltham , MA ) for histologic processing , or frozen in liquid nitrogen , inside pre-cooled Nalgene cryovials , and stored at -80°C for molecular analyses , or embedded in tissue freezing medium ( Cat #TFM-5; Triangle Biomedical Sciences , Durham , NC ) for IF analyses . Seven μm sections from the center of paraffin-embedded muscles were stained with hematoxylin and eosin ( H&E; cat #12013B , 1070C; Newcomer Supply , Middleton , WI ) and Masson’s trichrome ( Cat #HT-15; Sigma-Aldrich; St . Louis , MO ) . Injury area was quantitated from >30 non-consecutive sections per muscle . Analyses were conducted blinded to treatment group . Ten μm sections from the center of frozen-embedded muscles were collected on the cryostat ( chamber , -20°C; sample , -15°C; cat #CM1950; Leica , Wetzlar , Germany ) for immunostaining . At least 30 non-consecutive sections were analyzed per muscle per condition . Analyses were conducted blinded to treatment group . IF staining was performed using the following conditions: 4% PFA fixation ( 10 minutes , room temperature ) ; permeabilization with 0 . 2% Triton ( Cat #X-100; Sigma-Aldrich; St . Louis , MO ) , 1% bovine serum albumin ( Cat #A7906; Sigma-Aldrich; St . Louis , MO ) PBS ( 30 minutes , room temperature ) ; blocking in 1% BSA , 10% FBS PBS ( 30 minutes at room temperature ) . For pSmad3+ myonuclei detection , rabbit polyclonal primary antibody ( Cat #ab51451; Abcam , Cambridge , MA ) staining was counterstained with 1μg/ml WGA conjugated to AlexaFluor594 ( Cat #W11262; Thermo Fisher Scientific , Waltham , MA ) at room temperature for 1 hour , to outline myofibers . For EBD+ myofiber detection , sections were counterstained with 1μg/ml WGA conjugated to AlexaFluor488 ( Cat #W11261; Thermo Fisher Scientific , Waltham , MA ) at room temperature for 1 hour; nuclei were counterstained with 0 . 5μg/ml Hoechst PBS ( 45 minutes , room temperature ) . EBD is spontaneously fluorescent in the TRITC channel . Imaging was performed using a Zeiss Axio Observer A1 microscope , using 10X and 20X objectives . Gryphax software ( version 1 . 0 . 6 . 598; Jenoptik , Jena , Germany ) was used for brightfield pictures , while ZEN 2 software ( version 2011; Zeiss , Jena , Germany ) was used for immunofluorescence images . Quantitation of injury area and myofiber count was based on sections collected throughout the major muscle axis ( at least 10 sections per muscle per animal ) and was performed using ImageJ ( NIH ) . Frozen quadriceps muscles ( 100mg ) was used to measure hydroxyproline content , as previously described [25] . Analyses were conducted blinded to treatment group . Results were reported as mmol ( HOP ) /mg ( tissue ) . Total RNA was extracted by means of Trizol ( Cat #15596018; Life Technologies , Grand Island , NY ) from 30mg tissue as per manufacturer’s instructions . Reverse transcription used two μg of RNA with the qScript cDNA kit ( Cat #95048; Quanta Biosciences , Beverly , MA ) following kit’s instructions . cDNA was diluted 1:7 and 2μl was used per 10μl qPCR reaction . Each qPCR reaction contained 100nM primers and 5μl iTaq SybrGreen Mix ( Cat #1725124; Bio-Rad , Hercules , CA ) . The list of primers and sequences is provided in S1 Table . CFX96 RealTime System ( Bio-Rad , Hercules , CA ) was used to run the qPCR reaction ( 95°C , 15sec; 59°C , 60sec; 40 cycles ) and quantitate fluorescence . Relative fold change among biological groups was calculated using Pgk as internal normalizer . ChIP-qPCR was performed according to previously reported conditions [60] and adjustments [61] . Forty-eight hours after treatment , 106 myoblasts were collected , washed , fixed in 1% PFA . Fixation was quenched with 0 . 1375 mmol glycine ( Cat #G7126; Sigma-Aldrich; St . Louis , MO ) . After lysis of cells and nuclei , chromatin was sonicated for 15 cycles ( 30 sec , high power; 30 sec pause ) in a water bath sonicator set at 4°C ( Bioruptor 300; Diagenode , Denville , NJ ) . One μg chromatin was used for pull-down or for input control samples . The primary antibody ( anti-SLUG/SNAIL , cat #ab180714 , Abcam , Cambridge , MA ) were added at a 1:100 dilution in 300μl final volume , while shaking overnight at 4°C . Chromatin complexes were precipitated with proteinA/G beads ( cat #20421; Thermo Scientific , Waltham , MA ) . DNA was de-complexed with 0 . 07μg/μl proteinase K ( cat #19131; Qiagen , Hilden , Germany ) at 55°C and purified through QIAQuick PCR purification kit ( cat #28106; Qiagen , Hilden , Germany ) . qPCR amplification was conducted as described for gene expression analysis , with a dedicated thermal profile ( 95°C , 30 sec; 55°C , 30 sec; 72°C , 30 sec; 50 cycles ) . Results were expressed as % of raw expression of the respective input . ChIP-qPCR on isolated myofibers was performed as above , with the following adjustments before chromatin sonication . Freshly-isolated gastrocnemius muscle was finely minced and digested in 5ml/muscle of PBS supplemented with 1mM CaCl2 and 100U/ml collagenase II ( Cat # 17101 , Life Technologies , Grand Island , NY ) at 37°C for 1 hour with shaking . After filtration through a 40μm strainer ( Cat # 22363547 , Fisher Scientific , Waltham , MA ) , the unfiltered fraction ( enriched in myofibers ) was kept for further procedures . Separation of mononuclear fraction from myofibers in the filtered suspension was confirmed at a microscope . Myofiber lysis was performed in lysis buffer , using 700μl per muscle , with ~250μl 2 . 3mm zirconia/silica beads ( Cat # 11079125z , BioSpec , Bartlesville , OK ) . Lysis buffer consisted of 10mM HEPES ( pH 7 . 3; Cat # H3375 ) , 10mM KCl ( Cat # P9541 ) , 5mM MgCl2 ( Cat # M8266 ) , 0 . 5mM DTT ( Cat # 646563 ) , 3μg/ml cytochalasin B ( C6762; all reagents from Sigma , St . Louis , MO ) ; protease inhibitor cocktail ( Cat # 11852700 , Roche , Mannheim , Germany ) ) . Myofibers were homogenized at the Mini-BeadBeater-16 ( Cat # 607 , Biospec , Bartlesville , OK ) for 30 sec , then by rotating at 4°C for 30 min . Samples were then centrifuged at 3000g for 5 minutes at 4°C; pellet was resuspended in cell lysis buffer , as per described protocol [60] , supplemented with 3μg/ml cytochalasin B , and incubated on ice for 10 minutes . Nuclei were pelleted at 300g for 10 min at 4°C , and resuspended in 1ml 1% PFA for 5 min at room temperature . Fixation was quenched with 100μl of 1 . 375M glycine ( Cat # BP381-5 , Fisher Scientific , Waltham , MA ) . Nuclei were re-pelleted as before , and then processed following the described procedure [60] , as mentioned for myoblasts . However , all solutions were supplemented with 3μg/ml cytochalasin B during chromatin preparation and sonication , antibody incubation , and wash steps . Statistical analyses were performed with Prism ( Graphpad , La Jolla , CA ) . Tests used for statistical comparison depended on group number and normality test ( Pearson-D’Agostino ) . Typically , 2way ANOVA with Bonferroni multi-comparison was used to compare treatment or genotype effect on curves over time . When comparing >2 groups for one variable ( typically treatment , or genotype ) , 1way ANOVA + Bonferroni multi-comparison was used . When comparing two groups for one variable , unpaired t-test with Welch’s correction was used , in order to account for skews in standard deviation between groups . For ANOVA and t-test analyses , a P value less than 0 . 05 was considered significant . Data were presented as single values ( dot plots , histograms ) when the number of data points was less than 10 . In analyses pooling larger data point sets per group , Tukey distribution bars were used to emphasize data range distribution and histograms with error bars were used to emphasize shifts in average values . Analysis pooling data points over time were presented as marked line plots . Dot plots , histograms and marked line plots depict mean ± SEM . Box plots depict the Tukey distribution of the data pool: interquartile distribution; lower whisker , 25th percentile minus 1 . 5 times the interquartile range; upper whisker , 75th percentile plus 1 . 5 times the interquartile range .
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Genetic modifiers for muscular dystrophy have been identified through transcriptomic and genomic profiling in humans and mouse models . Two modifiers , Ltbp4 and Spp1 , encode extracellular proteins while a third modifier , Anxa6 , specifies a membrane-associated protein . Using a model of muscle injury , we assessed the interaction of these modifiers , identifying a feed forward loop between Ltbp4 and Spp1 that promotes TGFβ signaling . This feed forward loop is expected to contribute to the progressive nature of muscular dystrophy . We also evaluated the interaction between Anxa6 and Ltbp4 , identifying an additive effect of these two genetic modifiers .
|
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"signaling",
"signaling",
"cascades"
] |
2017
|
Genetic modifiers of muscular dystrophy act on sarcolemmal resealing and recovery from injury
|
Giardia duodenalis is prevalent in tropical settings where diverse opportunities exist for transmission between people and animals . We conducted a cross-sectional study of G . duodenalis in people , livestock , and wild primates near Kibale National Park , Uganda , where human-livestock-wildlife interaction is high due to habitat disturbance . Our goal was to infer the cross-species transmission potential of G . duodenalis using molecular methods and to investigate clinical consequences of infection . Real-time PCR on DNA extracted from fecal samples revealed a combined prevalence of G . duodenalis in people from three villages of 44/108 ( 40 . 7% ) , with prevalence reaching 67 . 5% in one village . Prevalence rates in livestock and primates were 12 . 4% and 11 . 1% , respectively . Age was associated with G . duodenalis infection in people ( higher prevalence in individuals ≤15 years ) and livestock ( higher prevalence in subadult versus adult animals ) , but other potential risk factors in people ( gender , contact with domestic animals , working in fields , working in forests , source of drinking water , and medication use ) were not . G . duodenalis infection was not associated with gastrointestinal symptoms in people , nor was clinical disease noted in livestock or primates . Sequence analysis of four G . duodenalis genes identified assemblage AII in humans , assemblage BIV in humans and endangered red colobus monkeys , and assemblage E in livestock and red colobus , representing the first documentation of assemblage E in a non-human primate . In addition , genetic relationships within the BIV assemblage revealed sub-clades of identical G . duodenalis sequences from humans and red colobus . Our finding of G . duodenalis in people and primates ( assemblage BIV ) and livestock and primates ( assemblage E ) underscores that cross-species transmission of multiple G . duodenalis assemblages may occur in locations such as western Uganda where people , livestock , and primates overlap in their use of habitat . Our data also demonstrate a high but locally variable prevalence of G . duodenalis in people from western Uganda , but little evidence of associated clinical disease . Reverse zoonotic G . duodenalis transmission may be particularly frequent in tropical settings where anthropogenic habitat disturbance forces people and livestock to interact at high rates with wildlife , and this could have negative consequences for wildlife conservation .
Giardia is a genus of parasitic protozoan that infects the small and large intestines of a broad range of vertebrate hosts [1] . Considered among the most common human intestinal protozoa , especially in the tropics [2] , G . duodenalis ranges in clinical severity from asymptomatic to highly pathogenic [3] . Both host factors ( e . g . nutrition , immunity , co-infection with other agents ) and pathogen factors ( e . g . strain , infectious dose ) are thought to contribute to the clinical severity of giardiasis [2] . G . duodenalis is also notable for cross-species transmission , including zoonotic transmission [3] , [4] . Molecular techniques have shed considerable light on this aspect of G . duodenalis ecology [5] . Sequencing of phylogenetically informative genes has , for example , revealed transmission among humans , dogs ( Canis familiaris ) , and cattle ( Bos taurus ) in Italy [6] , and among humans , cattle and mountain gorillas ( Gorilla beringei beringei ) in Uganda [7] . At present , six G . duodenalis “assemblages” ( A–G ) are recognized , infecting a range of mammalian hosts and likely representing as many distinct species [8] . Most studies that have applied molecular methods to G . duodenalis in wild mammals have found that samples fall into assemblages A or B , which characteristically infect people , concluding that the animal hosts involved may represent reservoirs of infection for humans ( e . g [7] , [9]–[13] ) . We conducted a cross-sectional study of G . duodenalis in rural western Uganda , near Kibale National Park , a location of high human-livestock-wildlife overlap and conflict [14] . We sampled people , livestock , and wild non-human primates associated with forest fragments outside of the protected areas of the park , where primates interact frequently and often antagonistically with people [14] , where we have documented increased rates of human-primate-livestock bacterial transmission [15] , and where we previously documented a G . duodenalis prevalence of 3 . 8% in primates using microscopy [16] . Our goal was to use molecular methods to assess the prevalence and cross-species transmission potential of G . duodenalis in this area , and to examine risk factors for infection and clinical disease .
Prior to data collection , all protocols were reviewed and approved by the Uganda National Council for Science and Technology and the Uganda Wildlife Authority , as well as by the Institutional Review Board of the University of Illinois and the Animal Care and Use Committee of the University of Illinois . Due to low literacy rates , oral informed consent was obtained by trained local field assistants and documented by witnessed notation on IRB-approved study enrollment forms . The study took place in Kibale National Park , western Uganda ( 0°13′–0°41′N , 30°19′–30°32′E ) , and in surrounding forest fragments . This habitat consists primarily of moist semi-deciduous and evergreen forest , between approximately 1 , 100 and 1 , 600 m in elevation [17] , [18] . Kibale supports an exceptionally high species diversity and density of primates [19] . The Kibale region is noted for its rapidly expanding human population and intensive human-wildlife ecological interaction and conflict [14] . This conflict is especially pronounced outside of the protected areas of Kibale , in remnant forest fragments that sustain small populations of primates [20] . For the present study , we focused on three such forest fragments , Bugembe , Kiko 1 , and Rurama , and the villages surrounding them . These sites , which are described in detail elsewhere [15] , range from approximately 0 . 7 to 1 . 5 km2 and contain small populations of monkeys ( between 4 and 60 individuals of up to three species; see below ) . Our previous investigations have shown that rates of human-primate-livestock bacterial transmission are elevated in these locations due to anthropogenic habitat disturbance related to timber harvesting , agriculture , and the collection of forest products ( e . g . firewood ) [15] . Primates inhabiting these fragments also have elevated prevalence of infection with parasitic nematodes and protozoa , including G . duodenalis [16] , [21] . In May and June , 2007 ( dry season ) , we collected fecal samples from two folivorous monkey species , the red colobus ( Procolobus badius tephrosceles; n = 30 ) and the black-and-white colobus ( Colobus guereza; n = 29 ) , and one omnivorous monkey species , the red-tailed guenon ( Cercopithecus ascanius; n = 22 ) , from undisturbed areas within Kibale National Park , as well as from the highly disturbed Bugembe , Kiko 1 , and Rurama forest fragments . We collected single fecal samples non-invasively from individual animals on 13 days , at the same time that we collected demographic information and behavioral observations , as previously described [15] . We sampled local human volunteers ( n = 108 ) and their livestock ( cattle , Bos taurus and B . indicus , n = 25; goats , Caprus hircus , n = 57; and sheep , Ovis aries , n = 7 ) in villages surrounding each forest fragment . People and livestock in these villages use forest fragments intensively for such purposes as firewood collection and grazing , respectively , thus increasing ecological overlap with primates [14] . People were selected from among willing volunteers within target households , which were chosen at random from households within 0 . 5 km from the forest fragment edge [15] . This protocol yielded multiple samples from the same households , but individual volunteers were sampled only once . Volunteers were instructed in the proper method for placing fecal samples into sterile cups , which were collected the following day . Livestock were sampled from households where human volunteers resided . As with people , multiple samples were collected from the same households , but individual animals were sampled only once . Fresh livestock feces were collected from the rectum using a sterile glove , or from the ground if the animal was observed to defecate , with care taken to avoid environmental contamination by sampling only those portions of the fecal material that had not contacted the ground . Fecal samples were transported to our field laboratory as soon as possible after collection ( within 6 hours ) . 1 ml of fecal material from each sample was homogenized with an equal volume of RNA-later nucleic acid stabilizing buffer ( Ambion ) and stored at −20°C in the field prior to transport to the United States . Concurrent with human fecal sample collection , a survey was administered to each participant . The survey focused on demography , gastrointestinal symptoms , patterns of land use , and interactions with animals during the four-week period prior to sample collection . The survey was administered in Rutooro ( the local language ) by trained field assistants who were also members of the local communities; response biases caused by the presence of foreigners were thereby avoided . DNA was extracted from 500 µl of fecal+RNA-later suspension using the FastDNA Spin Kit for Soil ( MP Biomedicals , Solon , OH ) , followed by an additional wash and ethanol precipitation in the presence of CTAB in order to remove potential PCR inhibitors [22] . Samples were tested for the presence of G . duodenalis DNA using a real-time PCR targeting the small subunit RNA gene on an ABI Prism® 7000 Sequence Detection System ( Applied Biosystems , Inc . ) , with primers , probe , and cycling conditions following published methods [23] . Samples were run in duplicate , using 1 µl of extracted DNA template per reaction . To infer genetic relationships among G . duodenalis from samples that tested positive by real-time PCR , we conducted conventional PCR amplification and direct sequencing of four G . duodenalis genes . Conditions were optimized for each locus separately using the Failsafe PCR System ( Epicentre Biotechnologies , Madison , WI ) according to the manufacturer's recommendations and based on published primers and protocols for each gene: ef1-α [24] , gdh [25] , SSU-rDNA [26] , [27] , and tpi [24] ( complete protocols are available upon request ) . PCR products were electrophoresed on 2 . 0% agarose gels containing 0 . 5µg/ml ethidium bromide in 1× Tris-acetate-EDTA buffer at 100 volts for 30–45 minutes at room temperature ( sub-cell model 192 electrophoresis system , Bio-Rad , Hercules , CA ) . Each well contained 25 µl of PCR product and 4µl 6× loading dye or 6 µl of 0 . 5 mg/ml GeneRuler 100-bp DNA ladder ( Fermentas , Glen Burnie , MD ) . Amplicons were visualized under UV light , and bands of the predicted sizes were excised for DNA extraction using the Zymoclean Gel DNA Recovery Kit ( Zymo Research , Orange , CA ) , according to the manufacturer's protocol . Following extraction , amplicons were sequenced in both directions on ABI 3730XL capillary sequencers located in the Roy J . Carver Biotechnology Center at the University of Illinois at Urbana-Champaign . Sequences were edited using the computer program Sequencher , Version 4 . 2 ( Gene Codes Corporation , Ann Arbor , MI ) and were queried against known sequences using BLAST [28] . Population genetic and phylogenetic analyses were conducted using the computer program MEGA4 [29] .
Real-time PCR detected G . duodenalis in 64 ( 23% ) of 278 total fecal samples ( Table 1 ) . Overall , the prevalence of G . duodenalis was higher in humans than in either non-human primates ( “primates” hereafter ) or livestock ( Table 1 ) . In humans , the prevalence of G . duodenalis was markedly higher in Rurama community than in either Bugembe or Kiko 1 communities ( Table 1 ) , and this difference was statistically significant ( odds ratio ( OR ) = 6 . 2; 95% Wald confidence limits 2 . 6–14 . 7; Fisher's exact P<0 . 001 ) . No similar differences were observed in the prevalence of G . duodenalis in livestock among these locations , however ( Table 1 ) . The prevalence of G . duodenalis in humans was higher in individuals 15 years or younger ( n = 62; 53 . 2% ) than in individuals between 16 and 75 years ( n = 45; 22 . 2% ) , and this difference was statistically significant ( OR = 4 . 1; 95% Wald confidence limits 1 . 7–9 . 7; Fisher's exact P<0 . 001 ) . Subadult livestock ( n = 24 ) harbored G . duodenalis at a higher rate ( 25 . 0% ) than did adult livestock ( n = 65; 7 . 7% ) , and this difference was also statistically significant ( OR = 2 . 7; 95% Wald confidence limits 1 . 1–14 . 7; Fisher's exact P = 0 . 037 ) , mirroring the trend in humans . We were unable to examine age as a risk factor for G . duodenalis infection in primates , due to the difficulty of determining the ages of individual wild primates . Data from survey responses ( 83 . 5% of people responding ) were used to identify risk factors for human G . duodenalis infection related to land use , demography , and behavior ( Table 2 ) . No factors related to behavior were significantly associated with infection status , including working in fields , working in the forest , fetching water from an open water source ( e . g . a pond or stream ) , fetching water from a protected well , or tending livestock ( Table 2 ) . Residence in a household with at least one other G . duodenalis-positive person was significantly associated with infection , as was residence in a household with at least one positive cattle , goat , or sheep . We found no association between infection with G . duodenalis and the reporting of gastrointestinal symptoms or the taking of medicines ( Table 2 ) . This was despite a strong association between the reporting of gastrointestinal symptoms and the reporting of medication usage during the same time period ( OR = 48 . 3; 95% Wald confidence limits 6 . 1–383 . 4; Fisher's exact P = 0 . 001 ) . The lack of an association between infection status and the reporting of gastrointestinal symptoms held true even when individuals ≤15 years ( n = 48 ) were analyzed separately ( OR = 1 . 15; 95% Wald confidence limits 0 . 37–3 . 64; Fisher's exact P = 0 . 704 ) . To account for potential confounding effects , we used multiple logistic regression with various strategies of model selection ( e . g . forward addition , backward stepwise elimination; details not presented ) . Regardless of the method used , the same two variables were retained in the final model in all cases: age of ≤15 years ( aOR = 4 . 78; Wald 95% CI = 1 . 79–12 . 78; chi-square = 9 . 76; P = 0 . 002 ) and residence in Rurama ( aOR = 5 . 40; Wald 95% CI = 1 . 88–15 . 50; chi-square = 9 . 83; P = 0 . 002 ) . Residence in a household with another positive person or residence in a household with a positive animal , which were significant in our univariate analysis , fell out of the model as non-significant when all predictors were considered together . All sequences generated during this study were submitted to GenBank ( Accession Numbers GQ502935–GQ503034 ) . Our success in generating G . duodenalis nucleotide sequences from the 64 positive samples identified by real-time PCR varied by locus , with success being highest for SSU-rDNA ( Table 3 ) . Genetic diversity also varied considerably among the G . duodenalis loci , with tpi containing the highest overall nucleotide diversity and ef1-α the lowest ( Table 3 ) . Genetic diversity was marginally higher among G . duodenalis from humans than from other species at three of four loci ( Table 3 ) . Phylogenetic analyses of G . duodenalis nucleotide sequences yielded trees that were topologically similar across loci , but that differed in their phylogenetic resolution ( Figure 1 ) . The tree based on SSU-rDNA had the lowest phylogenetic resolution , but was nevertheless able to resolve G . duodenalis clades of assemblage E from livestock , assemblage A or F from humans , livestock , and primates , and assemblage B from humans and primates . The tree based on tpi was able to resolve G . duodenalis clades of assemblage B from humans and livestock , assemblage E from livestock and a red colobus , and assemblage A from humans . The tree based on ef1-α was able to resolve G . duodenalis clades of assemblage B from humans and primates and assemblage E from livestock , although the phylogenetic positions of other sequences remained ambiguous . The tree based on gdh had the highest phylogenetic resolution and was able to resolve G . duodenalis clades of assemblage BIV from humans and red colobus , assemblage E from livestock and red colobus , and human-only clades of assemblage BIII and AII . In addition , the gdh tree was able to resolve genetic relationships among G . duodenalis sequences even within assemblages . Notably , G . duodenalis sequences from three red colobus and one human had identical gdh sequences within the assemblage BIV clade . Using our phylogenetic results , we were able to classify 36 human G . duodenalis into either assemblage A or assemblage B . We were unable to detect an association between assemblage and any demographic , behavioral , or clinical variable , including age ( ≤15 years; OR = 0 . 32; 95% Wald confidence limits 0 . 05–1 . 96; Fisher's exact P = 0 . 200 ) or the reporting of gastrointestinal symptoms ( OR = 1 . 60; 95% Wald confidence limits 0 . 33–7 . 85; Fisher's exact P = 0 . 430 ) . We were , however , limited by a small sample size of infected children ≤5 years of age for whom both clinical data and G . duodenalis assemblage were available ( n = 6 ) ; this precluded meaningful analysis of an association between assemblage and clinical disease in this age category , which might have been expected based on published results [30] .
Our data provide evidence for multiple cross-species G . duodenalis transmission cycles in western Uganda . Our sequence analysis was able to resolve four G . duodenalis clades: one involving assemblage BIV in humans and primates , one involving assemblage E in livestock and primates , and two involving assemblages AII and BIII in humans . Our phylogeny based on gdh was additionally able to resolve sub-clades of G . duodenalis within assemblages , including from humans and red colobus within assemblage BIV and from livestock and red colobus within assemblage E . Although our small sample sizes precluded formal cladistic analyses of the directionality of cross-species transmission [31] , we believe human-to-primate and livestock-to-primate transmission to be most likely in the case of assemblages BIV and E , respectively , given what is already known about the characteristic species that these assemblages infect [8] . Furthermore , the prevalence of G . duodenalis in humans was higher than in either primates or livestock ( Table 1 ) , as was the genetic diversity of G . duodenalis at 3 of 4 loci ( Table 3 ) , suggesting a human G . duodenalis reservoir for at least some assemblages . The association of G . duodenalis assemblages AII , BIII , and BIV with humans and E with livestock as described above agrees with past research [8] , [32] , [33] , as does our finding of assemblage B G . duodenalis in non-human primates , which has previously been documented in captive settings [34] . Our study adds new information about G . duodenalis assemblages in wild primates . Specifically , our finding of assemblage E G . duodenalis in red colobus is , to our knowledge , the first account this assemblage in a non-human primate . If assemblage E G . duodenalis can in fact be transmitted between livestock and primates , this would support findings by Foronda et al ( 2008 ) , who inferred assemblage E G . duodenalis in another primate - humans - in Egypt from tpi gene sequences , implying a possible cattle-human transmission link [35] . Such “atypical” transmission might be enhanced in settings where ecological overlap between species is high , such as our study area , where primates must often cross cattle pastures to move between habitat patches [14] . In this light , we note that Graczyk et al ( 2002 ) analyzed 130 bp of the small subunit ribosomal RNA gene from G . duodenalis in people , cattle , and mountain gorillas in Bwindi Impenetrable National Park , Uganda ( approximately 200 km from our study site ) , where ecological overlap between species is also high , and inferred infection with assemblage A in all three species [7] . That we did not find assemblage A G . duodenalis in species other than humans may reflect real differences between sites; however , we also note that SSU-rDNA had the lowest phylogenetic resolution of any gene in our study ( Figure 1 ) and might thus be prone to causing errors of misclassification . Our results also demonstrate that the prevalence of G . duodenalis in people in rural western Uganda is high , with up to approximately two thirds of people infected in some locations . These results are similar to those of other recent studies that have documented high rates of G . duodenalis infection in impoverished rural populations with limited access to health care , with prevalence ranging from a typical 20–30% to approximately 70% in some populations ( e . g . [35]–[38] ) . Our prevalence estimates are considerably higher than has been reported for school children in Moyo District , Uganda ( approximately 400 km from our study area ) [39] or in the capital city of Kampala in school children [40] or children hospitalized with diarrhea [41] , perhaps due to the higher sensitivity of our PCR-based detection method than the microscopic methods used in these studies . In this light , we note that the prevalence estimate we report here for primates ( 11 . 1% ) is higher than in our previous investigation of these same primate populations [16] , in which we documented a 3 . 8% Giardia prevalence using immunofluorescent microscopy ( albeit with a separate set of samples collected two years earlier ) . This observation again suggests that PCR-based methods are more sensitive than microscopy . We also documented a high local heterogeneity of G . duodenalis prevalence among human communities . People from Rurama community were infected with G . duodenalis at a rate approximately three times that of people in Bugembe or Kiko 1 communities , despite the roughly similar demographic composition of these communities and their close proximity to each other ( within approximately 7 km [15] ) . Intriguingly , neither livestock nor primates in Rurama were infected with G . duodenalis at elevated rates , implying that general “parasite pollution” of the physical environment probably does not account for the trend observed in humans . We speculate that this variation may reflect local differences in human health or behavior , such as coinfection with other agents or methods of food preparation , respectively . The lack of any measurable association between infection of people with G . duodenalis and the reporting of gastrointestinal symptoms was surprising , but it is concordant with some other recent studies . For example , Cordón et al . ( 2008 ) found G . duodenalis at 28 . 1% prevalence in diarrheic Peruvian children as well as in 19 . 5% of nondiarrheic children , emphasizing the importance of asymptomatic patients in G . duodenalis transmission where hygiene and sanitation are poor [42] . Other studies in India [24] , Ethiopia [37] , Bangladesh [38] , and Peru [43] have found similarly weak or non-existent associations between G . duodenalis infection status and gastrointestinal symptoms . Although we found little evidence for an effect of G . duodenalis on human health , we cannot exclude the possibility that the parasite may be impacting the health of livestock or that of wild primates . Such effects could , in turn , have consequences for conservation . The Ugandan red colobus monkey , for example , is endangered and may be declining due to a combination of nutritional stress and parasitism [44] . Increasing encroachment into primate habitats and consequent human-primate conflict ensure that , without intervention , such trends will continue [14] . We emphasize that our results are based small sample sizes and short nucleic acid sequences . Moreover , variable amplification success among loci and samples precluded phylogenetic analysis of concatenated sequences ( i . e . multilocus sequence tying ) , which might have improved phylogenetic resolution . Findings such as our discovery of assemblage E G . duodenalis in red colobus monkeys , which would be the first report of this assemblage in a non-human primate , should ideally be confirmed with additional sampling and sequencing . Also , we were unable to examine the relationship between infection status and Giardia-specific treatment in people , which could have altered prevalence and the clinical manifestations of infection . We therefore view the results of this study as indicating a strong need for future research into the epidemiology , cross-species transmission ecology , and clinical consequences of G . duodenalis infection in both humans and wildlife , especially where these species interact in anthropogenically disturbed habitats in the tropics .
|
Giardia duodenalis is a common protozoan parasite that infects multiple mammalian species , including humans . We analyzed G . duodenalis from people , livestock , and wild non-human primates in forest fragments near Kibale National Park , western Uganda , where habitat disturbance and human-animal interaction are high . Molecular analyses indicated that endangered red colobus monkeys were infected with G . duodenalis assemblages BIV and E , which characteristically infect humans and livestock , respectively . G . duodenalis infected people at rates of up to 67 . 5% in one village , and people age 15 years or younger were especially likely to be infected . G . duodenalis infection in people was not associated with other factors related to behavior and hygiene , and infected people were no more likely to have reported gastrointestinal symptoms than were uninfected people . These results demonstrate that G . duodenalis transmission from humans and domestic animals to wildlife may occur with ease in locations such as western Uganda , where habitat disturbance causes ecological overlap among people , livestock , and primates . This conclusion has conservation implications for wildlife such as red colobus , which are already endangered by habitat loss .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"Methods",
"Results",
"Discussion"
] |
[
"ecology",
"infectious",
"diseases/epidemiology",
"and",
"control",
"of",
"infectious",
"diseases"
] |
2010
|
Molecular Epidemiology of Cross-Species Giardia duodenalis Transmission in Western Uganda
|
β-III spectrin is present in the brain and is known to be important in the function of the cerebellum . Heterozygous mutations in SPTBN2 , the gene encoding β-III spectrin , cause Spinocerebellar Ataxia Type 5 ( SCA5 ) , an adult-onset , slowly progressive , autosomal-dominant pure cerebellar ataxia . SCA5 is sometimes known as “Lincoln ataxia , ” because the largest known family is descended from relatives of the United States President Abraham Lincoln . Using targeted capture and next-generation sequencing , we identified a homozygous stop codon in SPTBN2 in a consanguineous family in which childhood developmental ataxia co-segregates with cognitive impairment . The cognitive impairment could result from mutations in a second gene , but further analysis using whole-genome sequencing combined with SNP array analysis did not reveal any evidence of other mutations . We also examined a mouse knockout of β-III spectrin in which ataxia and progressive degeneration of cerebellar Purkinje cells has been previously reported and found morphological abnormalities in neurons from prefrontal cortex and deficits in object recognition tasks , consistent with the human cognitive phenotype . These data provide the first evidence that β-III spectrin plays an important role in cortical brain development and cognition , in addition to its function in the cerebellum; and we conclude that cognitive impairment is an integral part of this novel recessive ataxic syndrome , Spectrin-associated Autosomal Recessive Cerebellar Ataxia type 1 ( SPARCA1 ) . In addition , the identification of SPARCA1 and normal heterozygous carriers of the stop codon in SPTBN2 provides insights into the mechanism of molecular dominance in SCA5 and demonstrates that the cell-specific repertoire of spectrin subunits underlies a novel group of disorders , the neuronal spectrinopathies , which includes SCA5 , SPARCA1 , and a form of West syndrome .
Spectrins are a diverse family of membrane scaffold proteins . They were originally found in erythrocytes where mutations result in various haemolytic anemias [1] , [2] . Spectrins have been identified in the brain [3] but until recently little was known of the effects in humans of brain spectrin mutations . In 2006 , heterozygous mutations of the brain spectrin gene SPTBN2 , encoding β-III spectrin , were found to cause Spinocerebellar Ataxia Type 5 ( SCA5 ) [4] . SCA5 is an autosomal dominant , slowly progressive , adult onset , pure cerebellar ataxia , which was first identified in a large family who are the descendents of relatives of the US President Abraham Lincoln; SCA5 is therefore sometimes referred to as “Lincoln ataxia” [5] , [6] , [7] . Two other SCA5 families have been described in the literature , one from France and one from Germany [8] , [9] . β-III spectrin is a 2 , 390 amino acid protein comprising an N terminal domain containing the actin/ARP1 binding site , 17 spectrin repeats , ( the latter containing regions which bind the glutamate transporter EAAT4 [10] , and ankyrin [11] ) , and a C terminal domain of uncertain function . β-III spectrin forms antiparallel tetrameric heterodimers with α-II spectrin , encoded by SPTAN1 . The tetrameric self-association probably requires the presence of the C terminal β spectrin repeats , B16 and B17 , and the N terminal α spectrin repeats , A0 and A1 , with absence of these regions highly likely to impair the formation of a functional tetramer [12] . Three heterozygous dominant mutations in SPTBN2 have been reported to cause SCA5: in the US ( Lincoln ) family a 13 amino acid in-frame deletion ( E532_M544del ) in the third spectrin repeat , in the French family a small complex in-frame deletion-insertion ( L629_R634delinsW ) , also in the third spectrin repeat , and in the German family a missense mutation ( L253P ) , in the N terminal domain . The mechanism of action of these mutations is not immediately obvious and could be explained by haploinsufficiency , in which the mutant allele is inactive and the normal stoichiometry for tetramer formation is lost , a dominant negative effect which suppresses wild type ( wt ) function , or a gain of function effect . Several lines of evidence have suggested that a dominant negative effect in SCA5 is most likely . Using targeted gene disruption of mouse β-III spectrin , Perkins et al , reported that homozygous knockout mice ( β-III spectrin −/− ) had cerebellar ataxia , a progressive loss of cerebellar Purkinje cells and an associated decrease in the Purkinje cell specific glutamate transporter EAAT4 [13] . The β-III spectrin −/− mutant mice lack all full-length β-III spectrin but do express , at a low level , a form of β-III spectrin ( ∼250 KDa ) that lacks most of the actin-binding domain encoded by exons 2–6 . The heterozygous mice ( β-III spectrin +/− ) were reported to be normal . Further work has shown that the L253P ( German ) missense mutation has a dominant negative effect on wild type function by preventing protein trafficking from the Golgi apparatus [14] . There is evidence also that de novo in-frame mutations in SPTAN1 encoding α-II spectrin have dominant negative effects , causing a form of West Syndrome ( infantile epilepsy with developmental delay ) [15] . However , although experimental data has strongly suggested that small in-frame mutations or missense mutations in α-II or β-III spectrins have a dominant negative effect , no recessive mutations in spectrins have been found , and such data would lend further strong support for this hypothesis . Here we report the first description of recessive mutations in SPTBN2 in which there is a severe developmental childhood ataxia but also significant cognitive impairment . The homozygous stop codon c . 1881C>A ( p . C627X ) , was identified in three affected individuals from a consanguineous family using targeted capture and next generation sequencing and both the ataxia and cognitive impairment co-segregate with the mutation . However , since more than one mutation can co-segregate , particularly in consanguineous families , we considered whether a second recessive mutation , either homozygous or compound heterozygous , could account for the cognitive impairment . We investigated this using a combination of SNP array analysis and whole genome sequencing , but found no evidence of a second mutation . We also investigated β-III spectrin −/− knockout mice [13] for supportive evidence that the cognitive impairment in the human subjects is caused by loss of β-III spectrin . We examined the mouse model for morphological abnormalities of neurons in brain regions ( other than cerebellum ) , which are thought to be involved in memory function including prefrontal cortical ( PFC ) layers , the caudate putamen/striatum and hippocampus ( HPC ) . Finally we tested the mice using object recognition tasks , which have been shown to correlate with function of the PFC and HPC [16] , [17] . The morphological and behavioural abnormalities found in the knockout mice provide further evidence that the cognitive impairment in our human subjects is an integral part of this novel recessive disorder which we have called SPARCA1 ( “Spectrin-associated Autosomal Recessive Cerebellar Ataxia type 1” ) . We suggest that this represents one of a novel group of disorders , the neuronal spectrinopathies , which demonstrate that the cell-specific functional repertoire of spectrin subunits are involved in brain development including the cortex , in addition to cerebellar development and function .
The three affected individuals are from a UK family of Pakistani origin with complex consanguinity ( see Figure 1A ) , but no other family history of neurological disorders . The clinical phenotype in the 3 individuals is identical ( Table 1 ) . V1 was referred at the age of 13 months with motor delay; she was extremely floppy and was unable to crawl . She sat at 10 months , crawled at 18 months and was pulling to stand at 20 months . She walked with a walker by the age of 5 and started to walk with support at age 7 . She was noted to have language delay and at age 5 was just starting to join words together . Global developmental delay was subsequently noted , she was educated at a special school and now attends a college for adults with special educational needs . On examination there are abnormal eye movements with a convergent squint , hypometric saccades , jerky pursuit movements , and an incomplete range of movement particularly in the horizontal plane . There is obvious dysmetria and dysdiadochokinesia of the limbs and gait ataxia with inability to tandem walk without falling . Limb tone is normal , reflexes are normal and plantars flexor and there is no evidence of any sensory abnormality . Rombergs sign is normal . Neuropsychological assessment reveals significant global cognitive impairment with all IQ scales falling at the second percentile or below , and with Full Scale IQ scores falling in the learning disabled range ( Table 1 ) . A brain CT scan at age 2 did not show any abnormality , but a recent MRI brain reveals significant cerebellar atrophy ( Figure 2A ) . V2 is the younger sibling of V1 . She was noted to have developmental delay in early childhood and also did not start to walk until age 7 . On examination , she has an identical clinical phenotype to that of her sister except for occasional beats of nystagmus on eye examination . She attends a school for children with learning disabilities and a recent assessment ( at age 16 ) shows functioning in English and Mathematics at the level of an average 5–7 year old in the UK requiring special educational support . Formal cognitive assessment also showed very similar impairments to V1 with scores on all IQ scales falling at the second percentile or below , and with Full Scale IQ scores falling in the learning disabled range ( Table 1 ) . The difference between Verbal and Performance IQ for each individual was not statistically significant ( p = 0 . 15 ) . MRI imaging in V2 at age 6 revealed cerebellar atrophy and this was found to have progressed over time ( Figure 2Bi and Bii ) . V3 is the first cousin of V1 and V2 . He was noted to have poor head control and balance in early childhood . Clinical examination is identical to his cousins and also shows an identical developmental profile in that he has just started to walk with assistance at the age of 7 . He also has an identical eye movement disorder , a convergent squint , dysmetria and dysdiadochokinesia . He is hypotonic with normal reflexes downgoing plantars and no evidence of a sensory neuropathy . He attends a mainstream school but requires full time one to one support . Cognitive assessment of V3 also showed significant global cognitive impairment ( Table 1 ) . The slightly higher IQ scores in V3 results from a floor effect in the normative data rather than a significant difference in cognitive ability from his older cousins . In this age cohort the lowest attainable scores are VIQ = 62 , PIQ = 73 and FSIQ = 63 and therefore V3 falls in the same learning disabled range as his cousins . Brain imaging of V3 showed a normal cerebellum at age 5 , but mild hypoplasia of the posterior corpus callosum ( Figure 2C ) . The normal appearance of the cerebellum in V3 at an early age is not unexpected as both his cousins imaging shows progression with time . Neurological examination of both sets of parents was entirely normal , with no evidence of ataxia . The father of V1 and V2 works as a bus driver , having left school at age 16 with 5 GCSEs ( General Certificates of Secondary Education ) and the father of V3 works in a warehouse and has a similar educational background . Formal psychometric testing in the father of V1 and V2 showed IQ indices falling in the low average range consistent with his educational attainment . The father of V3 was not available for testing but has very similar attainment levels to his brother . Formal assessment of the mothers could not be performed since neither speak English , but interview of the family did not reveal any evidence of learning disability . There is no history of the siblings or grandparents of the affected individuals having any cognitive or neurological abnormalities . We initially performed targeted capture of >100 known ataxia genes ( including SPTBN2 ) in a group of children with unexplained ataxia including patient V3 , followed by next generation sequencing . In V3 we identified only one mutation , a homozygous stop codon p . C627X ( c . 1881C>A ) , located in the third spectrin repeat in SPTBN2 and used Sanger sequencing to confirm that all three affected patients in the family had the same mutation whereas the neurologically normal parents of V3 , were shown to be heterozygous for the mutation ( Figure 1B ) . Since mutations in β-III spectrin are associated with cerebellar degeneration in SCA5 , the newly identified mutation was considered likely to explain the ataxia , although of a developmental type with a much earlier onset . However , since more than one mutation can co-segregate , particularly in consanguineous families , we went on to consider the contribution of the mutation in SPTBN2 to the observed cognitive impairment . We therefore used SNP array analysis and whole genome sequencing to search for any evidence of a second mutation . To investigate whether a second homozygous mutation segregated with the cognitive impairment , all 3 affected individuals ( V1 , V2 and V3 ) and the unaffected parents of V3 ( IV3 and IV4 ) were genotyped to identify regions of homozygosity ( ROH ) shared by V1 , V2 and V3 and not present in either IV3 or IV4 . This analysis identified 20 shared homozygous segments on autosomes totalling 17 . 1 Mb ( Table 2 ) . SPTBN2 , on chromosome 11 , was located in the largest ROH shared by V1 , V2 and V3 and not present in either IV3 or IV4 ( Figure 3 ) . Whole genome sequencing of patient V2 was performed on the Illumina HiSeq2000 as 100 bp paired end reads , using v3 clustering and sequencing chemistry . After duplicate reads removal , the mean coverage across the genome was 25 . 6× with 90 . 4% of bases covered at 15× or more . The mean coverage over the 17 . 1 Mb ROH identified by SNP analysis was 25 . 9× with 93 . 4% of bases covered at 15× or more . Variant calling was performed as detailed in the Materials and Methods . We firstly based our data analysis on an autosomal recessive disease model , caused by one or more rare homozygous mutations and focused on homozygous variants occurring in the shared ROH identified by SNP array analysis , filtering them out if they were: These filtering steps identified 68 candidate variants , subdivided into functional classes ( Table 3 ) . Only 2 exonic variants were found: a synonymous variant , NPHP1 L551L on chr2 which is not predicted to be pathogenic and is not located near a splice site , and the stop codon C627X in SPTBN2 on chr11 ( Table 2 and Table 3 ) . Of the remaining variants , 21 were intergenic and also considered unlikely to be disease related , and 4 variants were in untranslated regions ( 5′ UTR ) or in non-coding RNAs and all were in positions which scored poorly with PhyloP and GERP . In addition , none of the associated genes ( UBIAD1 , LINC00116 , LOC100130987 ) appear to be relevant for this disorder . The other 41 were in intronic and upstream regions but based on evolutionary conservation and available information in databases ( eg HGMD [18] ) we found no evidence of potential involvement in the disease . The only likely pathogenic variant is the stop codon in SPTBN2 . We also considered a model of recessive inheritance with compound heterozygous mutations segregating with the ataxia and/or cognitive impairment . Our criteria were that all 3 affecteds must have two different variants in the same gene and where this occurred the variants should be in trans ( ie each parent is a carrier ) . We identified all potential compound heterozygous coding variants present in the WGS data for individual V2 . In total there were variants fulfilling our criteria at 13 different loci but in only 1 case were both variants present in all 3 affecteds and further analysis revealed that in this instance both variants were also in the father of V3 ( ie were in cis ) . Furthermore , none of the variants identified are known to be associated with ataxia or cognitive impairment and the majority of genes had data suggesting an alternative function ( such as taste or fertility ) , nor were there any likely candidates based on pathogenicity bioinformatic prediction programs ( Table S2 ) . The phenotype of our patients suggested that β-III spectrin is involved in cognitive development , in addition to being essential for motor functions . We therefore utilised β-III spectrin knockout mice which have progressive cerebellar degeneration and lack any full length β-III spectrin [13] , to further investigate the role of β-III spectrin in other brain regions . Our previous work revealed that β-III spectrin is required for the correct dendritic development of Purkinje cells [19] , [20] and therefore we initially examined dendritic organisation in other brain regions by immunostaining sagittal sections from the brains of 6-week-old wild-type and β-III spectrin knockout animals for microtubule associated protein 2 ( MAP2 ) , a dendritic marker . This revealed irregular reactivity throughout the PFC layers and within the caudate putamen/striatum of knockout animals when compared to WT mice but no obvious difference in the HPC ( Figure 4A ) . However no difference was observed between WT and β-III spectrin knockout animals when the cortex and striatum were immunostained for tau or myelin basic protein ( MBP ) indicating that there was no change to axonal structure ( Figure S1 ) . The PFC in humans is believed to be important for complex cognitive tasks , and given there is evidence of a close association between this area and the neocerebellum , as well as high expression levels of β-III spectrin in mouse [10] we further investigated the prefrontal cortical region in β-III spectrin knockout animals . There was no difference in the thickness of individual prefrontal cortical layers ( data not shown ) but the morphology of individual pyramidal neurons in β-III spectrin knockout animals was found to be altered . Morphometric analysis of dye-injected pyramidal neurons from layer 2/3 showed basal dendrites in 8-week-old β-III spectrin knockout mice were significantly thinner distally compared to wild type cells ( Figure 4B–4D ) . Moreover , the basal dendrites of knockout mice tapered more rapidly than those of wild types , being significantly reduced in thickness between 20 and 30 µm from the soma , whereas wild type dendrites showed no significant narrowing until 90 µm from the soma . However , no difference in spine density was observed between genotypes in either dye injected ( Figure 4D: +/+ , 2 . 8±0 . 6 , n = 8; −/− , 3 . 2±0 . 2 spine/µm3 , n = 7; p = 0 . 56 ) or Golgi-impregnated ( Figure 4E: +/+ , 12 . 4±1 . 7 , n = 4; −/− , 13 . 7±1 . 3 spine/10 µm , n = 6; p = 0 . 56 ) pyramidal neurons . Only small sections of apical dendrites could be reconstructed from the serial stacks of dye-injected cells . Nevertheless , quantification of the short regions imaged , when normalized to length analysed , indicated reduced apical dendritic volumes , and hence thinner apical dendrites in β-III spectrin knockout animals ( +/+ , 4 . 3±0 . 47; −/− , 2 . 5±0 . 36 µm3/µm , n = 6 for each genotype; p = 0 . 011 ) . Since patient V3 shows mild hypoplasia of the posterior corpus callosum we examined this brain structure in 8-week old β-III spectrin knockout animals to determine if the morphological defect in the human subject could be a consequence of β-III spectrin loss or is unlinked to the homozygous stop codon c . 1881C>A ( p . C627X ) mutation in SPTBN2 . No signs of posterior hypoplasia were observed in sagittal sections stained either with cresyl violet ( Figure 5A ) or an anti-tau antibody ( Figure 5B ) . Similarly width of corpus callosum , measured from coronal sections immunostained for MBP ( Figure 5C ) , was no different between WT and knockout animals ( +/+ , 469 . 7±46 . 6; −/− , 480 . 6±41 . 3 µm , N = 3 for each genotype; p = 0 . 28 ) . Four object recognition memory tasks ( two- and four- novel object preference , object-in-place and object location; Figure 6A–6D ) were carried out to assess whether β-III spectrin knockout animals displayed any cognitive deficits . No impairment in the two novel object recognition task ( “object identity” ) was observed in β-III spectrin knockout animals compared with wild type animals ( Figure 6A ) ; however knockout animals performed worse in the four novel object recognition task ( Figure 6B ) . Knockout animals were also worse at discriminating between rearranged and non-rearranged objects in the object-in-place task compared with litter mate controls , shown by their failure to spend more time exploring the two objects in different locations compared with the two objects that had not moved ( “object displacement” ) ( Figure 6C ) . However , there was no significant difference in performance for the object location task ( Figure 6D ) . The poorer performance in the four-novel object recognition task for knockout animals was not a consequence of less exploration in the 5 minute sample phase as in fact they explored more than wild type animals ( +/+ , 64 . 9±6 . 7; −/− , 88 . 7±4 . 8 sec; p = 0 . 018 ) . Similarly for the object-in-place task although there was no significant difference between genotypes there was a trend for greater exploration in knockout animals ( +/+ , 42±3 . 6; −/− , 62 . 2±8 . 7 sec; p = 0 . 054 ) .
The integrated evidence from clinical , genetic and neuropsychological analysis in humans and behavioural and morphological analysis in a mouse model demonstrate that we have identified a novel recessive disorder , SPARCA1 , associated with mutations in β-III spectrin . The 3 human subjects with a premature stop codon and the mouse knockout all have very early onset cerebellar ataxia , indicating a developmental role for β-III spectrin . The human and mouse knockout phenotype also show that β-III spectrin is involved in cognitive development and function . The human subjects have global cognitive impairment in the mild/moderate range . The specific brain structures and connections associated with this impairment are not yet known and further detailed neuropsychological testing will be required . However , we have shown that in the mouse knockout there are morphological abnormalities especially thinning of dendrites in PFC neurons , similar to that previously reported for Purkinje neurons [19] , but with no obvious changes in various regions of HPC ( CA1 , CA3 and dentate gyrus ) , and the behavioural tests in the mouse are consistent with this . Based on published lesion studies , deficits in the object-in-place task but not the object location task would indicate defects in the PFC not HPC , since PFC is believed to mediate memory for object location ( Òobject displacementÓ ) , whereas HPC integrates information as to object identity and the temporal order of object presentation with HPC lesioned animals being impaired on object location task [16] , [17] , [21] . However , further to the above discussion , there is also increasing recognition that the cerebellum itself has a direct role in cognition [22] and it is possible that some of the phenotype results directly from cerebellar abnormalities . Further investigation should also allow a detailed analysis of which specific brain regions mediate mild/moderate cognitive impairment in humans . The data demonstrate that our β-III spectrin knockout mouse [13] is an excellent model for the novel recessive disorder we have identified and will allow further molecular analysis of β-III spectrin , in addition to the morphological and behavioural analysis . β-III spectrin is known to be expressed widely throughout the brain , kidney , liver and testes and to be associated with the Golgi and other cytoplasmic vesicles [23] , but the mechanisms by which mutations lead to impaired brain development are unknown . The premature stop codon C627X identified in our family is predicted to result in truncation of β-III spectrin near the end of the 3rd spectrin repeat ( Figure 7 ) . This truncated protein would be unable to form tetramers with α-II spectrin , nor be able to bind to EAAT4 or ankyrin , but it is possible that there is nonsense mediated decay and loss of the entire protein . Since SPTBN2 is expressed at only very low levels in peripheral blood , further in vitro expression studies will be required to determine this . However , it is most likely that β-III spectrin is absent in the brain of the human subjects and this has resulted in neuronal dysfunction in widespread brain regions , notably cerebellum and prefrontal cortex . Future studies will investigate other brain regions such as striatum and perirhinal cortex as well . Our findings also provide insights into the mechanism of molecular dominance in SCA5: the heterozygous carrier parents of the C627X stop codon in the SPARCA1 family are neurologically normal despite carrying a stop codon which in the homozygous state is a recessive loss of function mutation . Therefore haploinsufficiency is highly unlikely to be the mechanism underlying SCA5 and this lends considerable weight to the body of experimental evidence suggesting that SCA5 results from a dominant negative effect , possibly by interfering with normal binding to ARP1 [13] , [14] , [24] . One difference between the human and mouse model is that the mouse shows progressive motor deficits in addition to progressive Purkinje cell loss whereas there is no evidence of clinical progression in the patients at the moment despite one of our subjects having progressive cerebellar atrophy on imaging . This lack of clinical progression and discordance between the clinical and imaging findings could suggest that there is significant plasticity within the human cerebellum , although we cannot exclude the possibility that slow clinical progression will occur with time . The phenotypic spectrum of neuronal spectrinopathies now appears to be very wide . In SCA5 , the ataxia is generally a pure adult-onset ataxia whereas recessive mutations in SPTBN2 cause SPARCA1 , a more severe childhood ataxia with cognitive impairment . In West Syndrome , associated with SPTAN1 mutations , the patients have epilepsy , profound developmental delay and in addition have shortening of the corpus callosum and cerebellar vermis atrophy . Only one of our patients , V3 , had shortening of the corpus callosum and it is tempting to speculate that this additional feature may be part of the SPARCA1 phenotype , although there are no signs of hypoplasia in the β-III spectrin knockout mice . It also may be that this feature is caused by another gene mutation or a genetic modifier and to clarify this additional cases will need to be identified . Overall , our data suggest that region specific expression of spectrin subunits is important in prenatal brain development and further work is required to define their temporal and spatial contribution . Our data also suggest the possible and testable hypothesis that the phenotype in neuronal spectrinopathies relates in part to the total amount of functional spectrin tetramers: in SCA5 , all α-II/β-II tetramers are normal and functional but α-II/β-III tetramers will contain mutant β-III spectrin which likely have a dominant negative action and may not be fully functional; in SPARCA1 , a recessive disorder , there is complete loss of the tetramerisation site of β-III spectrin so there will be normal α-II/β-II tetramers but no functional α-II/β-III tetramers , whereas the heterozygotes who are effectively “haploinsufficient” have enough α-II/β-III tetramer to be clinically normal; in West Syndrome , caused by in-frame dominant SPTAN1 mutations [15] , the majority of both α-II/β-II and α-II/β-III tetramers are abnormal resulting in the most severe of the disorders to be described so far ( Figure S2 ) . This model would suggest that homozygous loss of function α-II spectrin mutations might be more severe or lethal and a very recent report of an α-II knockout mouse supports this and it will be important to identify the equivalent human disorder [25] . There may be other disorders associated with human disease: dominant negative or recessive mutations in β-II and proteins interacting with brain spectrins may also have similar phenotypes . For example , a mouse knockout model of Ankyrin G , was reported to cause Purkinje cell degeneration [26] but a human phenotype has not yet been found . In addition , seizures are described in SPTAN1 mutations [15] and another β-III spectrin knockout [24] and it will be important to search for spectrin mutations in epilepsy patients . In conclusion , the identification of recessive mutations in β-III spectrin provides evidence that the cell-specific repertoire of spectrin subunits underlies a novel group of disorders , the neuronal spectrinopathies , including SCA5 , a dominant form of West Syndrome and SPARCA1 . It is likely that other human disorders are caused by mutations in neuronal spectrins and searches for these are in progress . We also demonstrate the power of analysing complex phenotypes in consanguineous families by using whole genome sequencing , which was critical in establishing that both the ataxia and the cognitive impairment were caused by the same mutation and illustrate how the use of genome sequencing , even in single human families , can help provide mechanistic insights into disease .
Our institutional ethics committee approved the study on human participants and specific consent was obtained to include whole genome analysis . All procedures involving analysis of mutant mice were carried out according to the United Kingdom Animals ( Scientific Procedures ) Act ( 1986 ) and other Home Office regulations under specific pathogen-free conditions . The exonic sequences of 129 genes known or suspected to be associated with ataxia were selected for targeted capture ( Table S1 ) and 120-mer baits with 2X tiling designed using the Agilent eArray design tool . The total size of the targeted region amounted to 605 . 8 kb . Multiplex sequencing was performed on the Illumina GAII with 51 bp paired-end reads . A total of 5 , 046 , 154 reads were generated for patient V3 and aligned to the human reference genome ( GRCh37/hg19 ) with STAMPY [27] About 60% of the reads mapped to the target region , providing a mean depth coverage of 218 . 4× with 89 . 8% of target bases covered at 30× or more . Single nucleotide variants ( SNVs ) and indels were called respectively with SAMTOOLS [28] and DINDEL [29] . Variants were annotated with respect to gene and transcripts using the Ensembl database ( release 62 , Apr 2011 [30] ) by means of the associated Variant Effect Predictor tool . Results were confirmed using Sanger Dideoxy Sequencing with the following primers across exon 14 of SPTBN2: Forward: CTACCTCTGCTGCACGACCT; Reverse: AGGGAGGGAAGTCCAAGAGA . Genomic DNA was amplified with Taq Polymerase ( Roche ) and PCR products were used as templates for sequencing with BigDye Terminator reagents ( Life Technologies ) on a 3730xl DNA Sequencing Analyzer ( Life Technologies ) . The sequence traces were aligned to the gene-specific reference sequence ( NCBI build 37 ) with Sequencher 4 . 10 . 1 ( Gene Codes ) . Genotyping was performed using the Illumina HumanCytoSNP-12v1 BeadChip , containing nearly 300 , 000 genetic markers . Hybridization to the chip was performed according to manufacturer's protocols found on registration at http://www . illumina . com/support/array/array_kits/humancyto-snp-12_v2-1_dna_analysis_kit/documentation . ilmn . In brief , patient DNA was denatured , amplified and enzymatically fragmented and then hybridized onto CytoSNP-12 BeadChips by rocking in an Illumina hybridization oven at 48°C for 16–24 hrs . The BeadChips were washed according to the Illumina Inc . protocol and the hybridized DNA detected by primer extension with labelled nucleotides followed by detection using fluorescent antibodies . The data were processed using Illumina's GenomeStudioV2009 . 2 . As SNP coordinates in the chip were reported with respect to human genome build 36 , we downloaded the corresponding coordinates for build 37 from the website http://www . well . ox . ac . uk/~wrayner/strand/ , cross-checking them using the USCS Genome Browser liftOver utility ( http://genome . ucsc . edu/cgi-bin/hgLiftOver ) and the dbSNP database ( Build 135 [31] ) . We filtered out ∼18 , 000 markers which could not be mapped unambiguously to build 37 of the human genome . We further excluded SNPS with missing calls in one or more samples , thus reducing the number of markers to 271 , 208 . PLINK v1 . 07 ( http://pngu . mgh . harvard . edu/purcell/plink/ [32] ) was used to identify regions of homozygosity ( ROH ) shared by V1 , V2 and V3 and not present in either IV3 or IV4 . For V1 , V2 and V3 , we applied relaxed parameters in order to include all potential ROH , resulting in potential false positives but minimizing false negatives . We defined a homozygous region as a run of ( at least ) 50 homozygous SNPS spanning more than 500 kb , allowing for some heterozygous calls within it . Shared ROH were identified from overlapping and allele matching segments . Further details of the algorithm are provided on the PLINKwebsite . We used the options: –homozyg –homozyg-group –homozyg-window-kb 500 –homozyg-window-snp 50 –homozyg-snp 50 –homozyg-kb 500 . All other parameters were left at default values . ROH were then identified in IV3 and IV4 . In this case very stringent criteria were applied to confidently include only true ROH and avoid false positives . We defined a homozygous region as an uninterrupted run of ( at least ) 500 homozygous SNP's spanning more than 5 Mb . In IV3 we identified 8 ROH on autosomes totalling 78 Mb ( the largest ROH was 18 . 4 Mb ) ; in IV4 we identified 2 large ROH on chromosome 11 present also in V1 , V2 and V3 ( Table 2 and Figure 3 ) . These regions were excluded in the search for pathogenic variants as both IV3 and IV4 are unaffected . As a result , the search was restricted to 20 regions totalling 17 . 1 Mb , among which the ROH harbouring SPTBN2 was the largest . Screening of cognitive function was undertaken using the Wechsler Abbreviated Intelligence Scale ( WASI ) . For immunostaining and histological analysis brains from wild type and β-III spectrin knockout animals were removed and immersion-fixed with either 1 or 4% paraformaldehyde in 0 . 1 M sodium phosphate buffer , pH 7 . 4 overnight at 4°C and cryoprotected in 0 . 1 M sodium phosphate buffer ( pH 7 . 4 ) containing 30% sucrose . Tissue was embedded in OCT then 16 µm-thick sections cut and mounted onto poly-L-lysine coated slides . Primary antibodies used were mouse anti-MAP2 ( Sigma ) , rabbit anti-tau ( DAKO ) and rat anti-myelin basic protein ( AbD Serotec ) . Secondary antibodies were cyanine 3 ( Cy3 ) -conjugated goat anti-mouse IgG ( Jackson laboratories ) , fluorescein isothiocyanate ( FITC ) -conjugated goat anti-rabbit IgG ( Cappel ) and Alexa Fluor 488 –conjugated donkey anti-rat ( Invitrogen ) . For Golgi impregnation brains were removed and immersion-fixed with 4% paraformaldehyde in 0 . 1 M sodium phosphate buffer , pH 7 . 4 overnight at 4°C and processed as described previously [39] . For cell filling animals were deeply anesthetized with isofluorane and sacrificed by transcardial perfusion with 4% paraformaldehyde in 0 . 1 mM phosphate buffer , pH 7 . 4 . Brains were dissected and postfixed in 1% paraformaldehyde overnight at 4°C . Coronal sections were cut ( 250 µm-thick ) and individual neurons in layer 2/3 of the prefrontal cortex were visualized with a 20× immersion objective and injected with 0 . 2 mM Lucifer Yellow ( Sigma ) and 0 . 02 mM Alexa FluorAR 568 hydrazide ( Invitrogen ) . Slices were post-fixed and 4% paraformaldehyde overnight at 4°C and wet-mounted with Vectashield onto 0 . 13 mm thick borosilicate glass and neurons imaged using the Alexa 568 dye . All images were captured using a Zeiss inverted LSM510 confocal scanning laser microscope and serial stacks used for three-dimensional reconstruction of dendritic arbors using NeuronStudio software ( CNIC ) . Animals were handled for 1 week and then habituated to the arena ( 40 cm×40 cm×40 cm ) for 5 d before testing . All tests involved a 5 min sample phase followed by a 5 min test phase after a delay of 5 min . Exploratory behaviour was recorded via a WebCam positioned above the testing arena and two researchers blind to genotype scored the investigation of each sample using ANY-maze software ( Stoelting ) . As described previously [16] , [21] for the novel object preference tasks one object from the sample phase was replaced with a novel object in the test phase; the object-in-place task comprised switching the location of two familiar objects in the test phase; and for the object location task position of one familiar object was changed ( Figure 6A–6D ) . Duplicate copies of familiar objects were used in the test phases to remove any chance of olfactory cues being present . Discrimination ratios were calculated as the time spent exploring the novel or location switched object ( s ) divided by the total time spent exploring all objects . Statistical analysis was performed using Student's t-test , two sample assuming unequal variance , apart from analysis of filled pyramidal cells where a two-way ANOVA was used .
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β-III spectrin is present in the brain and is known to be important in the function of the cerebellum . Mutations in β-III spectrin cause spinocerebellar ataxia type 5 ( SCA5 ) , sometimes called Lincoln ataxia because it was first described in the relatives of United States President Abraham Lincoln . This is generally an adult-onset progressive cerebellar disorder . Recessive mutations have not previously been described in any of the brain spectrins . We identified a homozygous mutation in SPTBN2 , which causes a more severe disorder than SCA5 , with a developmental cerebellar ataxia , which is present from childhood; in addition there is marked cognitive impairment . We call this novel condition SPARCA1 ( Spectrin-associated Autosomal Recessive Cerebellar Ataxia type 1 ) . This condition could be caused by two separate gene mutations; but we show , using a combination of genome-wide mapping , whole-genome sequencing , and detailed behavioural and neuropathological analysis of a β-III spectrin mouse knockout , that both the ataxia and cognitive impairment are caused by the recessive mutations in β-III spectrin . SPARCA1 is one of a family of neuronal spectrinopathies and illustrates the importance of spectrins in brain development and function .
|
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"Methods"
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2012
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Recessive Mutations in SPTBN2 Implicate β-III Spectrin in Both Cognitive and Motor Development
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Many immune correlates of CD8+ T-cell-mediated control of HIV replication , including polyfunctionality , proliferative ability , and inhibitory receptor expression , have been discovered . However , no functional correlates using ex vivo cells have been identified with the known ability to cause the direct elimination of HIV-infected cells . We have recently discovered the ability of human CD8+ T-cells to rapidly upregulate perforin—an essential molecule for cell-mediated cytotoxicity—following antigen-specific stimulation . Here , we examined perforin expression capability in a large cross-sectional cohort of chronically HIV-infected individuals with varying levels of viral load: elite controllers ( n = 35 ) , viremic controllers ( n = 29 ) , chronic progressors ( n = 27 ) , and viremic nonprogressors ( n = 6 ) . Using polychromatic flow cytometry and standard intracellular cytokine staining assays , we measured perforin upregulation , cytokine production , and degranulation following stimulation with overlapping peptide pools encompassing all proteins of HIV . We observed that HIV-specific CD8+ T-cells from elite controllers consistently display an enhanced ability to express perforin directly ex vivo compared to all other groups . This ability is not restricted to protective HLA-B haplotypes , does not require proliferation or the addition of exogenous factors , is not restored by HAART , and primarily originates from effector CD8+ T-cells with otherwise limited functional capability . Notably , we found an inverse relationship between HIV-specific perforin expression and viral load . Thus , the capability of HIV-specific CD8+ T-cells to rapidly express perforin defines a novel correlate of control in HIV infection .
Approximately 35–40 million people are currently infected with HIV worldwide . Most of these individuals fail to control HIV replication , and ultimately progress to acquired immune deficiency syndrome ( AIDS ) if left untreated . However , a subset ( <1% ) of the HIV-infected population , termed elite controllers ( EC ) , can spontaneously control viral replication to undetectable levels [1] , [2] , [3] . Understanding the mechanisms of immunologic control of HIV replication in EC may identify candidate markers of immune control useful for assessing HIV vaccine strategies . The host immune response , in particular HIV-specific CD8+ T-cells , is at least partially responsible for the control of viral replication in many EC . For example , EC are enriched for certain HLA alleles , such as HLA-B13 , B15 , B51 , B27 , B57 , and B58 [4] , [5] , [6] , [7] . EC contain a greater fraction of HIV-specific CD8+ T-cells that can degranulate , produce multiple functional cytokines and chemokines and display markedly better proliferative potential upon HIV peptide stimulation than individuals with progressive disease [7] , [8] , [9] , [10] , [11] , [12] , [13] . Additionally , recent evidence has demonstrated that HIV-specific CD8+ T-cells from EC have enhanced cytotoxic capabilities compared to progressors: Several groups have shown that HIV-specific CD8+ T-cells from EC display a superior ability to suppress the replication of HIV during extended culture [14] , [15] , [16] . Using CD8+ T-cells expanded in vitro for six days , Migueles and colleagues observed a higher cytotoxic capacity on a per-cell basis of HIV-specific CD8+ T-cells from EC [17] . Collectively , these findings suggest that CD8+ T-cells may be critical to the control of HIV replication in vivo . CD8+ T-cells are thought to kill virally-infected cells predominantly through the release of lytic proteins - mainly perforin and granzymes - that are secreted via exocytosis of pre-formed granules following recognition of infected targets [18] , [19] , [20] . Granule-mediated killing by CD8+ T-cells occurs within minutes to hours of target cell recognition; however , the reconstitution of intracellular perforin following degranulation has been reported to first require cellular proliferation [13] , [21] , [22] . We have recently identified another mechanism by which perforin-mediated CD8+ T-cell killing can take place: the rapid upregulation and targeted release of newly produced perforin , which traffics to the immunological synapse via a route that largely bypasses cytotoxic granules [23] . De novo synthesis of perforin by human CD8+ T-cells can be detected by flow cytometry in conjunction with standard intracellular cytokine-staining ( ICS ) [24] , thus permitting simultaneous assessment of CD8+ T-cell cytotoxic potential and cytokine production . Here , we measured the ability of HIV-specific CD8+ T-cells to express perforin in a cross-sectional cohort of chronically-infected individuals that differentially control viral replication . Several previously published studies have examined perforin expression in HIV-specific CD8+ T-cells in both progressive and nonprogressive infection [13] , [25] , [26] , [27] . However , due to the nature of the anti-perforin antibody employed [23] , these studies have uniformly assessed only pre-formed , granule-associated perforin present within resting or long-term activated HIV-specific CD8+ T-cells . In this work we demonstrate that HIV-specific CD8+ T-cells from EC , compared to progressors , have a superior ability to express perforin immediately upon activation , without the need for prior proliferation or the addition of exogenous cytokines . Overall , this work identifies the rapid expression of perforin as a novel correlate of control of HIV replication and urges a closer examination of CD8+ T-cell polyfunctionality in HIV infection .
We assessed the magnitude and functional characteristics of HIV-specific CD8+ T-cells by stimulating PBMC from 35 elite controllers ( EC ) , 29 viremic controllers ( VC ) , and 27 chronic progressors ( CP ) [Table 1 and Table S1] with overlapping peptide pools encompassing all HIV-1 ( clade B ) proteins . We developed a flow cytometric staining panel ( Fig . S1A ) that simultaneously measured memory phenotype ( CD27 , CD45RO , and CD57 ) , degranulation [surface expression of CD107a [28]] , cytokine expression ( IFN-γ , TNFα , and IL-2 ) , and chemokine production ( MIP1α ) . As a sixth functional parameter , we included an anti-perforin antibody ( clone B-D48 ) to measure perforin upregulation [23] , [24] . As shown in Figure S1B , the historically used antibody ( δG9 clone ) cannot detect perforin expression within activated CD8+ T-cells in the same ICS assay format . As shown in Figure 1A , the total HIV-specific CD8+ T-cell response magnitude to Pol , Env , Nef , or TRVVV stimulation did not differ substantively across the groups , but EC displayed a somewhat higher Gag-specific response . The lack of large differences in response magnitude is in agreement with previous studies that measured the total magnitude of CD8+ T-cell responses in EC and CP using flow cytometry [7] , [8] , [13] . We next determined the relative contribution of CD107a , IFN-γ , TNFα , IL-2 , and MIP1α to the HIV-specific CD8+ T-cell response ( Fig . 1B ) . In general , no clear trends emerged in overall functionality between the groups . For example , compared to EC , CP demonstrated a slightly enhanced ability to degranulate , lower levels of TNFα , but no statistically significant difference in the proportion of the average HIV-specific CD8+ T-cell response comprised of either IFN-γ or MIP1α . The largest difference in functionality was IL-2 expression , which was higher among EC and VC compared to CP . Previous studies have also shown enhanced production of IL-2 after HIV-specific stimulation in subjects with low or undetectable viremia [7] , [8] , [10] . Similar overall observations were found for the individual HIV antigens as well ( data not shown ) . We next assessed perforin expression by HIV-specific CD8+ T-cells in each cohort group . We consistently observed higher co-expression of perforin within responding cells from EC compared to VC or CP for all HIV antigens ( Fig . 1C shows representative Nef-specific responses producing IFN-γ; other HIV antigens are not shown but yielded similar results ) . In fact , perforin expression comprised a significantly greater proportion of the average HIV-specific CD8+ T-cell response in EC than in CP ( Fig . 1D ) . The relative contribution of perforin to the CD8+ T-cell response was significantly higher ( ∼3 fold ) in EC compared to CP for all of the individual HIV antigens ( Fig . 1E ) . In addition to the proportion of the HIV-specific CD8+ T-cell response comprised of perforin , EC also displayed a greater magnitude of perforin expression upon stimulation by all HIV antigen pools compared to both VC and CP ( Fig . S2 ) . However , we found no correlation among EC between the total magnitude of an HIV-specific response and the corresponding amount of perforin expression ( Fig . S3 ) . As shown in Figure S4 , there was , however , some variability among EC subjects in the contribution of perforin to the HIV-specific CD8+ T-cell response . Within some EC there was low perforin expression induced by one HIV antigen ( e . g . Gag ) but higher perforin production to another peptide pool ( e . g . Pol ) . Some EC demonstrated high HIV-specific perforin in response to every antigen . Although several EC did express low levels of HIV-specific perforin , only 20% of all EC in the cohort failed to achieve 30% perforin for the CD8+ T-cell response to at least one of the antigen pools ( data not shown ) . In contrast , only 15% of CP demonstrated even one HIV antigen-specific CD8+ T-cell response comprised of 30% perforin ( data not shown ) . Thus , our data suggests that EC are not simply a homogenous group of HIV-infected individuals and do demonstrate some variability , which is in agreement with previous findings [7] , [29] . Next , we examined the functional profile of the average Nef-specific CD8+ T-cell response among the EC , VC , and CP groups ( Fig . 2A and 2B; the other HIV antigens are not shown but yielded similar results ) . Only the functional combinations that were significantly different between at least two of the groups are shown in Figure 2A; all 64 combinations are shown in Figure S5 . We rarely observed simultaneous expression of all six functions because perforin and IL-2 are generally not co-expressed by the same cell [30] . The average Nef-specific functional profile in EC and VC was composed of more CD8+ T-cells than in CP that simultaneously expressed five functions ( Fig . 2B ) . Additionally , the percentage of the Nef-specific response that was perforin-positive ( black arcs in Fig . 2B ) was significantly higher among EC ( 44% ) compared to VC ( 27%; p<0 . 05 ) or CP ( 14%; p<0 . 001 ) . Similar findings were observed for Gag- , Pol- , Env- , and TRVVV-specific responses ( data not shown ) . The majority of perforin was produced by cells expressing only a single other function: CD107a or MIP1α ( Fig . 2B ) . The CD8+ T-cells that co-expressed CD107a and perforin likely upregulated perforin de novo since a cell that was CD107a+ presumably lost all ( or nearly all ) of its granule-associated perforin through the process of degranulation . As shown in Figure S6 , the proportion of the HIV-specific response in EC that was both CD107a+ and perforin+ was significantly higher than CP for all HIV antigens . The second major population of perforin+ cells co-expressed only MIP1α . The relevance of this population is unclear . However , we have previously shown that activated CD8+ T-cells can transport newly synthesized perforin directly to the immunological synapse without trafficking first through cytolytic granules [23] . Thus , despite the absence of apparent degranulation , MIP1α+ perforin+ cells may potentially be involved in ongoing cytolytic activity . One consistent host factor associated with durable control of HIV is the presence of certain HLA class I alleles , particularly HLA-B27 and B57 [1] , [4] , [31] , [32] , [33] . Other HLA-B alleles have also been associated with delayed disease progression or lower viral loads , including HLA-B13 , B15 , B51 , and B58 [5] , [6] . Among EC in our cohort , 54% of the subjects expressed HLA-B27 or B57 , while 32% of VC carried these alleles ( data not shown ) . Additionally , 43% of EC in the study cohort expressed either HLA-B13 , B15 , B51 , or B58 , while 32% of VC carried these alleles ( data not shown ) . As shown in Figures 3A and S7 , we found no association between protective HLA-B status and perforin expression to any HIV peptide pool in either EC or VC ( Gag shown in Fig . 3A , Nef shown in Fig . S7 , and data not shown ) , or when perforin expression to all HIV peptide pools was averaged within each subject ( Fig . 3B ) . Thus , there was no apparent relationship between protective HLA-B alleles and the capacity of HIV-specific CD8+ T-cells to express perforin after stimulation . We next examined the memory phenotype , based on surface expression of CD27 , CD45RO , and CD57 , of HIV-specific CD8+ T-cells in each group . The majority of HIV-specific CD8+ T-cells that expressed perforin in EC , VC , and CP were CD27-CD45RO-CD57+/- ( Fig . 4A and 4B and data not shown ) , commonly considered an effector-type profile , which is in agreement with previous reports that examined the presence of perforin in various human CD8+ T-cell memory subsets [34] , [35] . This phenotype was common to virtually all perforin+ HIV-specific CD8+ T-cells regardless of their specificity for Gag , Pol , Nef , Env or TRVVV ( Fig . 4A and data not shown ) . HIV-specific CD8+ T-cells among many CP subjects were skewed toward a CD27+CD45RO+/- memory phenotype ( Fig . 4C ) , as previously shown [8] , [36] , [37] . However , a higher proportion of HIV-specific CD8+ T-cells in EC than in CP displayed a memory phenotype consistent with highly differentiated effector cells ( Fig . 4C ) . Overall , the presence of CD27-CD45RO- HIV-specific CD8+ T-cells was less common among CP than EC ( Fig . S8 ) in agreement with a previous study [14] . The absence of effector-like HIV-specific CD8+ T-cells in CP is not , however , reflective of the total CD8+ T-cell pool in these individuals . A substantial fraction of CD8+ T-cells in CP that responded to CEF stimulation were CD27-CD45RO- ( Fig . 4D ) . However , responding Gag-specific CD8+ T-cells within the same subjects were primarily CD27+CD45RO+ ( Fig . 4D ) . Having observed higher perforin expression in HIV-specific CD8+ T-cells in EC , we next examined the relationship between perforin expression and viral load . We found a significant inverse correlation between the average HIV-specific perforin expression within each subject and HIV viral load ( Fig . 5A ) . This inverse relationship was found for every individual HIV antigen specificity ( data not shown ) and when only considering subjects with detectable viremia ( EC subjects excluded; Fig . S9 ) . We also found a statistically significant positive correlation between CD4+ T-cell counts in the blood and HIV-specific perforin expression by CD8+ T-cells across all subjects ( Fig . S10 ) , a finding most likely driven by the high CD4+ T-cell counts among the EC subjects ( Table 1 ) . Furthermore , when we examined the other functional parameters in a similar manner , we only found a statistically significant inverse relationship between IL-2 expression and viral load ( Fig . S11 ) , which is an expected result based upon previous studies . To better understand the relationship between viral load and perforin expression , we next compared HIV-specific CD8+ T-cell responses among EC to viremic nonprogressors ( VNP ) , who maintain stable CD4+ T-cell counts in the face of consistently high viral loads ( median 35 , 000 viral RNA copies/mL plasma; Table 1 ) without progressing to AIDS . The infection duration in both groups was similar ( 17 vs . 20 years in the absence of therapy; Table 1 ) . Therefore , by comparing these two groups , we can control for the rate of CD4+ T-cell decline , progression rate , and duration of infection . As shown in Figure 5B , perforin expression by HIV-specific CD8+ T-cells in VNP is significantly lower than EC and actually closely resembles the perforin levels observed in CP . Together , these data indicate that the degree of HIV-specific CD8+ T-cell perforin expression is predictive of the ability to control viral load independent of the rate of CD4+ T-cell decline , progression status , or infection duration . In order to determine whether the low perforin expression associated with progression was reversible , we examined HIV-specific perforin expression by CD8+ T-cells in HAART-treated individuals with undetectable HIV viremia ( Table 1 ) . Compared to EC , the total CD8+ T cell response magnitude was lower in HAART-treated subjects to Gag , Pol , and Nef stimulation; however , only the difference in the total Gag-specific magnitude reached statistical significance ( Fig . S12 ) . Despite some differences in total magnitude , there were no substantive differences in the relative contribution of degranulation , IFN-γ , TNFα , or MIP1α production ( Fig . S13 ) . However , HIV-specific perforin expression in HAART-suppressed subjects was considerably lower than EC , and was similar to the levels observed in CP ( Fig . 5B ) . Thus , the ability to express and rapidly upregulate perforin by HIV-specific CD8+ T-cells in chronic HIV infection is not recovered following HAART .
While many cell surface markers , activation profiles , and functional parameters of both ex vivo HIV-specific CD8+ and CD4+ T-cells have been shown to correlate with control of viremia [8] , [38] , [39] , [40] , [41] , [42] , few , if any , can potentially mediate direct control of HIV replication through the lysis of infected cells . Here we have shown that perforin expression by ex vivo HIV-specific CD8+ T-cells is significantly higher in EC compared to patients with uncontrolled viral replication . HIV-specific CD8+ T-cells that express perforin bear predominantly an effector phenotype , indicating that effector populations , in addition to central memory populations [43] , [44] , may be critically important to the control of HIV infection . We also find an inverse correlation between perforin expression by HIV-specific CD8+ T-cells and viral load . Together , these results represent an unique assessment of HIV-specific immunity and provide a novel platform for measuring potential vaccine efficacy in clinical trials . There is little question regarding the crucial importance of perforin in the control of infectious pathogens . Indeed , mutation or dysregulation of perforin in humans results in compromised cellular immunity and enhanced susceptibility to viral infections [45] . Previous reports on ex vivo HIV-specific CD8+ T-cells have uniformly found low or absent perforin expression in both CP and EC and no detectable differences in perforin levels between the groups [13] , [25] , [27] , [37] , [46] . However , these studies have in retrospect only defined the level of granule-associated perforin within resting HIV-specific CD8+ T-cells due to unforeseen limitations in the anti-perforin antibody employed in these studies [23] , [24] . Due to chronic activation and continual presence of viral antigen - albeit extremely low levels in EC [47] - HIV-specific CD8+ T-cells are unlikely to reach a true resting state; therefore , it is unlikely these cells accumulate cytolytic granules containing perforin in vivo . However , our results indicate that this does not preclude their ability to upregulate new perforin upon antigen-specific stimulation , a killing mechanism that we have recently shown potentiates the cytotoxic ability of human CD8+ T-cells [23] . We have shown previously that both the commonly used anti-perforin antibody ( δG9 clone ) and the anti-perforin antibody used in this study ( B-D48 clone ) stain resting CD8+ T-cells equivalently [24] . Thus , previous research that found no difference in the levels of perforin within resting HIV-specific CD8+ T-cells between EC and CP [13] , [25] , [27] , [37] , [46] were not necessarily incorrect . Here , we have shown using a perforin antibody that can detect both granule-associated and granule-independent forms of perforin that HIV-specific CD8+ T-cells from EC express this protein to a higher degree than patients with uncontrolled viremia . It is important to note , though , that the B-D48 clone cannot specifically distinguish pre-formed from newly upregulated perforin using flow cytometric-based assays . Nevertheless , to identify the potential contribution of perforin produced de novo , we examined the proportion of the HIV-specific CD8+ T-cell response that both degranulated ( CD107a+ ) yet remained perforin+ after six hours of stimulation . These CD8+ T-cells that co-expressed CD107a and perforin likely upregulated new perforin; they have presumably lost most or all of their pre-formed perforin through the process of degranulation . By analyzing this specific population , we found that the proportion of the HIV-specific CD8+ T-cell response in EC that co-expressed CD107a+ and perforin+ was significantly higher than CP to all HIV antigens . However , we have also shown that newly synthesized perforin largely bypasses cytotoxic granules [23]; therefore , we are almost certainly underestimating the levels of perforin upregulation by focusing only on cells that have degranulated . The capacity of unstimulated CD8+ T-cells from EC to begin to eliminate HIV-infected autologous CD4+ T-cell targets within several hours of co-incubation has been previously reported [14] . The results from this study suggested that HIV-specific CD8+ T-cells were responsible for the elimination of infected CD4+ T-cells through a mechanism dependent on cell-to-cell contact and MHC-I restriction . Our findings on perforin upregulation by HIV-specific CD8+ T-cells shortly after stimulation are consistent with the results of Saez-Cirion and colleagues [14] and may even be a mechanism to explain their findings . Moreover , another previously published report indicated that HIV-specific CD8+ T-cells kill targets through the use of cytotoxic granules and not by the Fas/FasL pathway [48] . Therefore , available evidence indicates that the perforin/granzyme pathway of cytotoxicity is likely the primary means by which HIV-specific CD8+ T-cells kill infected cells in vivo . Our findings here suggest that HIV-specific CD8+ T-cells in EC have a superior cytotoxic potential by expressing higher levels of perforin . This supposition is supported by recent work from Migueles and colleagues [17] . These authors showed that HIV-specific CD8+ T-cells from EC accumulate more granule-associated perforin as a result of their superior ability to proliferate in vitro compared to CD8+ T-cells from progressors . They also found that higher amounts of perforin ( and granzyme B ) in HIV-specific cells translate into an enhanced ability to lyse infected targets . Thus , together with the previous work of Migueles et al . , our results show that EC have an enhanced ability to upregulate perforin either directly ex vivo or after in vitro proliferation . Given what is known about the importance of perforin in orchestrating cytotoxicity , we can conclude that HIV-specific CD8+ T-cells from EC certainly have the potential to elicit elimination of infected targets to a greater degree than progressors , which may directly impact viral load . Furthermore , we know that newly synthesized perforin traffics directly to the immunological synapse - the site of action of cytotoxicity [23] . Besides differences in cytotoxic capabilities , HIV-specific CD8+ T-cells from EC have also been shown to be more polyfunctional in nature; they can simultaneously degranulate and produce multiple functional molecules , such as IL-2 , IFN-γ , and TNFα , to a greater extent than CD8+ T-cells from progressors [8] , [49] . Our results here confirm and extend these findings . Polyfunctional HIV-specific CD8+ T-cells were also found in this study to comprise a greater fraction of the response in EC than in CP . Interestingly , we rarely observed HIV-specific CD8+ T-cells capable of producing all six functions simultaneously . This results from a dichotomous relationship between perforin and IL-2 production from the same cell [30] . The implications of this dichotomy are profound for our understanding of effective HIV-specific CD8+ T-cell responses: IL-2 producing CD8+ T-cells will presumably not have immediate cytolytic activity; conversely , perforin producing CD8+ T-cells may be inherently reliant upon production of IL-2 from cells in their surrounding environment for maintenance or modulation . Both cell types are most likely crucial to maintaining protective immunity . The IL-2 producing cells may be part of a population of CD8+ T-cells that can maintain itself through autocrine production of IL-2 . This ability may be important in the setting of diminished CD4+ T-cell help in HIV infection [10] . Alternatively , these cells may represent a self-renewing memory population of CD8+ T-cells responsible for long-term maintenance of effector cells . IL-2 producing cells likely do not display any direct anti-viral capability directly after activation [30] but may be able to differentiate into perforin producing effector cells . The increased IL-2 production observed by both HIV-specific CD8+ T-cells and CD4+ T-cells [42] in EC may also directly increase cytotoxic potential , as has recently been reported [50] , [51] . Interestingly , we found that a substantial fraction of the total perforin production by HIV-specific CD8+ T-cells among EC comes not from polyfunctional populations but instead from cells that elicit only a single other measured functional parameter: specifically MIP1α or CD107a . In previous studies , where perforin upregulation was not measured , the potential importance and cytotoxic capabilities of these populations was not appreciated . On this note , the degree of functionality of a CD8+ T-cell response is only reflective of what functional parameters are actually being measured . For example , we find that most CD8+ T-cells that upregulate perforin also produce granzyme B upon stimulation [30] . Therefore , many of the CD8+ T-cells found in this study to co-express perforin with MIP1α and/or CD107a , may actually be highly “polyfunctional” if we had also examined the expression of other parameters critical for cytotoxicity , such as granzyme B . Our data show that perforin expressing cells bear effector-like phenotypic markers . Thus , while a central memory phenotype is often considered a protective phenotype in HIV infected individuals , our results suggest that effector cells are also of significance . It should be noted , however , that simply achieving effector status does not guarantee the expression of perforin . Indeed , some HIV-specific CD8+ T-cells in both EC and CP were CD27-CD45RO- yet did not express perforin . Our results suggest that effector status is necessary but not sufficient for perforin upregulation . The importance of effector cells in the control of HIV infection is further supported by recent observations by Picker and colleagues who found that a rhesus-CMV-based SIV vaccine vector could stimulate protective effector SIV-specific CD8+ T-cells [52] . Our results suggest that perforin expression by HIV-specific CD8+ T-cells is not readily recovered by inhibition of viral replication or reduction in chronic immune activation by HAART - a finding which is consistent with a previous report showing that HAART treatment does not restore other functional parameters , such as proliferative capacity , polyfunctionality , or cytotoxic capacity [53] . We also found that perforin production does not appear to be directly influenced by beneficial HLA-B haplotypes or the relative maintenance of CD4+ T-cell levels over time . Whether perforin expression is lost early , late , or progressively during infection remains unclear . Further studies are necessary to identify the mechanism ( s ) underlying the relative absence of perforin upregulation in progressive HIV infection , and , if possible , to discover a means by which this critical function can be regained or elicited through therapeutic intervention .
Blood specimens were acquired with the written informed consent of all study patients and with the approval of the institutional review board at each respective institution where patient materials were collected: University of Pennsylvania ( IRB# 809316 ) , University Hospitals Case Western Medical Center ( IRB# FWA00003937 ) , University of Alabama at Birmingham ( IRB# X090708004 ) , University of Toronto and St . Michael's Hospital ( IRB# 07-106 ) , and Harvard University ( IRB# 2003-P-001894 and IRB# 2003-P-001678/75 ) . The study was conducted following the principles stipulated in the Declaration of Helsinki . We examined ex vivo HIV-specific CD8+ T-cell responses from 35 elite controllers ( EC ) , 29 viremic controllers ( VC ) , 27 chronic progressors ( CP ) , and 6 viremic nonprogressors ( VNP ) . Most EC and VC were recruited from outpatient clinics at local Boston hospitals as well as from providers throughout the United States [54] . Several EC were also recruited from clinics associated with the University of Toronto . PBMC samples from CP were from clinics associated with the University of Pennsylvania Center for AIDS Research , the University of Toronto , Case Western Reserve University , and the University of Alabama at Birmingham . VNP samples were obtained from the University of Toronto and Case Western Reserve University . PBMC samples from 15 HAART-suppressed patients were obtained from Harvard University and the University of Toronto . EC were defined by consistent plasma HIV RNA levels below the limit of detection ( e . g . <75 copies/mL by bDNA or <50 copies/mL by ultrasensitive PCR ) in a minimum of three determinations of plasma HIV RNA spanning at least a 12-month period . VC consistently maintained viral load between 50 and 2 , 000 copies/mL , while the majority of viral load measurements of CP were above 10 , 000 copies/mL . CD4+ T-cell counts were not considered for inclusion criteria in the EC , VC , or CP groups . VNP were identified as subjects with consistently high viremia ( above 10 , 000 copies/mL on average ) but with relatively stable CD4+ T-cell counts after long-term infection . It is the relative preservation of CD4+ T-cell numbers in spite of sustained high level HIV replication that was used to distinguish the VNP group clinically from CP . All subjects from the EC , VC , CP , and VNP groups were off antiretroviral therapy for at least 6 months prior to the sampling date; yet most subjects were treatment-naive . Refer to Table 1 and Table S1 for more detailed information on the study cohort . The following antibodies were used in this study: anti-CD4 PE Cy5 . 5 , anti-CD14 APC Alexa 750 , anti-CD19 APC Alexa 750 , anti-CD8 Texas Red-PE , anti-IFN-γ Alexa 700 ( Invitrogen , Carlsbad , CA ) , anti-CD107a FITC , anti-IL-2 APC , anti-TNFα PE Cy7 ( BD Pharmingen , San Diego , CA ) , anti-MIP1α PE ( R&D Systems , Minneapolis , MN ) , anti-CD27 PE Cy5 ( Beckman Coulter , Fullerton , CA ) , anti-CD57 Qdot 565 , anti-CD3 Qdot 585 , and anti-CD45RO Qdot 605 or 705 ( custom ) . Custom conjugations to Quantum ( Q ) dot nanocrystals were performed in our laboratory with reagents purchased from Invitrogen . The anti-perforin antibody ( B-D48 clone ) was purchased from Diaclone ( Besancon , France ) and conjugated to Pacific Blue ( Invitrogen ) in our laboratory . Cryopreserved PBMC were thawed and subsequently rested overnight at 37°C , 5% CO2 in complete medium ( RPMI supplemented with 10% FBS and 1% L-glutamine ) . The following morning , the cells were washed with complete medium and resuspended at a concentration of 2×106 cells/mL if sufficient cell numbers were available . Costimulatory antibodies ( anti-CD28 and anti-CD48d; each at 1 µg/ml final concentration; BD Biosciences; San Jose , California ) , monensin ( 1 µg/ml final concentration; BD Biosciences; San Jose , California ) and Brefeldin A ( 1 µg/ml final concentration; Sigma-Aldrich; St . Louis , Missouri ) were also added to each condition . Anti-CD107a was added at the start of all stimulation periods , as described previously [28] . PBMC were incubated at 37°C , 5% CO2 for six hours with overlapping 15-mer peptide pools encompassing HIV-1 ( clade B ) Gag , Pol , Env , Nef , and the viral accessory proteins ( TRVVV ) [as 5 separate conditions] . PBMC from many of the subjects were also stimulated with a CEF peptide pool , which contains peptides derived from CMV , EBV , and Influenza virus . Each individual peptide in the pools was at a final concentration of 2 µg/mL for all stimulations . At the end of six hours , cells were stained with Aqua amine-reactive dye ( Invitrogen; Carlsbad , California ) for 15 minutes in the dark at room temperature in order to later identify viable cells . A cocktail of antibodies was then added to the cells to stain for surface markers for an additional 20 minutes . Following staining for cell surface molecules , cells were permeabilized using the Cytofix/Cytoperm kit ( BD Biosciences; San Jose , California ) according to the manufacturer's instructions . A cocktail of antibodies against intracellular markers was then added to the cells and allowed to incubate for one hour in the dark at room temperature . Finally , cells were fixed in 1x PBS containing 1% paraformaldehyde ( Sigma-Aldrich; St . Louis , Missouri ) before being stored in the dark at 4°C until the time of collection on the flow cytometer . For each stimulation condition , at least 500 , 000 total events were acquired using a modified LSRII ( BD Immunocytometry Systems , San Jose , California ) . Data analysis was performed using FlowJo ( version 8 . 8 . 4; TreeStar , Ashland , Oregon ) and Spice ( version 4 . 2 . 3 , Dr . Mario Roederer , NIH , Bethesda , Maryland ) . Reported data have been corrected for background , and only responses with a total frequency above 0 . 25% of memory CD8+ T-cells ( after background subtraction ) were considered for analysis . Boolean gating analysis was carried out once positive gates were established for each functional parameter . This analysis resulted in 64 possible combinations of the 6 measured functions . Importantly , two combinations were ignored in all analyses: ( 1 ) events negative for all measured functional parameters and ( 2 ) perforin single-positive cells . By analyzing the data in such a manner , we only examined perforin expression resulting from HIV-specific stimulation . For this reason , perforin expression was only considered within activated , HIV-specific CD8+ T-cells expressing at least one other functional parameter . Refer to Figure S1A for further information on the gating strategy . As indicated by the gating strategy , naïve cells ( CD27+CD45RO- ) were excluded when performing all analyses except for the memory phenotyping data presented in Figure 4 . All graphing and statistical analysis was performed using R ( version 2 . 8 . 1 ) , JMP ( version 7 ) , or GraphPad Prism software ( version 5 . 0a ) . Functionality was compared between study groups using nonparametric tests ( Mann-Whitney test for two groups; Kruskal-Wallis test followed by a Dunns test for multiple comparisons when comparing three or more groups ) . Correlations between viral load or CD4+ T-cell counts and perforin expression were based on Spearman correlation coefficients . Comparisons between groups of specific functional permutations were based on a Lachenbruch's Two-part Wilcoxon test . This analysis simultaneously tests for a difference in the proportion of subjects who have an above zero response and a difference in the magnitude of the response [55] , [56] . Only those functional combinations for which the average response was greater than zero were considered to be relevant for consideration . Functional permutations were considered significantly different if the p value was below 0 . 01 . In all figures , * denotes a p value <0 . 05 , ** denotes a p value <0 . 01 , and *** denotes a p value <0 . 001 . Unless otherwise noted , error bars represent the standard deviation .
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While the majority HIV-infected individuals progress to AIDS , a fraction of these individuals—for reasons not completely understood—do not develop AIDS and also display sustained control over viral replication; these subjects are sometimes referred to as elite controllers ( EC ) . Prior evidence has shown that HIV-specific CD8+ T-cells , a component of adaptive immunity against intracellular pathogens , from EC exhibit enhanced functionality compared to individuals with progressive disease . Therefore , HIV-specific CD8+ T-cells likely play an important role in the favorable clinical outcomes witnessed in EC . We show in this study that the ability to control HIV replication in EC is associated with the expression of a protein called perforin , a critical molecule that enables CD8+ T-cells to directly kill infected cells - thereby preventing the spread of HIV to previously uninfected cells . In infected subjects with nonprogressive disease , we show that HIV-specific CD8+ T-cells demonstrate a superior ability to express perforin upon antigen-specific stimulation , whereas in progressors this property is diminished . Thus , we identify a functional capability of CD8+ T-cells , readily measured by standard intracellular cytokine staining assays , that potentially has a direct impact on HIV replication in vivo . These findings may , therefore , provide an important qualifier for future HIV vaccine research .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"infectious",
"diseases/hiv",
"infection",
"and",
"aids",
"immunology/immunity",
"to",
"infections",
"immunology/immune",
"response"
] |
2010
|
Perforin Expression Directly Ex Vivo by HIV-Specific CD8+ T-Cells Is a Correlate of HIV Elite Control
|
Chikungunya virus ( CHIKV ) , an alphavirus that causes fever and severe polyarthralgia , swept through the Americas in 2014 with almost 2 million suspected or confirmed cases reported by April 2016 . In this study , we estimate the direct medical costs , cost of lost wages due to absenteeism , and years lived with disability ( YLD ) associated with the 2014–2015 CHIKV outbreak in the U . S . Virgin Islands ( USVI ) . For this analysis , we used surveillance data from the USVI Department of Health , medical cost data from three public hospitals in USVI , and data from two studies of laboratory-positive cases up to 12 months post illness . On average , employed case-patients missed 9 days of work in the 12 months following their disease onset , which resulted in an estimated cost of $15 . 5 million . Estimated direct healthcare costs were $2 . 9 million for the first 2 months and $0 . 6 million for 3–12 months following the outbreak . The total estimated cost associated with the outbreak ranged from $14 . 8 to $33 . 4 million ( approximately 1% of gross domestic product ) , depending on the proportion of the population infected with symptomatic disease , degree of underreporting , and proportion of cases who were employed . The estimated YLDs associated with long-term sequelae from the CHIKV outbreak in the USVI ranged from 599–1 , 322 . These findings highlight the significant economic burden of the recent CHIKV outbreak in the USVI and will aid policy-makers in making informed decisions about prevention and control measures for inevitable , future CHIKV outbreaks .
Chikungunya virus ( CHIKV ) , an alphavirus transmitted by Aedes ( Stegomyia ) species mosquitoes , was introduced into the Americas in December of 2013 [1] . By April 2016 , almost 2 million suspected or confirmed cases were reported in 45 countries and territories in the Caribbean , Central , South , and North America [2 , 3] . Acute symptoms , including high fever , severe polyarthralgia , headache and myalgia , often resolve within 7–10 days [4–6] . However , a proportion of cases , up to 79% in some outbreaks , report persistent arthralgia and chronic inflammatory rheumatism , resulting in decreased quality of life for months to years following initial infection [5–16] . Currently , there is no antiviral treatment or vaccine for the infection , there are no specific therapeutics for chronic symptoms , and public health prevention measures , such as mosquito reduction , have thus far proven to be insufficient [4 , 17] . CHIKV was first identified to be locally transmitted in the U . S . Virgin Islands ( USVI ) in June 2014 . By February 2015 , almost 2 , 000 suspected cases had been reported in a population of 103 , 574 people [18 , 19] . The epidemiology of the CHIKV outbreak in the USVI has been previously described [20] . Previous studies from CHIKV outbreaks in La Réunion , Colombia , and India have noted the large resource burden from these outbreaks including high healthcare costs , lost wages due to absenteeism , and decreased quality of life for months following infection [21–26] . To our knowledge , the economic impact of the recent CHIKV epidemic in the Caribbean and years lived with disability ( YLDs ) associated with long-term sequelae of CHIKV illness have not been quantified . This information would inform decisions about prevention and control measures for inevitable , future CHIKV outbreaks . Using a societal perspective , we aim to estimate the cost of illness and burden of disease associated with the 2014–2015 CHIKV outbreak in the USVI by estimating direct medical costs , indirect cost of lost productivity due to absenteeism , and YLDs associated with long-term sequelae of the outbreak .
Verbal informed consent was obtained from all participants before interviewing them . Parental/guardian consent was acquired on behalf of all child participants and parents/guardians responded for children under the age of 12 . Verbal informed consent was documented on the questionnaire by the interviewer and entered into the database . Oral consent was used because almost half of the interviews took place over the phone . Ethics approval for this study , as well as the use of verbal consent was obtained from the University of the Virgin Islands and the University of Washington . Estimates of the direct and indirect cost of the outbreak were based on suspected cases reported to USVI Department of Health ( DOH ) . All costs were expressed in 2014 U . S . dollars ( USD ) . A suspected case was defined as a resident of the USVI who visited a hospital or healthcare clinic on St . John , St . Thomas , or St . Croix with acute onset of fever ( ≥38°C ) and severe arthralgia or arthritis not explained by another medical condition . A laboratory-positive case was defined as a suspected case whose blood sample tested positive for either CHIKV RNA or IgM antibodies . Of all reported suspected CHIKV cases who were tested , 30% tested negative for CHIKV . Therefore , when we used surveillance data to estimate potential costs , we used 0 . 70 as the proportion of non-tested reported suspected CHIKV cases who would have been positive had they been tested . Laboratory-positive cases were contacted by telephone and invited to participate in a follow-up investigation at 1–2 , 6 and 12 months after the acute phase of illness , as previously defined ( S1 Table ) [27] . The 1 to 2-month questionnaire asked about hospitalization and healthcare utilization during the first months after initial infection . The 12-month questionnaire asked additional questions about use of prescription medication and healthcare utilization between the first and last interview . Estimates of YLDs were based on reports of persistent arthralgia . Similar to a previous study [21] , we defined persistent arthralgia as joint pain at least once per week that occurred more than 15 days after the acute phase of illness . We used data from two previous studies to determine YLDs . The first study assessed the proportion of persons with laboratory-positive CHIKV infection who reported persistent arthralgia compared to a non-symptomatic control group of individuals who visited an emergency room of a hospital or a health care clinic in the USVI and were interviewed regarding presence of persistent arthralgia [27] . The control group was defined as USVI residents who did not report experiencing sudden onset of fever and joint pain in June 2014-June 2015 . The second study was a population-based study of seroprevalence that assessed the frequency of persistent arthralgia approximately 12 months following the introduction of the CHIKV and determined the proportion of persistent arthralgia attributable to CHIKV infection [28] . Productivity lost per CHIKV case was estimated assuming a standard 40-hour work week , and using the average hourly wage for each island [29] . Average hourly wages from the USVI were not available by gender or age . The following formula was used to estimate value of time lost due to CHIKV disease: Valueoftimelost=Mean#ofworkdaysmissedateachtimepoint*8hoursperday*averagehourlywage* ( total#ofreportedlaboratory-positiveCHIKVcases+0 . 70*#ofnon-testedreportedsuspectedCHIKVcases ) where mean # of work days missed include both market and non-market productivity . To obtain an estimate of the total wages lost for cases who were not reported , we used data from a 2015 seroprevalence study in the USVI that found an infection rate of 31% , ( 95% CI: 26%–36% ) , with 72% of those infected reporting symptomatic infection [28] . Based on this information , we estimated the fraction of the population with symptomatic infection to be 22% ( 0 . 31 * 0 . 72 ) . The estimated number of symptomatic CHIKV infections in the USVI population was multiplied by productivity lost per person to obtain an overall cost estimate of absenteeism due to the outbreak . This estimate assumes that absenteeism from school and other non-market activities has the same monetary value as formal employment . In reviewing both CHIKV and dengue cost-of-illness methodologies , some studies included all individuals with the disease or condition regardless of employment status ( to capture overall loss of productivity ) , while others included only those who were officially employed [22 , 23 , 25 , 30–38] . As a sensitivity analysis , we calculated absenteeism associated with CHIKV illness for only those who were employed ( 52 . 2% of the USVI population as of 2010 ) [39] . Because the 2015 serosurvey estimated that 70% of symptoms ( acute fever and joint pain ) among CHIKV infected individuals were attributable to their infection , we also conducted a sensitivity analysis to estimate the cost of absenteeism when including only the proportion of individuals with symptoms directly attributable to CHIKV infection ( 0 . 31 * 0 . 72 * 0 . 70 = 0 . 16 ) [26] . The medical costs for two phases of the illness ( acute and long-term ) were estimated with two different sources of data . For the acute phase of illness , inpatient and outpatient charges of all suspected CHIKV cases from Governor Juan F . Luis Hospital and Medical Center ( JFLHMC ) , the public hospital in St . Croix , were obtained from the finance department of the hospital . Mean costs of inpatient and outpatient visits among reported cases were calculated separately and multiplied by the total number of inpatient and outpatient visits captured by the USVI DOH surveillance system . Calculation assumes standard of care was the same across hospitals . These costs were applied to patients on all three islands , because cost data for suspected CHIKV cases were unavailable from Schneider Regional Medical Center ( SRMC ) in St . Thomas and Myra Keating Community Health Center ( MKCHC ) in St . John , the other two public healthcare facilities in the USVI . A sensitivity analysis was conducted for the missing cost data from SRMC and MKCHC based on the mean cost of standard outpatient and inpatient visits from those two healthcare facilities ( S2 Table ) . Data on diagnosis codes and length of inpatient stay were not collected . For the cost of subsequent outpatient visits up to 12 months after illness onset , the mean cost of standard outpatient visit was obtained from the finance departments of JFLHMC , SRMC and MKCHC . The mean number of additional healthcare visits reported by cases for treatment of CHIKV after acute illness from the interview sample was calculated from the 1–2 and 12-month questionnaires . The mean number of visits was multiplied by the total number of reported laboratory-positive cases and 70% of suspected but not tested cases by island to obtain an overall estimate of additional healthcare costs up to 12 months after acute illness . Note that these calculations are limited to reported cases , assuming that only people who sought healthcare at 1–2 months after the outbreak would seek follow-up care . Current literature indicates that a recall period of 1–2 months provides reliable estimates for outpatient visits [40–43]; however , previous studies have shown that 5%–47% of visits were not reported when individuals were interviewed about healthcare utilization of physician visits during a 12 month recall period [44 , 45] , while other studies have shown no underreporting [46] . Due to potential underreporting of healthcare utilization 12 months after illness onset , a sensitivity analysis was performed using a range of underreporting from 5–47% ( S3 Table ) . Prior studies estimating YLDs for CHIKV have used disability weights for osteoarthritis and rheumatoid arthritis since a disability weight has not been assigned to CHIKV disease [22 , 24 , 26 , 47] . However , these weights are from the 1990 Global Burden of Disease [48] . Here , we use the disability weight for post-acute effects from infectious diseases from the 2013 Global Burden of Disease study [49] , and use the weights for osteoarthritis and rheumatoid arthritis as a sensitivity analysis to maintain consistency with previous studies . We calculated YLDs to estimate the amount of time , ability , and activity lost due to persistent arthralgia from CHIKV illness using the following equation [50]: YLD= ( Disabilityweight*NumberofsymptomaticCHIKVinfectionsintheUSVI*Prevalenceofpersistentarthralgia6monthsafteracuteillnessonset*182 . 625/365 . 25 ) + ( Disabilityweight*NumberofsymptomaticCHIKVinfectionsintheUSVI*Prevalenceofpersistentarthralgia12monthsafteracuteillnessonset*182 . 625/365 . 25 ) The number of symptomatic CHIKV infections in the USVI is based on an estimate from the 2015 serosurvey in the USVI [28] . To ensure that reported persistent arthralgia among cases was due to CHIKV and not from other causes , we used a 32% prevalence estimate of persistent arthralgia among CHIKV cases interviewed at 6 months and a 21% prevalence estimate of persistent arthralgia among CHIKV cases interviewed at 12 months: 44% at 6 months and 33% at 12 months net of the 12% prevalence of persistent arthralgia in the non-symptomatic control group [27] . This latter estimate is consistent with the prevalence of reported arthritis in the USVI population from the Behavioral Risk Factor Surveillance System Report ( 15% ) [39] . We also used a more conservative 12-month estimate of persistent arthralgia attributable to CHIKV from the 2015 serosurvey in the USVI of 12% ( 95% CI: 7–17% ) [28] . The serosurvey did not assess persistent arthralgia at 6 months . Years of life lost were not calculated because cause of death could not be determined for the three deceased suspected CHIKV cases .
One to two months after acute disease onset , 86 laboratory-positive CHIKV cases were interviewed . Of the cases who were employed ( 33% ) , 89% reported missing work due to CHIKV illness ( Table 1 ) . On average , employed cases reported missing 6 days of work within 1–2 months after onset of CHIKV symptoms . One to two months after their initial healthcare visit , 33% of cases reported seeking additional healthcare at a clinic after initial infection and 9% reported being hospitalized due to CHIKV illness . Six months after acute disease onset , 165 laboratory-positive CHIKV cases were interviewed . Of the cases who were employed ( 41% ) , 88% reported missing work due to CHIKV illness , 4–5 months after their 1–2 month interview ( Table 1 ) . On average , employed cases reported missing two additional days of work 4–5 months after the 1–2 month interview . Twelve months after acute disease onset , 128 of the 165 laboratory-positive CHIKV cases were interviewed . Of the cases who were employed ( 34% ) , 9% reported missing work due to CHIKV illness during the six months after their 6-month interview ( Table 1 ) . On average , employed cases reported missing one additional day of work during that time period . Of the interviewed cases , 25% reported seeking additional healthcare 10–11 months after the 1–2 month interview and 24% reported taking prescription medication in the last 12 months for CHIKV-related symptoms . Forty percent ( n = 12 ) of those who reported taking prescription medication indicated that they were prescribed prednisone for joint pain and 47% ( n = 14 ) reported taking prescribed opioids for joint pain . The average cost of absenteeism related to CHIKV disease 1–2 months after illness onset ranged from $713–$825 per person , depending on island of residence ( Table 2 ) . Six months after illness onset , the average cost of absenteeism ranged from $275–$318 per person and 12 months after illness onset , the average cost per person ranged from $148-$172 . The total estimated cost of absenteeism associated with acute and long-term CHIKV illness up to 12 months after CHIKV disease onset was $1 . 76 million for all reported laboratory-positive cases and 70% of all suspected but not tested CHIKV cases . However , when using the estimated proportion of symptomatic CHIKV infection in the USVI ( 0 . 22 ) , almost 12 times the number of individuals were infected with CHIKV than were captured by surveillance data . When including these additional cases , the total estimated cost of absenteeism for acute and long-term CHIKV illness up to 12 months after CHIKV disease onset was $29 . 7 million ( Table 2 & Fig 1 ) . The total estimated cost of absenteeism associated with acute and long-term CHIKV illness up to 12 months after CHIKV disease onset for only the USVI population that was employed ( 52% ) was $15 . 5 million but this figure does not account for absenteeism from school and other non-market activities . Among infected individuals with symptoms attributable to CHIKV ( 0 . 16 ) , the estimated cost of absenteeism associated with acute and long-term CHIKV illness up to 12 months after CHIKV disease onset was $21 . 6 million , and $11 . 3 million when including only the proportion of the USVI population who was employed ( S4 Table ) . The average cost of an outpatient visit for a suspected CHIKV case during the acute phase of illness was $1 , 526 and the average cost of an inpatient visit was $16 , 982 ( Table 3 ) . These costs include laboratory testing and prescription medication . Of the 1 , 929 reported suspected cases , 1 , 850 had outpatient visits and 79 suspected cases were hospitalized . Assuming that 70% of these suspected cases were laboratory-positive , the total estimated cost of outpatient and inpatient healthcare visits associated with suspected CHIKV cases during the acute phase of the outbreak was $2 . 9 million , with the hospitalized cases comprising 48% of the total cost . As shown from the sensitivity analysis in S2 Table , adjusting the direct costs by the relative average outpatient cost reduces the total estimated direct cost by 27% . The 86 CHIKV cases interviewed 1–2 months after acute illness reported , on average , having 0 . 5 additional healthcare visits related to CHIKV disease ( Table 4 ) . The average cost of a standard outpatient visit varied by healthcare facility and island but ranged from $234-$600 . The 128 CHIKV cases interviewed 12 months after acute illness reported having on average 0 . 62 additional healthcare visits related to CHIKV disease 10–11 months after their 1–2 month interview . Therefore , the total estimated cost of additional outpatient healthcare visits related to CHIKV disease up to one year after illness onset was $620 , 400 ( Table 4 & Fig 1 ) . The sensitivity analysis for the potential underreporting of healthcare utilization 12 months after illness onset provided the following range of total estimated costs of additional outpatient healthcare visits related to CHIKV disease up to one year after illness onset: $620 , 400 for zero underreporting to $781 , 100 for 47% underreporting ( S3 Table ) . As a result , the total estimated direct cost associated with the CHIKV outbreak in the USVI ranges from $3 , 536 , 000-$3 , 696 , 700 . The total direct and indirect estimated cost associated with the 2014–2015 CHIKV outbreak in the USVI ranges from $14 , 827 , 500–$33 , 424 , 600 depending on the proportion of the population infected with symptomatic CHIKV , the degree of underreporting of healthcare utilization , and the proportion of cases who were employed at the time of the outbreak .
This study estimated the total direct and indirect cost and burden of disease associated with the 2014–2015 CHIKV outbreak in the USVI . The total estimated cost associated with the outbreak ranged from $14 . 8–$33 . 4 million , of which 12–24% was direct costs and 76–88% was indirect costs . Up to 1% of gross domestic product ( GDP ) in the USVI was estimated to be lost due to the CHIKV outbreak ( GDP in 2014 = $3 . 67 billion USD [51] ) . Our direct cost estimate of the outbreak in the USVI was comparable to the cost estimate of the 2005–2006 outbreak in La Réunion , ( $3 . 5 million for 22 , 786 cases in the USVI [$155 per case] compared to $50 . 4 million for 266 , 000 cases in La Réunion [$189 per case] ) [23 , 52] . Our indirect cost estimates , were also comparable when including only the proportion of the population who was employed [23] . The seroprevalence estimate of symptomatic CHIKV cases suggests that between 16–22% of the USVI population had symptomatic infection [26] . The surveillance data may not have captured many of these cases because during the height of the outbreak , hospitals and healthcare clinics reached capacity and had to turn residents away who were seeking care . Additionally , due to public health announcements in the media during the outbreak , many residents were aware of symptoms associated with infection and knew treatment for CHIKV did not exist , so they may have opted to stay home instead of seeking healthcare . We estimated that the number of years lived with disability associated with chronic symptoms of CHIKV ranges from 427–1 , 407 . Our YLD estimates are more conservative than the disability-adjusted life year estimates from Latin America , due to the fact that we provided a lower estimate of persistent arthralgia attributable to CHIKV illness at 12 months ( 21% and 12% compared to ~50% in Latin America ) [24 , 53] . This difference is present because both studies in the USVI [27 , 28] subtracted the prevalence of persistent arthralgia among non-diseased individuals from the prevalence of persistent arthralgia among CHIKV cases 12 months after acute illness , whereas the study in Latin America did not [53] . The Second United States Panel on Cost-Effectiveness in Health and Medicine recommends counting both productivity costs and YLDs for an analysis from the societal perspective , based on evidence that disability weights reflect health rather than productivity [[54]] . Although their recommendation does not necessarily apply to cost-of-illness studies , two of five published CHIKV cost-of-illness studies presented both indirect costs and YLDs , while the other three studies only presented YLDs [22–24 , 26 , 47] . Certain limitations should be considered when interpreting the results of this study . The total direct and indirect estimated costs of the 2014–2015 CHIKV outbreak in the USVI may lack precision . Ambulatory service charges , absenteeism of caretakers for those who were ill due to CHIKV and additional hospitalization costs after the acute phase of illness could not be measured and were therefore not included in analysis . The analysis also does not account for the cost of individuals with symptomatic CHIKV who did not seek acute care but did seek follow-up care . The mean cost of outpatient and inpatient visits was based solely on data from JFLHMC , and does not account for varying costs from SMRC , MKCHC and private healthcare clinics . We addressed this issue by conducting a sensitivity analysis of direct costs based on the standard cost of healthcare visits at SMRC and MKCHC . Although another sensitivity analysis was conducted to account for underreporting of healthcare utilization , the true magnitude of underreporting up to 12 months after illness onset remains unknown . Additionally , there are three potential sources of bias in the estimates of disability: 1 ) if cases with persistent arthralgia were more likely to participate in the follow-up study , disability would be over-estimated , 2 ) if the cause of death among the three cases who died was primarily CHIKV , disability would be underestimated by excluding their years of life lost , and 3 ) there are other documented long-term sequelae associated with CHIKV disease that we did not account for , such as mental health diagnoses , that would result in an underestimation of disability [55 , 56] . As a result , our YLD estimates are either consistent or more conservative than previous CHIKV studies [24 , 26 , 48 , 56] . Lastly , although using means , instead of medians to estimate costs is standard practice in economic analysis , the estimates presented might be elevated by certain individuals who incurred higher costs than others . Despite these limitations , this is one of the initial cost-of-illness studies that quantifies the number of years lived with disability due to long-term sequelae of CHIKV illness in the Caribbean . The results from this study highlight the substantial economic and long-term health burden of a CHIKV outbreak and provide evidence to inform policy decisions about prevention and control measures for inevitable future CHIKV outbreaks .
|
Chikungunya , a virus carried and transmitted by mosquitoes , causes fever , headache , and severe joint pain in humans that often resolves within 7–10 days . However , a proportion of cases , up to 79% in some outbreaks , report persistent joint pain and chronic inflammatory rheumatism , resulting in decreased quality of life for months to years following initial infection . In 2014 , chikungunya virus swept through the Americas , resulting in almost 2 million suspected or confirmed cases reported by April 2016 . Previous studies have noted the large resource burden from chikungunya outbreaks , including high healthcare costs , lost wages due to absenteeism , and decreased quality of life for months following infection . Our work aimed to estimate the direct medical costs , cost of lost productivity due to absenteeism , and years lived with disability associated with the chikungunya outbreak in the U . S . Virgin Islands . This information may aid policy-makers in making informed decisions about prevention and control measures for inevitable , future chikungunya outbreaks .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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"togaviruses",
"chikungunya",
"infection",
"pathogens",
"tropical",
"diseases",
"microbiology",
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"financial",
"management",
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] |
2019
|
Estimating the cost of illness and burden of disease associated with the 2014–2015 chikungunya outbreak in the U.S. Virgin Islands
|
Bdellovibrio bacteriovorus invade Gram-negative bacteria in a predatory process requiring Type IV pili ( T4P ) at a single invasive pole , and also glide on surfaces to locate prey . Ras-like G-protein MglA , working with MglB and RomR in the deltaproteobacterium Myxococcus xanthus , regulates adventurous gliding and T4P-mediated social motility at both M . xanthus cell poles . Our bioinformatic analyses suggested that the GTPase activating protein ( GAP ) -encoding gene mglB was lost in Bdellovibrio , but critical residues for MglABd GTP-binding are conserved . Deletion of mglABd abolished prey-invasion , but not gliding , and reduced T4P formation . MglABd interacted with a previously uncharacterised tetratricopeptide repeat ( TPR ) domain protein Bd2492 , which we show localises at the single invasive pole and is required for predation . Bd2492 and RomR also interacted with cyclic-di-GMP-binding receptor CdgA , required for rapid prey-invasion . Bd2492 , RomRBd and CdgA localize to the invasive pole and may facilitate MglA-docking . Bd2492 was encoded from an operon encoding a TamAB-like secretion system . The TamA protein and RomR were found , by gene deletion tests , to be essential for viability in both predatory and non-predatory modes . Control proteins , which regulate bipolar T4P-mediated social motility in swarming groups of deltaproteobacteria , have adapted in evolution to regulate the anti-social process of unipolar prey-invasion in the “lone-hunter” Bdellovibrio . Thus GTP-binding proteins and cyclic-di-GMP inputs combine at a regulatory hub , turning on prey-invasion and allowing invasion and killing of bacterial pathogens and consequent predatory growth of Bdellovibrio .
Bdellovibrio bacteriovorus is a small , predatory deltaproteobacterium which invades other Gram-negative bacteria wherein it replicates . Bdellovibrio can encounter their prey by fast motility , driven by rotation of a single flagellum in liquid environments [1] , [2] , or by slow gliding motility on solid surfaces [3] , but do not show social- or S-motility a process that is shown by other deltaproteobacteria ( discussed below ) . In Bdellovibrio invasion into the prey cell periplasm requires T4P , thus pilus-minus cells are incapable of host/prey-dependent ( HD ) growth and must be cultivated on artificial media as HI - host/prey-independent - cells [4] , [5] . In flagellate HD Bdellovibrio the T4P are at the non-flagellar pole and prey-invasion occurs only from that anterior pole . On surfaces a flagellum is not present and the Bdellovibrio glide bidirectionally . Both HD and HI Bdellovibrio can glide and invade prey on surfaces . Our study began by examining the genetics of surface motility control in Bdellovibrio . This work led us to find that proteins known for surface motility control in a second deltaproteobacterium , Myxococcus xanthus , have evolved to control predatory invasion of bacteria by Bdellovibrio . Regulation of surface motility in the deltaproteobacterium M . xanthus ( which is always non-flagellate ) , has been well characterised by pioneering work of the Søgaard-Andersen [6] , Mignot [7] , Zusman [8] , Hartzell [9] and Kaiser [10] groups for its two types of bidirectional surface motility . These are social ( S ) -motility , swarming movement of streams of cells using retraction of T4P at alternate poles of the cells; and adventurous ( A ) -motility , characterised by the movement of individual cells on a surface . A-motility ( or gliding ) , is thought to be powered by cell envelope-spanning motor-protein complexes , [11] , [12] , though the precise mechanism of movement is still being revealed [13]–[15] . In M . xanthus , T4P localize to one pole at a time . Occasionally , M . xanthus cells reverse direction; this involves a switch in the polarity of the two motility systems , including a switch in the pole at which T4P assembly occurs . Thus , M . xanthus cells can assemble T4P at both poles but at any one time , T4P are found only at one pole [16] . Recent data suggest that the four putative gliding motor-gene operons in the B . bacteriovorus HD100 genome are evolutionarily linked to those A-motility gene clusters in Myxococcus [17] , with subtle distinctive absences and additions likely reflecting Bdellovibrio morphology and gliding differences . Bdellovibrio exhibits A-motility on surfaces in a gliding process that does not use T4P [3] . In this gliding , A-motility , individual Bdellovibrio cells move bidirectionally , cells can follow each other along previous paths and reversals of individual cells and re-orientations are seen . Gliding may be a particularly important mechanism by which Bdellovibrio explores biofilms and locates bacteria to prey upon [3] , [18] . It is critical for HD Bdellovibrio to be able to explore or leave solid surfaces by gliding ( when its flagellum cannot operate ) . Unlike other non-predatory bacteria , Bdellovibrio HD cells cannot replicate outside prey without acquiring “HI mutations” to do so [19] , [20] , thus without surface motility they could be trapped and starve . B . bacteriovorus gliding motility is slow , with cells moving , on average , 16 µm hr−1 [3] compared to the 24–36 µm hr−1 of Myxococcus [21] . Both B . bacteriovorus and M . xanthus show reversals in gliding direction . In Myxococcus , reversals during surface motility are known , from the work of the Søgaard-Andersen and Mignot labs , to be regulated by a Ras-like GTPase , MglA , which polarises the cell during gliding [6] , [7] , and GTPase-activating protein ( GAP ) protein MglB , which activates the GTPase activity of MglA to inhibit cellular reversals [6] , [7] . MglA is important for activation of both the A- and S- motility “engines” ( S motility engines are T4P ) , at the alternating leading pole , during bidirectional movements [6] , [7] . In the absence of MglA , Myxococcus is both A- and S- non-motile . This means that MglA in M . xanthus , in conjunction with interacting partner RomR , regulates the localization/pole-switching activity of both T4P and gliding engine component proteins , in this bipolar bacterium . Chemotactic signals via the Frz system control cellular reversals in M . xanthus [22] via the RomR response regulator; RomR receives signals from the chemosensory Frz system and this modulates MglA activity [23] , [24] . Although romR is conserved in Bdellovibrio , the genes encoding the Frz apparatus are not . Bdellovibrio gliding is controlled by the bacterial secondary messenger cyclic-di-GMP . A diguanylyl cyclase ( dgcA ) mutation abolishes gliding , rendering Bdellovibrio cells unable to glide out of a consumed prey cell bdelloplast on a surface , even 2 hours after making lytic pores in it [25] . The c-di-GMP receptor CdgA ( GVNEF – a degenerate GGDEF protein ) was found to be present at the predatory pole of B . bacteriovorus and deletion of cdgA slowed prey-invasion significantly , showing a link between c-di-GMP signalling and predation [25] . Whilst the B . bacteriovorus HD100 genome encodes MglA ( Bd3734; accession: NP_970444 . 1 ) , it does not encode an MglB homologue [23] . This report caused us to ask how bipolar switching might be achieved during Bdellovibrio gliding on surfaces; and whether the non-equivalent poles of the monoflagellate Bdellovibrio in liquids might correlate with an alternative role for MglABd . Here we show that MglABd is required for predatory invasion , as well as being associated with changes in gliding reversal behaviour in B . bacteriovorus , but is not required for gliding motility per se . This activity of MglABd occurs without an MglB partner , but in a cell with a RomRBd homologue . Both of these latter proteins are important to the control of bipolar motility in Myxobacteria . However we show that RomRBd has an essential role for growth in Bdellovibrio . We also report a previously undescribed interacting protein partner of MglA , and show that MglABd and RomRBd interact with this tetratricopeptide repeat protein ( TPR ) which is also required for predation . TPR is expressed from an operon that encodes a TamAB transport system and again TamA was essential for growth . Implications of this for predation and the onset of predatory growth upon prey-invasion are discussed . Whilst MglAMx is involved in regulation of T4P-mediated social motility in M . xanthus , we show that MglABd is involved in Bdellovibrio in the control of pilus extrusion for the process of T4P-mediated invasion of prey cells at the single predatory pole . We show that a complex of proteins , additional to the T4P , is required at the ‘biting’ pole to organise the prey-entry machinery .
To investigate the role of MglABd , a deletion strategy was adopted screening for possible Bdellovibrio mutants in both prey/host-dependent ( HD ) and host-independent ( HI ) growth modes . All attempts to inactivate mglA in host/prey-dependent B . bacteriovorus HD100 were unsuccessful , despite screening many more cells than required to generate other Bdellovibrio deletion strains [26] ( 364 revertants obtained from second crossover events , but no deletion mutants , from three separate conjugations ) ; suggesting that MglABd is essential for an aspect of the predatory life cycle . Three host-independent ( HI ) ΔmglABd strains were obtained through sucrose-suicide counter-selection from a total of 76 screened . When challenged with prey , ΔmglABd HI B . bacteriovorus strains were unable to lyse E . coli in either a soft agar prey-lawn on the surface of YPSC plates , or in liquid culture ( Figure 1A ) . Introduction of wild type mglABd by in cis complementation method ( as described previously [25] ) restored predation ( Figure 1B ) confirming that MglABd is essential for predatory growth . The ΔmglA HI B . bacteriovorus strain could not reduce E . coli numbers in liquid culture , though this strain could still attach to the exterior of potential prey cells ( Figure 2 ) . A parallel assay showed that 43 . 5% of wild-type B . bacteriovorus HI cells attached to , or had entered , E . coli prey cells after 1 hour ( Figure 2A ) but no ΔmglA HI strain formed prey-bdelloplasts ( Bdellovibrio cause the prey to round-up into ‘bdelloplast’ structures after invasion ) , even after 22 hours . Figure 2 also shows that both the ΔmglA HI and ΔpilA HI ( Δbd1290 , which is known to lack pili and is obligately host-independent [4] ) could still attach to E . coli prey cells , albeit at a lower frequency . This suggests that pili are not a prerequisite for attachment , ( although they are required for prey-invasion [4] , [5] ) , and suggests that the ΔmglA HI predatory defect is not due to the inability of the Bdellovibrio cell to attach to prey cells . The nature of the predatory defect of the ΔmglA HI strain was analysed further by microscopy , using a fluorescent E . coli S17-1::pMAL_p2-mCherry prey strain [27] . Addition of the ΔmglA HI strain to E . coli S17-1::pMAL_p2-mCherry and incubation for 22 hours demonstrated that although ΔmglA HI cells could attach to the outside of a prey cell , they could not invade to form bdelloplasts ( Figure 2B ) . A wild-type HI B . bacteriovorus strain ( HID50 ) successfully invaded E . coli cells and killed them ( as shown in Figure 1 ) and at the 22 hour stage was shown to have formed bdelloplasts from 26 . 3% of the remaining E . coli , compared to zero bdelloplasts for the ΔmglA HI strain . Thus the deletion of mglABd abolished a process required for prey-invasion . The ΔmglA HI strain showed a similar phenotype to that observed in a pilus-minus ( ΔpilA ) strain , which was known to be unable to invade prey cells [4] . We hypothesised that B . bacteriovorus ΔmglA might be defective in the synthesis or extrusion of pili , preventing prey cell invasion . This seemed plausible given that MglA regulates both the pole-switching of the A-motility and Type IV pilus-mediated S-motility systems in M . xanthus . Transmission electron microscopy of HI Bdellovibrio cultures grown to an OD600 of 0 . 2–0 . 3 showed that a wild type HI control had pili in 14 . 3% of cells , whilst ΔmglA HI had pili in only 2 . 3% of cells analysed ( p = 0 . 02 ) . These data suggested that MglABd regulates formation of pili; loss of mglA reduces the number of piliated cells . But , in contrast to the ΔpilA strain which completely lacks pilus fibres , the total inability of ΔmglA cells to invade , despite the presence of a low ( but significant ) frequency of piliated cells , suggests that these few pili present in the ΔmglA cells are not competent to facilitate invasion . This could be due to a defect in pilus retraction upon attachment to prey surfaces , or a requirement for another MglA-controlled factor to mediate invasion . Candidate MglABd-interacting proteins for invasive processes are discussed later . Knowing that MglABd controls pilus-mediated bacterial invasion in B . bacteriovorus , but that in M . xanthus both pilus-mediated S-motility and gliding A-motility are MglA controlled , we used time-lapse microscopy to observe ΔmglA and wild-type B . bacteriovorus strains for gliding motility on 1% agarose/CaHEPES . Surface motility in B . bacteriovorus begins after a period of incubation on an agarose surface and allows exploration of environments for potential prey . In contrast to recent studies in Myxococcus xanthus which showed that a ΔmglAMx strain is non-motile on surfaces [7] , and a mglAG21V strain displays hyper-reversals during A-motility [6] , we found that Bdellovibrio ΔmglA cells showed sustained gliding runs on surfaces ( Figure 3 ) , indicating that MglABd is not absolutely required for Bdellovibrio cells to glide . A Bdellovibrio strain with C-terminally His8-tagged MglABd , expressed from the endogenous bd3734 promoter in cis , with a plasmid promoter-driven wild-type copy of mglABd , could be grown predatorily , in contrast to the ΔmglA strain which was non-predatory . In a previous study in M . xanthus , the presence of tagged MglAMx protein in conjunction with wild-type MglAMx allowed gliding to remain fully functional [7] . In contrast to the sustained gliding motility of the ΔmglABd strain ( Figure 3A ) , the predatory B . bacteriovorus HD100 MglA-His8 showed increased reversals during gliding: on average 9 . 0 reversals hr−1 ( n = 28 ) , significantly more than wild-type HD100 cells with an average of 3 . 2 reversals hr−1 ( n = 21 ) ( p<0 . 001 ) ( Figure 3B , C ) . The same hyper-reversal phenotype was also observed in B . bacteriovorus HD100 MglA-mCherry cells ( data not shown ) . MglABd ( Bd3734 ) shares significant sequence similarity ( Figure 4 ) with MglAMx ( MXAN1925 accession: YP_630169 . 1 ) , with 64% protein identity and 82% similarity ( NEEDLE global alignment ) . The majority of residues shown to be important for MglAMx function [28] , [29] are conserved in MglABd ( Figure 4A–D ) . The P-loop region ( 19GXXXXGKT26 ) of MglAMx was shown by Søgaard Andersen and co-workers to be important for GTP hydrolysis , and for MglA function [28] , and substitutions in this region , such as G21V , were reported to decrease hydrolysis [6] . The P-loop region of MglABd contains a natural serine at residue 21; the corresponding G12S substitution in eukaryotic G protein Ras activates Ras protein [30] , essentially locking the protein in a GTP-bound state , in the same way as a Ras G12V substitution . This suggests that MglABd exists in a permanently GTP-bound state . The G21-equivalent residue is a conserved glycine across 7 deltaproteobacterial genera ( Figure S1A ) which all also have a conserved mglB gene , though in Bdellovibrio the equivalent residue is a serine . The difference at residue 21 in the MglABd sequence suggested to us a reason why we did not observe conservation of the gene encoding MglB in Bdellovibrio , as the GAP activity of an MglB would likely be ineffective on a permanently GTP-bound MglA protein such as that suggested by the MglABd sequence with S at position 21 . We thought that it might also explain the lack of a Bdellovibrio Frz system [23] , which stimulates motility reversals in M . xanthus , as a mutation , causing MglAMx G21V , bypasses the requirement for Frz for reversals in that deltaproteobacterium [6] . Thus we turned to examine the presence of mglB in the deltaproteobacterial relatives of Bdellovibrio . We also tested the conserved RomRBd protein , while also looking for other proteins , specific to Bdellovibrio , with which MglABd might interact . In M . xanthus , RomR is found at both poles of the cell and interacts with both MglA and MglB to link the Frz system to regulate polarity control [23] , [24] . The majority of sequenced deltaproteobacteria genomes contain both mglA and mglB , and these are often co-transcribed at the same locus , including in M . xanthus where the MglBMX protein has an important role in motility [6] , [7] , [31] . Although the mglA gene product in B . bacteriovorus HD100 shares extensive sequence similarity with other MglA proteins , there is no mglB homologue in the HD100 genome , despite neighbouring genes ( dnaX , recR , mglA and a DUF149-encoding gene ) showing conserved synteny to other deltaproteobacteria that do have an mglB . The closely related B . bacteriovorus Tiberius [32] also lacks an mglB homologue . The predatory , invasive , marine bacterium Bacteriovorax marinus is also closely related to B . bacteriovorus , although the Bdellovibrio and Bacteriovorax genera have diverged separately from Myxobacteria . A 16S rRNA phylogenetic tree of the deltaproteobacteria shows the ancestral lineage leading to Bdellovibrio and Bacteriovorax diverged from the ancestral lineage leading to the clade including Myxococcus xanthus [33] and in that divergent Bdellovibrio branch we detect mglB loss ( Figure S1A ) . We found that in B . marinus , which also has an mglA gene ( BMS_0054 ) , there is an adjacent putative mglB homologue ( BMS_0053 ) , both genes lying downstream of recR ( Figure S1B ) . BMS_0053 shares only limited sequence similarity with other MglB Roadblock domain proteins ( BMS_0053 , 168 residues , shares 22% identity and 43% similarity ( NEEDLE global alignment ) with M . xanthus MglB protein , 159 residues , Figure S1C ) . This highly divergent MglB homologue in Bacteriovorax is likely still functional , since no frameshift or nonsense mutations have arisen in the B . marinus lineage , and protein sequence length is conserved; however , its function is unclear . We are unable to test whether mglB is under positive selection ( dN/dS>1 ) in Bacteriovorax because synonymous substitution rates are saturated for available sequence comparisons ( dS>2 ) . The Bacteriovorax MglA homologue is much more conserved ( 66% identity and 83% similarity to MglABd ) and may function in an analogous predatory role to that of B . bacteriovorus . As MglABd had both similarities and differences to MglAMx , we sought to identify proteins that interact with MglA homologue Bd3734 in B . bacteriovorus as we reasoned that these proteins might have a predatory role . We used a pull-down co-purification assay with proteins from the predatory B . bacteriovorus strain producing MglABd with a C-terminal His8 tag from the endogenous mglABd promoter , mentioned above . For the co-purification assay , a host-independent isolate of the MglABd-His8 strain was used , as previous array data showed that mglABd transcription is up-regulated in wild type HI cells , ( which remain predatory but are longer than attack phase Bdellovibrio ) . Whole cell lysates of this HI strain were used in the assay , in which the bait His-tagged protein MglABd binding to TALON-NX cobalt-charged resin allowed interacting proteins to be identified ( Figure S2 ) that were not present in the control without the His-tag . MglABd co-purified with Bd2492 ( accession: NP_969302 . 1 ) ( Figure S2 ) - a B . bacteriovorus protein with a hypothetical annotation , with predicted tetratricopeptide repeat ( TPR ) domains typically involved in protein-protein interactions . Bands were excised from the gel and analysed by LC-MS/MS . Corresponding regions of the wild-type HID13 control lane were also analysed , and neither MglABd nor Bd2492 were found in these regions , suggesting that MglABd and Bd2492 ( TPRBd ) interact in vivo . The mglA ORF and bd2492 ORF were cloned into pUT18C and pKT25 vectors containing T18 and T25 fragments of adenylate cyclase , respectively [34] . The bacterial two-hybrid assay for MglA and Bd2492 showed a strong signal ( Figure S3A–B ) suggesting that the two B . bacteriovorus proteins interact . This interaction was supported by the observation that MglA co-purifies with His6-tagged Bd2492 in nickel-affinity chromatography of E . coli lysates heterologously expressing these two proteins from plasmid pD2492N/3734 ( Figure S4 ) . Gel filtration and SDS-PAGE of purified MglA and Bd2492-His6 indicated that the MglA-Bd2492 complex has an Mw of approximately 63 kDa and exists predominantly as a heterodimeric complex of 1∶1 stoichiometry ( data not shown ) . As the B . bacteriovorus mglA mutant was non-predatory , we tested whether bd2492 ( encoding TPRBd ) was essential for predatory growth . All attempts to inactivate bd2492TPR in host-dependent B . bacteriovorus HD100 were unsuccessful ( 68 revertants obtained from second crossover events , but no deletion mutants ) . Two host-independent ( HI ) Δbd2492 strains were obtained through sucrose-suicide counter-selection from a total of 10 screened . When challenged with prey , Δbd2492TPR HI strains were unable to lyse E . coli in liquid culture ( Figure S5 ) . As with the ΔmglA HI strains , the Δbd2492TPR HI strains could still attach to E . coli prey cells ( attachment assay; 26 . 6% of E . coli cells had attached Bdellovibrio ) , but could not invade to form bdelloplasts ( invasion assay; 0/389 E . coli cells ) . The B . bacteriovorus Δbd2492TPR HI strain was still able to glide on 1% agarose CaHEPES ( data not shown ) . TPR gene bd2492 is co-transcribed with bd2494 and bd2495 ( Figure S6 ) . The same gene synteny is also found in M . xanthus ( MXAN_5763-5766 ) and B . marinus SJ ( BMS_0137-140 ) ( Figure 5 ) where the gene encoding a TPR domain protein is followed by genes encoding homologues of Bd2494 and Bd2495 . In M . xanthus , the genes encoding homologues of Bd2492 and Bd2494 ( MXAN_5766 and MXAN_5764 ) are interrupted by a gene encoding a putative Sec system ATPase , MXAN_5765 . B . bacteriovorus gene bd2492 encodes a hypothetical 353 amino acid tetratricopeptide repeat ( TPR ) protein; TPRpred ( http://tprpred . tuebingen . mpg . de/tprpred ) was used to predict TPR domains [35] . TPRpred confirmed that both BMS_0137 ( 524 residues; accession: YP_005034048 . 1 ) and MXAN_5766 ( 1031 residues; accession: YP_633903 . 1 ) are also predicted to contain TPR domains . All three TPR domain proteins do not have predicted signal sequences , as predicted by SignalP [36] . Bd2494 is a predicted transmembrane protein with a DUF490 domain . Both BMS_0139 ( accession: YP_005034049 . 1 ) and MXAN_5764 ( accession: YP_633901 . 1 ) also contain predicted DUF490 domains . Bd2495 is a surface antigen variable number repeat domain protein of the ( outer membrane protein ) Omp85 ( TamA/BamA/YaeT ) superfamily , hereafter termed TamABd; homologues of which are conserved in both B . marinus ( BMS_0140; accession: YP_005034050 . 1 ) and M . xanthus ( MXAN_5763; accession: YP_633900 . 1 ) . As mentioned in the introduction , RomRMx interacts with the MglAMX signalling system to regulate surface motility in response to Frz system signals [23] , [24] , but the Frz system is not conserved in Bdellovibrio . We assessed the interaction of the RomRBd ( Bd2761; accession: NP_969553 . 1 ) with the MglA-interacting protein TPRBd ( Bd2492 ) by bacterial two-hybrid ( Figure S3A ) . RomRBd shares homology with the REC domain and C-terminal region of RomRMx , whilst the remainder of the protein is less well conserved ( Figure S7 ) . RomRBd and TPRBd interact in the BTH assay ( Figure S3A , C ) . We found that RomRBd and MglABd interacted weakly , but not significantly ( p = 0 . 18 ) ( Figure S3B–C ) . Fluorescent tagging of RomRBd and TPRBd with C-terminal mCherry revealed that both proteins are localised at only one pole of the cell . Co-incubation with E . coli prey cells confirmed that both RomRBd-mCherry and TPRBd-mCherry are found at the anterior , prey-interaction pole of B . bacteriovorus cells ( Figure 6 ) . Fluorescent tagging of MglABd with mCherry typically showed cells with diffuse fluorescence localization in cells directly after applying to 1% agarose/CaHEPES ( i . e . not gliding ) ( Figure 6 ) ; 63% of HD100 MglA-mCherry Bdellovibrio had diffuse fluorescence , the remainder showing a unipolar focus ( 28 . 4% ) or bipolar foci ( 8 . 6% ) . We found earlier that the Bdellovibrio ΔmglA strain does not show a hyper-reversal or non-motility phenotype ( Figure 3 ) . Thus , the regulation of MglABd localization in the control of gliding reversals ( in the absence of MglB and Frz ) is likely to employ an alternative signalling system to that of M . xanthus . Previous work suggested that this could be c-di-GMP as we have shown [25] that lack of GGDEF protein Bd0367 DgcA abolished gliding exit from bdelloplasts . We had also had previously noted a link between a c-di-GMP binding protein and prey-invasion in Bdellovibrio [25] . Degenerate GGDEF ( GVNEF ) protein CdgA , Bd3125 ( accession: NP_969891 . 1 ) , is located at the prey invading pole of B . bacteriovorus and lack of this polar protein causes a very significant slowing of prey-invasion with bdelloplast formation taking 40–90 minutes compared to 30–40 minutes for wild type [25] . We concluded in that paper that “CdgA organises processes at the Bdellovibrio “nose” that are crucial to rapid prey-invasion” . In our current study , we found that both RomRBd and TPRBd ( though not MglA ) interacted with CdgA in the bacterial two-hybrid assay ( Figure S3 ) , supporting this idea . Whether RomRBd has a role in the regulation of gliding motility will be the subject of a subsequent study , but our interaction data suggested a link between RomRBd and predatory growth ( as ΔcdgA was affected in predation [25] ) , so we tested for a romRBd deletion strain . Given the CdgA and TPRBd interactions found at the B . bacteriovorus invasive pole , we speculated that RomRBd would be required for prey-invasion . Attempts to delete romRBd , both predatorily ( HD ) and host-independently ( HI ) , were unsuccessful ( HD 104; HI 120 revertants screened ) , suggesting that RomRBd is required for both predatory and host-independent Bdellovibrio growth . As RomRBd interacted , by BTH , with TPRBd , encoded in an operon with the tamAB genes , we speculated that the TamAB complex would also be required for predatory growth . Attempts to delete tamABd also proved unsuccessful ( HD 140; HI 97 revertants screened ) , suggesting that TamABd is also essential for both phases of Bdellovibrio growth .
There are three lines of evidence to suggest this: ( 1 ) The deletion of mglABd caused a non-prey-invasive phenotype ( Figure 1 ) and severely reduced pilus formation on the cell surface; ( 2 ) the natural substitution in MglABd of serine for glycine ( Figure 4 ) at the position equivalent to residue 21 in MglAMx suggests that MglABd exists in a permanently GTP-bound state , and is not involved in the GTPase cycle which is key to the alternate bi-polar switching of motility proteins in M . xanthus [6] , [7]; ( 3 ) RomR-mCherry is unipolar in B . bacteriovorus ( Figure 6 ) , in contrast to its asymmetric bipolar localization in Myxococcus , controlling MglAMx positioning . We had hypothesised that RomRBd might be involved in regulating pole activity to control gliding motility . As RomRBd was found at the predatory pole only , this suggested an alternative role . We could not detect a significant interaction between RomRBd and MglABd by BTH , but we did detect a significant interaction with Bd2492 TPR protein ( Figure S3 ) , which is also at the anterior pole ( discussed later ) . The RomRBd location at the anterior pole of B . bacteriovorus puts it where prey-invading T4P are located . Lotte Søgaard-Andersen's group showed that an mglAMx deletion mutant resulted in unipolar RomRMx , with RomRMx and T4P , ( used in that bacterium for bipolar social motility ) , found at the same pole [37] . Sequence- and localization- differences between unipolar RomRBd and MglABd ( in the absence of an MglB ) in B . bacteriovorus , versus those in M . xanthus ( which has MglB ) , might explain why T4P are only found at the anterior Bdellovibrio pole where they control prey-invasion . Deletion of romRBd abolished Bdellovibrio growth in both HI and predatory conditions , but in M . xanthus romR is viable with abolition of gliding motility and reduction of T4P-dependent social motility [23] , [24] . Thus RomRBd , which does show some sequence divergence from RomRMx ( Figure S7 ) , could be reporting T4P activity and prey-invasion , at the anterior pole , back to initiate Bdellovibrio growth . It should be recalled that predatory “attack phase” Bdellovibrio do not replicate outside prey , but initiate replication when prey are entered [20] . Our BTH interaction data were too weak to prove a significant interaction between RomRBd and MglABd . This could be interpreted to mean that RomRBd transiently docks with MglABd when RomRBd is complexed at the pole , that other partner proteins are required to contribute to this interaction , or that they do not interact , in contrast to published data for MglAMx [23] , [24] . Our finding that RomRBd is unipolar fits with evidence in M . xanthus that MglBMX is required for bipolar localization of RomRMx [23] and the apparent loss of MglB from the prey-invasive Bdellovibrio lineage in evolution . The Bdellovibrio-like invasive B . marinus has a putative mglB gene , the product of which shows only limited sequence similarity to other MglB Roadblock domain proteins ( Figure S1 ) . This mglBBm gene is highly divergent from mglbMx but likely still functional . It may be undergoing selection to evolve an alternative function , while the B . marinus mglA gene is maintained for a predatory role analogous to that in B . bacteriovorus . MglA and MglB were shown to be conserved by Keilberg and co-workers in many deltaproteobacteria but also occur in some evolutionarily distant bacteria such as the green non sulphur bacteria , Acidobacteria and Deinococcus-Thermus group , Figure S3 in Ref [23] . The authors calculated the following: out of a total of 70 species with ( at least one ) predicted MglA homologue 87% = 61/70 species have MglB and an MglA . Of the 9 without MglB , 4 bacteria had MglA G21 with no MglB; 5 had MglA A/S21 with no MglB . Of these 9 with no MglB , only B . bacteriovorus and one other species , ( a soil Acidobacterium named Candidatus koribacteria versatilis ) , have predicted RomR homologues . Thus bacteria with RomR and MglA and B may have interacting protein complexes that move between poles; but our study on B . bacteriovorus is the first to examine the situation in a bacterium where MglA and RomR are present but MglB is not . As mentioned above , we detected an interaction with an additional protein that could contribute to the localization of MglABd and RomRBd at the single prey-invasion pole of Bdellovibrio . This was with the unipolar tetratricopeptide repeat TPR protein , Bd2492 ( TPRBd ) shown using both His-tag pull-downs and BTH for MglA and BTH for RomR . TPRBd could sequester either MglABd or RomRBd at the prey-invasive pole , regulating their freedom to interact with each other , or promoting an interaction on the TPRBd surface . Deletion of bd2492TPRBd abolished prey-invasion in the same manner as ΔmglABd ( Figure S5 , Figure 1 ) . It was not possible to monitor localization of fluorescently tagged proteins informatively in the HI derivative strains of the non-predatory ΔmglABd and Δbd2492 mutants . This is because HI derivatives have pleomorphic cell morphotypes ( HI cells naturally differ greatly in length and shape ) [38] , and indeed some long HI cells are predatory at both poles [25] . The bd2492 gene is located upstream of , and is co-expressed ( Figure 5 , Figure S6 ) in an operon with , gene bd2494 , which encodes a transmembrane protein with a C-terminal DUF490 domain , homologous to the TamB component of the TamAB autotransporter-secretion system [39] . Bd2494 might dock with TPRBd at the prey-invasive nose . The last gene in the operon ( bd2495 ) encodes a 7-POTRA ( polypeptide-transport-associated ) -domain , outer membrane protein ( OMP ) member of the Omp85 superfamily . The Omp85 protein family includes the BamA component of the BAM complex , known to receive and assemble beta barrel proteins during outer membrane growth [40] . The family also includes the TamA component of the TamAB complex , which aids autotransporter secretion [39]; and two-protein secretion ( TPS ) proteins [41] . The TamA and TamB genes are typically adjacent in proteobacteria [39] , suggesting that the adjacent B . bacteriovorus bd2494-2495 genes encode a TamAB-like transporter . Thus our finding that MglABd and RomRBd interact with a TPR protein ( Figure S3 ) , encoded from the 5′ gene of a tamAB-like operon , suggests that the Bd2494-2495 TamAB-like transport activity might be required for OMP/autotransporter proteins involved in predation . This may account for our observation that some pili are present on the ΔmglA mutant but that despite this , it does not invade due to an effect on TamAB-dependent predatory protein transport . Similarly , the Δbd2492 mutant was also non-predatory ( Figure S5 ) , but attached to prey . This suggests that either: TPRBd and MglABd are important in the positioning of proteins ( probably Bd2494-5 TamABBd ) at the predatory pole of the B . bacteriovorus cell to facilitate prey entry; or that binding of RomRBd and MglABd to TPRBd affects its activity , and that of the TamABBd complex , regulating predatory protein secretion . Reinforcing our observation ( mentioned above ) that RomRBd is essential , we found , by attempting to delete bd2495 , that TamABd was also essential for both HD and HI growth of Bdellovibrio . This suggests that the activity of the TamAB complex ( possibly involving a TPR-mediated interaction with RomRBd ) is required for secretion of proteins required for prey-invasion and both predatory and HI growth . Potential candidates for TamAB export are proteins involved in the synthesis/secretion/maturation of extracellular polysaccharide ( EPS ) or polyelectrolytes; an earlier study proposed that RomR was responsible for stimulating polyelectrolyte secretion in M . xanthus [37] . We cannot yet define whether RomRBd activates a TamAB dependent process that is essential for predatory and HI growth , or whether it reports on the activity of a TamAB complex , via its interaction with TPRBd , to regulate Bdellovibrio growth . This will be the subject of a further extensive genetic study . Although a TPR protein interaction with MglAMx or RomRMx has not been previously reported , the MXAN_5766 gene encoding a TPR domain protein , from a gene cluster with similar synteny to the B . bacteriovorus bd2492-2495 genes ( Figure 5 ) , has previously been implicated in M . xanthus S-motility by transposon studies carried out by the Hartzell group [42] . The low percentages of TPR ORF similarity/identity between MXAN_5766 and Bd2492 could reflect the greatly different protein sizes and may indicate interactions with additional protein partners in M . xanthus . However , in M . xanthus , similar TPR interactions with RomR , MglA and TamAB-like proteins could play a role in bipolar motility control . Whether or not this is the case in M . xanthus , it is clear that TPR , and likely TamABBd , proteins play an important role in defining the single , active , predatory pole of Bdellovibrio . We propose a predatory regulatory ‘hub’ of proteins at the B . bacteriovorus prey-invasive pole ( Figure 7 ) , with the TamAB-associated Bd2492-5 TPRBd protein complex involved in the organisation/assembly of OMPs or autotransporters at the predatory pole . This is reflective of TamAB protein functions in other bacteria ( discussed in [39] ) . Such protein secretion could facilitate predation directly or produce other extra-cellular compounds such as EPS or polyelectrolytes , as mentioned above , which contribute to predatory invasion . Predatory proteins could be secreted in outer membrane vesicles ( OMVs ) ; Sar and Arf GTPases ( homologous to MglA ) have functions in vesicle transport [43] and M . xanthus vesicles likely have an extra-cellular predatory role in the “wolf-pack” [44] hunting of M . xanthus [45] . Our studies show that the directed prey-invasion of Bdellovibrio requires a protein encoded by a tamAB operon , suggesting synergies in TamAB-mediated predation and cell interaction processes of B . bacteriovorus and M . xanthus which is worthy of further investigation . Regulatory protein hubs are reported to control pili and flagella in other bacteria [46] . Considering evolutionary differences that led Bdellovibrio to prey-invasion via a single pole , we also suggest that the absence of mglB in B . bacteriovorus ( and the high degree of divergence of this gene in B . marinus ) , is because MglB is no longer required for pole switching of pili: B . bacteriovorus pili are found at only one - the non-flagellar , prey-invasive pole [4] . This is also concordant with B . bacteriovorus cells being incapable of S-motility ( which would require pole-switching of T4P ) and instead using T4P at a single pole for prey-invasion . However , the absence of an MglB homologue does suggest that an alternative mechanism for regulating reversals during gliding motility is likely to exist . The mechanism by which reduced incidence of pili or a change in their retraction state is caused , in the B . bacteriovorus ΔmglABd strain , remains to be determined . Capeness and coworkers have recently shown that regulation of Bdellovibrio pilus retraction status does correlate with prey-invasion [26] . Pilus retraction occurs through secretin PilQ [47] , which is required for predation in B . bacteriovorus [18] . The OM-assembly of a pilus-biogenesis protein such as PilQ could be affected by the Bd2492-5 TamAB complex activity . Alternatively , OMPs required for secretion of EPS might be perturbed at the Bdellovibrio pole , preventing pilus retraction; EPS is required for pilus retraction in M . xanthus [48] . These considerations will be the subject of a subsequent study . The MglA/RomR-TPR interactions reported in this paper may have evolved from ancient interactions common to ancestors of M . xanthus and Bdellovibrio , and are now used in B . bacteriovorus for prey-invasion control . They may also underlie the motility and “wolf-pack” predation of Myxobacteria , but the function of the M . xanthus TPR protein homologue remains to be explored . Pioneering work by Mignot/Theodoly has shown that adhesion during gliding motility is mediated by slime deposition [14] , [15] on a solid surface and that gliding directionality is controlled by MglAMx [6] , [7] and other interacting proteins . In nature gliding of M . xanthus may occur on top of prey bacterial biofilms and we hypothesise that the Bd2492-5 TamAB associated system may have a role in producing vesicles , not only for gliding , but to damage prey cells as part of the M . xanthus wolf-pack lytic process . In M . xanthus , chemotactic phospho-transfer signalling , involving Frz proteins , governs the localization of soluble RomRMx , MglAMx and MglBMx proteins to alternately activate or deactivate each cell pole for surface-motility directionality [23] , [24] . In B . bacteriovorus , we detected an interaction between RomRBd and the CdgA GVNEF domain c-di-GMP binding protein ( Figure S3 ) which has been shown to affect prey entry [25] . There is no Frz system in Bdellovibrio [23] but our finding that CdgA binds RomRBd ( Figure S3 ) suggests that this c-di-GMP signalling pathway could contribute to RomRBd localization in the control of the prey-invasive pole . Further work is underway to define any signalling-link to RomRBd and CdgA from our previous observations that c-di-GMP synthases control gliding motility , predation and the switch from predatory to host-independent growth [25] . The data we present here show how the “phenotype space” and function of B . bacteriovorus MglA has diverged from that in M . xanthus . MglABd functions in the control of unipolar prey-invasion: a critical process in the predatory lifecycle of B . bacteriovorus . Our present observations indicate ( Figure 7 ) that MglABd , RomRBd and the interacting TPR-domain protein TPRBd and TamABBd complex act at a single pole in B . bacteriovorus to facilitate prey-invasion via a mechanism that has diverged from that which controls M . xanthus S-motility .
Bacterial strains and plasmids used are listed in Table S1 . Primers used for gene manipulation or PCR amplification are listed in Table S2 . Markerless deletion strains of mglABd and bd2492 ( encoding TPRBd ) were generated using a modified technique of that of the Pineiro lab [49] , and as described previously [25] . Construction of each mutant is described in full in Text S1 . Fluorescent protein tags were generated as described previously [25] by cloning of a whole gene fused to mCherry at the 3′ end . Construction of each tag is described fully in Text S1 . To observe the fluorescence of B . bacteriovorus mCherry-tagged strains during attachment to E . coli prey cells , 1 ml of a B . bacteriovorus predatory culture ( containing 2 . 5×108 pfu ml−1 ) was concentrated 20-fold and added to a microcentrifuge tube containing 30 µl CaHEPES and 40 µl E . coli S17-1 pZMR100 ( from a culture grown for 16 hours at 37°C 200 rpm in YT broth supplemented with Km50 ) diluted to OD600 2 . 0 in CaHEPES , before incubating at 29°C for 5 minutes to allow attachment to occur . Cells were immobilised on a 1% agarose/CaHEPES pad and images were taken on using a Nikon Eclipse E600 epifluorescence microscope with a 100× objective lens and an hcRED filter ( excitation 550 to 600 nm; emission 610 to 665 nm ) with a Hamamatsu Orca ER camera . Images were analysed using Simple PCI software ( version 5 . 3 . 1 Hamamatsu ) . Procedures for attachment , invasion and predation assays of HI Bdellovibrio cells on E . coli prey are described in Text S1 . 3 biological replicates were performed . B . bacteriovorus gliding motility was observed on 1% agarose/CaHEPES by timelapse microscopy as previously described [3] . Briefly , 1 ml of an predatory culture ( containing 2 . 5×108 pfu ml−1 ) was concentrated 10-fold ( HI cultures were not concentrated ) and 8 µl was spotted onto the agarose pad . Measurements of gliding reversals were calculated after cells had been gliding for >1 hr . To analyse percentages of piliated cells , each HI strain was back-diluted and grown to OD600 0 . 1–0 . 5 in PY broth at 29°C 200 rpm . Cells were then stained with 2 . 0% phosphotungstic acid ( PTA ) on carbon formvar copper grids ( Agar Scientific ) and analysed for the presence/absence of a pilus structure , as described previously [26] . Procedures for bacterial two-hybrid and protein co-purification are described in Text S1 .
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Bacterial cell polarity control is important for maintaining asymmetry of polar components such as flagella and pili . Bdellovibrio bacteriovorus is a predatory deltaproteobacterium which attaches to , and invades , other bacteria using Type IV pili ( T4P ) extruded from the specialised , invasive , non-flagellar pole of the cell . It was not known how that invasive pole is specified and regulated . Here we discover that a regulatory protein-hub , including Ras-GTPase-like protein MglA and cyclic-di-GMP receptor-protein CdgA , control prey-invasion . In the deltaproteobacterium , Myxococcus xanthus , MglA , with MglB and RomR , was found by others to regulate switching of T4P in social ‘swarming’ surface motility by swapping the pole at which T4P are found . In contrast , in B . bacteriovorus MglA regulates the process of prey-invasion and RomR , which is required for surface motility regulation in Myxococcus , is essential for growth and viability in Bdellovibrio . During evolution , B . bacteriovorus has lost mglB , possibly as T4P-pole-switching is not required; pili are only required at the invasive pole . A previously unidentified tetratricopeptide repeat ( TPR ) protein interacts with MglA and is essential for prey-invasion . This regulatory protein hub allows prey-invasion , likely integrating cyclic-di-GMP signals , pilus assembly and TamAB secretion in B . bacteriovorus .
|
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2014
|
Ras GTPase-Like Protein MglA, a Controller of Bacterial Social-Motility in Myxobacteria, Has Evolved to Control Bacterial Predation by Bdellovibrio
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Fascioliasis is a neglected zoonosis with major public health implications in humans . Although triclabendazole ( TCBZ ) is the drug of choice , there are records of TCBZ failure worldwide . TCBZ-resistant fascioliasis is treated with alternative approved drugs including nitazoxanide ( NTZ ) , with varying levels of efficacy . Data on NTZ efficacy after TCBZ failure in Egypt is scarce . This study evaluated the efficacy of NTZ in cases of TCBZ failure during an outbreak of fascioliasis in Assiut governorate of Upper Egypt . This prospective study included 67 patients from the outpatient clinic in Manfalout locality of Assiut governorate with clinical manifestations of acute fascioliasis . These included high eosinophilia ( > 6% eosinophils in peripheral blood ) , positive anti-Fasciola antibodies , and hepatic focal lesions ( HFL ) or ascites on abdominal ultrasound or computed tomography . All patients initially received TCBZ at recommended doses . Patients were followed up after 1 month to assess response . According to the responses , patients were categorized as non-responders and responders . The non-responders received a trial of NTZ and were re-assessed for response based on clinical manifestations , eosinophil count , and abdominal ultrasound . Patients not responding to NTZ received additional doses of TCBZ . One month after initial TCBZ treatment , 37 patients responded well to TCBZ , while 30 patients failed to respond with persistence of fever , abdominal pain , high eosinophilia , and HFL . Most non-responders were male ( 56 . 7% ) ; females predominated among TCBZ responders ( 62 . 2% ) . The mean age of the non-responders was relatively lower , at 20 . 57 ± 14 . 47 years ( p = 0 . 004 ) . Following NTZ therapy , HFL disappeared in 9/30 ( 30% ) patients and eosinophil counts normalized in only 2 ( 6 . 7% ) patients , indicating an overall efficacy of 36 . 6% . The remaining cases received additional doses of TCBZ with complete clinical , pathological , and radiological resolution . Nitazoxanide was partially effective in TCBZ failure in acute human fascioliasis in Upper Egypt . Further studies with larger samples are highly encouraged and further research is urgently needed to find new therapeutic alternatives to TCBZ .
Fascioliasis has emerged as a notable zoonotic disease with considerable impact on veterinary and public health . This prompted the World Health Organization ( WHO ) to include human fascioliasis among the important neglected tropical diseases ( NTDs ) [1] . It is a foodborne disease caused by trematodes belonging to the genus Fasciola ( F . hepatica and F . gigantica ) . In the past few decades , the incidence of human fascioliasis has considerably risen in different parts of the world . The rise has been particularly remarkable in South America , Asia , and Africa including Egypt , where the two common species of Fasciola coexist [2] . Recent studies have revealed a large number of cases of fascioliasis ( 2 . 4 to 17 million cases ) worldwide [3] . Fasciolids are parasites of the hepato-biliary ducts , and the disease is mostly confined to the liver . Therefore , the main pathogenic sequelae are hepatic lesions , fibrosis , and chronic inflammation of the biliary passages . The pre-patent period together with the time to onset of signs/symptoms of the disease may range from a few days to 2–3 months or longer . There are 2 main clinical stages in fascioliasis . The acute stage coincides with larval migration and mechanical destruction of the liver tissue . This stage extends till worm maturation in the hepatic tissues , and lasts for 2–4 months . The chronic stage coincides with the persistence of adult Fasciola worms in the bile ducts and may last for months or even years [4] . Eosinophilia is the most common clinico-pathological feature against fascioliasis in both stages . In Egypt , fascioliasis has probably been prevalent for a very long period , since the times of the pharaohs [5 , 6] . High levels of infestation have been widely described in livestock , [7] resulting in considerable economic losses and expenditure for purchase of anthelmintics , liver condemnation , loss of production due to mortality , lower production of meat , milk , and wool , reduced weight gain , and impaired fertility [8] . The mainstay of treatment in fascioliasis affecting animals and humans is triclabendazole ( TCBZ ) , which targets both the immature stages and mature adult worms [9] . Older drugs , such as tetrachloride , tetrachlorethylene , and bithionol , are currently considered to be less effective , unacceptably toxic , or both [10] . Although TCBZ is the only effective treatment for fascioliasis , it is currently registered for human use in only 4 countries [11] . The widespread use of TCBZ in the livestock industry led to the emergence of resistance in fluke populations affecting ruminants in both , developed and developing countries including Ireland , Spain , Australia , Peru , and Argentina [10] . The zoonotic nature of fascioliasis may raise concerns regarding the transmission of resistant strains to humans , particularly in endemic areas such as Peru , Bolivia , and Egypt [12] . In recent years , a few reports have described the occurrence of TCBZ resistance in humans . The first case was reported in a livestock farmer in the Netherlands , followed by 4 , 1 , and 7 cases in Chile , Turkey , and Peru , respectively [13–16] . Unfortunately , despite the prevalence of TCBZ resistance in Egypt , a review of the literature does not reveal any published data . Reliance on monotherapy poses a risk for the treatment of fascioliasis , particularly in the absence of a vaccine for the prevention of the disease [9] . As cases of TCBZ resistance are continuously being documented from livestock , human cases of TCBZ-resistant fascioliasis are most likely to occur . This is a serious challenge for treatment in humans , with considerable public health implications [8] and emphasizes the urgent need for developing new fasciocidal drugs [17] . Several trials were conducted in the search for effective alternative drugs for fascioliasis . Nitazoxanide ( NTZ ) , which is a broad spectrum antiparasitic agent , has been found to be well tolerated by humans , with adverse effects similar to that of placebo [10] . Across different studies , its efficacy has ranged from 40–100% [18] . The aim of the present study was to investigate the efficacy of nitazoxanide as a treatment for fascioliasis in the face of incomplete response to triclabendazole in Upper Egypt .
This prospective study was conducted between August and November 2018 . The study protocol was approved by the Institutional Review Board of the Faculty of Medicine of Assiut University , Egypt . Written informed consent was obtained from all patients prior to participation in this study . A total of 74 patients with diagnosed or suspected fascioliasis were recruited in the study . All these patients were referred to the outpatient clinic in the Tropical Medicine and Gastroenterology Department at the Al-Rajhi Liver University Hospital during an outbreak of fascioliasis in Manfalout locality of Assiut Governorate in Upper Egypt . The included patients had symptoms and signs suggestive of fascioliasis such as fever , abdominal pain , jaundice , and hepatomegaly . The complete blood count ( CBC ) , including eosinophil percentage and absolute eosinophil count was individually assessed using the ADVIA 2120i Hematology System ( Siemens Healthcare Diagnostics Inc . Tarrytown , NY 10591 , USA ) . Stool examination was also performed for all cases for the qualitative diagnosis of fascioliasis using the native lugol and formalin ethyl acetate sedimentation method [19] . Stool samples were also examined for the presence of other co-existing intestinal parasites that could potentially cross-react or overlap with fascioliasis . Liver function tests were also performed . Further investigations included; serological analysis was done by F . hepatica IgG Enzyme-linked immune sorbent assay ( ELISA ) kits ( DiaColon Tech Houston , USA ) for qualitative diagnosis of fascioliasis . The result was read photometrically at 450 nm ( TECAN Sunrise Absorbance Reader ) . ( values greater than 10 . 0 AU/ml were interpreted as seropositive , cut-off value 0 . 25 according to the manufacturer’s instructions ) Indirect hemagglutination assay ( IHA ) using Distomatose Fumouze ( Laboratories Fumouze Diagnostic , Levallois Perret , France ) was also done to compare antibody titers ( a titer ≥ 1/320 was considered to be positive ) . Abdominal ultrasound ( US ) , and abdominal computerized tomography ( CT ) were also done . Endoscopic retrograde cholangiopancreatography ( ERCP ) was performed in cases presenting with obstructive jaundice and a dilated common bile duct ( CBD ) on abdominal US and/or CT . All patients received a double dose of triclabendazole ( Egaten , Novartis Pharma AG ) at a dose of 10 mg/Kg/dose , at 12-hour interval in a joint venture with the WHO . Patients were advised to avoid vegetables that posed a risk for re-infection . The endpoints for treatment response were evaluated on follow up after 1 month . Evaluation was based on 3 parameters , namely , resolution of clinical symptoms and signs , normalization of eosinophil counts , and improvement of hepatic lesions on US . According to the WHO criteria , persistence of symptoms or signs with either eosinophilia ( > 6% eosinophils in peripheral blood ) or hepatic focal lesions , was considered to be a probable indicator of treatment failure with TCBZ [1] . Patients were then divided into 2 groups according to treatment response . The first group included the patients who did not respond to TCBZ and were administered NTZ ( non-responders ) , while the second group included patients who successfully responded to TCBZ ( responders ) . The non-responders received NTZ at a dose of 500 mg orally every 12 hours for 7 days . Patients were clinically assessed for response after 1 month . Resolution of both , eosinophilia in the CBC and/or hepatic focal lesions on US were indicative of response . Patients who failed to respond to NTZ were re-treated with TCBZ at doses similar to the initial dose and were followed up for response . Patients who received any other anthelminthic drugs within 1 month before TCBZ or NTZ therapy including bithionol , praziquantel , albendazole , dihydroemetine , or emetine hydrochloride , and patients who showed hypersensitivity to nitazoxanide were excluded from this study . Data entry and analysis were performed using the IBM SPSS Statistics for Windows , Version 20 . 0 . ( Armonk , NY: IBM Corp ) software package . Data were presented as numbers , percentages , means , and standard deviations . The Chi-square and Fisher’s exact tests were used to compare qualitative variables . The Mann-Whitney test and the Wilcoxon signed rank test were used to compare variables between independent and dependent groups , respectively . In case of non-parametric data , the Wilcoxon signed rank test was used to compare the quantitative variables before and after treatment . A P-value < 0 . 05 was considered statistically significant .
In this prospective study , 74 patients were initially recruited . Among them , 67 patients with symptoms and signs suggestive of acute fascioliasis were included for the NTZ trial; 7 patients were excluded as they presented with obstructive jaundice and a dilated CBD on ultrasound ( suggesting chronic fascioliasis ) . These 7 patients underwent endoscopic sphincterotomy and extraction of the adult worm by ERCP followed by TCBZ therapy . The included patients received initial treatment with a double-dose of TCBZ . The pretreatment demographic , clinical , and laboratory data of the studied patients are shown in Tables 1–3 , respectively . The cohort comprised 31 male and 36 female patients with a mean age of 26 . 27±15 . 3 ( range: 4–60 ) years . The patients presented with one or more of the symptoms and signs of acute infection , which include fever , abdominal pain , hepatomegaly , splenomegaly , and ascites . Laboratory data showed mild anemia ( hemoglobin [Hb]: 11 . 8± 0 . 7 g/dl ) , high eosinophilia ( 41 . 1 ± 15 . 7% ) , high alanine transaminase ( ALT ) and aspartate transaminase ( AST ) levels , and a positive serological titer ( 936 . 1±387 . 2 ) . As depicted in Fig 1 , radiological investigations showed the presence of hepatic focal lesions ( HFL ) in 25 patients ( 37 . 3% ) . Stool examination was positive for Fasciola eggs in 7 of 67 patients ( 10 . 4% ) with absence of other co-existing parasitic infections that could , potentially , construct immunological cross-reactions or clinical symptoms overlapping with fascioliasis . The studied patients were followed up after 1 month to evaluate the response to first line TCBZ . A total of 37 cases ( 55 . 2% ) showed good response to TCBZ ( the responder group ) as evidenced by disappearance of signs and symptoms , normalization of peripheral eosinophil counts , and resolution of HFL . The remaining 30 cases ( 44 . 8% ) ( the non-responder group ) showed persistence of infection , as evidenced by persistence of clinical manifestations , high eosinophilia , and HFL . This group received nitazoxanide and were followed up after 1 month ( Fig 2 ) . The demographic , clinical , and sonographic characteristics of both groups , as summarized in Table 4 , showed that most patients in non-responder group were male ( 56 . 7% ) , while females were predominant in the responder group ( 62 . 2% ) . Also , the mean age in the responder group ( 30 . 89 ± 14 . 57 years ) was significantly higher than that of the non-responder group ( 20 . 57 ± 14 . 47 years ) ( p = 0 . 004 ) . However , the clinical presentation and sonographic evidence of HFL were not significantly different between the groups . As shown in Table 5 , the hematological , biochemical , serological and parasitological parameters of patients at baseline were not considerably different between patients in both groups , except for total leucocyte count , and levels of ALT and AST , that were significantly higher in the non-responder group ( p = 0 . 008 , p = 0 . 026 , and 0 . 047 , respectively ) . Furthermore , the assessment of response to first line TCBZ showed complete resolution of the clinical manifestations in all patients in the responder group; patients in the non-responder group had persistent fever and abdominal pain . The pre-treatment eosinophil counts were not significantly different between the groups ( p = 0 . 081 ) . After treatment , limited improvement in eosinophil counts was observed in the non-responder group , with a reduction from 26 . 72% ± 13 . 21 to 20 . 00% ± 11 . 28 . In the responder group , the counts reduced from 30 . 47% ± 15 . 18 to 3 . 6% ±1 . 7 , showing statistically significant difference between the groups ( p = 0 . 000 ) . After NTZ treatment in the non-responder group , HFL disappeared in 9/30 patients ( 30% ) as opposed to all patients in the TCBZ responder group; this difference was statistically significant ( p = 0 . 015 ) ( Table 6 ) . In addition , eosinophil counts normalized in only 2 ( 6 . 7% ) patients after NTZ therapy . Patients who did not show improvement after NTZ therapy received an additional dose of TCBZ , similar to the initial dose , with complete clinical , laboratory , and radiological resolution . Therefore , based on the improvement of eosinophil counts and HFLs in patients with TCBZ failure , nitazoxanide was effective in 11/30 patients ( 36 . 6% ) .
Owing to its activity against juvenile and adult forms of the parasite , TCBZ is the drug of choice in the treatment of F . hepatica and F . gigantica infections in humans [1] . Mass control programs for human fascioliasis in Egypt , Vietnam , Bolivia , and Peru have used TCBZ , which was donated through an agreement between the WHO and the manufacturer [20] . Several previous studies have documented the clinical efficacy of TCBZ with various treatment regimens in different regions including Egypt [21–23] . The results of these drug trials are indicative of a dose–response relationship . The WHO currently recommends the administration of a single dose of TCBZ at a dose of 10 mg/kg for the treatment of human fascioliasis , and a double dose of 10 mg/kg , 12 hours apart , in severe cases [1] . In a randomized open-labeled study conducted in Egypt , which compared 1- and 2- dose regimens of TCBZ at 10 mg/kg , the 2-dose regimen showed more favorable results [21] . Indeed , TCBZ is the only first-line medication with reports of high efficacy in humans . Therefore , the effective management of resistance to this drug is of utmost importance [9] . Clinical trials on alternatives to TCBZ are limited . This is probably the first study to evaluate the efficacy of NTZ in the management of cases of acute fascioliasis with TCBZ failure in Egypt . In the current study , all cases of acute fascioliasis were defined based on clinical manifestations , high eosinophilia , and radiological signs with positive anti-Fasciola antibodies . However , stool examination was positive in only 7 cases ( 10 . 4% ) with a low egg burden . In the present study we could not rely only on coprological examination for the diagnosis and follow up of cases . This is attributed to many factors , including prepatent or acute infections ( where the patients were symptomatic prior to the appearance of eggs in the stool ) [24] , the inability of adult Fasciola worms to produce eggs ( due to its lack of adaptation to the human host ) , encapsulation of eggs in granulomas or abscesses in the liver , and low egg shedding related to low infection burdens [25] . Coprological examination may also overestimate the response to treatment since the age of the fluke or its anatomic location , which may be associated with increased susceptibility to treatment , may impact the results [26] . In a study previously conducted in Egypt including 23 cases , Fasciola eggs were detected in only 2 cases ( 8 . 6% ) as the patients were diagnosed in the hepatic phase [27] . An immature worm feeds on liver tissue without producing eggs; the only evidences of infection are eosinophilia and HFL , which are observed in early stages of the infection [28] . The detection of anti-Fasciola antibodies by the ELISA test is a reliable and sensitive test for diagnosis of fascioliasis compared with stool examination . The main advantage is that results are positive as early as 2 weeks post infection . However , since serum antibodies may persist for 4–5 months after successful treatment , it is not a reliable test in the evaluation of response during follow up [24] . Eosinophilia as a host defense mechanism is a common feature of fascioliasis and is encountered in 14%- 82% of patients , and may rise and fall during the chronic stage [29] . As described by Marcos et al . , the primary outcome measures for clinical cure after treatment are defined by resolution of the clinical picture and eosinophilia during follow up [30] . Therefore , in the current study , post-treatment follow-up was based mainly on the persistence of clinical manifestations with either high eosinophilia with or without radiological signs . In the present study , as evidenced by the disappearance of signs and symptoms , normalization of peripheral eosinophil counts , and resolution of HFL , 37 patients ( 55 . 2% ) showed good response to TCBZ . The remaining 30 cases ( 44 . 8% ) were suspected to have TCBZ failure and were treated with NTZ . The mean age of the non-responder group was lower than that of the TCBZ responders; this may have had an impact on the treatment response . A double blinded placebo-controlled trial in Peru , which employed NTZ for the treatment of chronic fascioliasis , has shown a low cure rate in children ( 40% ) and a slightly higher efficacy in adults ( 60% ) [9] . In our cohort , most non-responders were male ( 56 . 7% ) ; females were predominant among the responders ( 62 . 2% ) . The gender of the studied patients did not significantly differ between groups . However , previous studies have indicated differences in sensitivity to flukicides depending on the sex of the host animals infected with F . hepatica [31] . Notably , in the current study , patients who did not initially respond to TCBZ in the acute stage , responded to the subsequent trial of TCBZ administered 2 months after the initial dose , in the chronic stage . This relationship between response to TCBZ and the stage of the disease has also been previously mentioned by Marcos et al . [30] , who reported the amelioration of eosinophil counts after a single dose of TCBZ in 10 patients with acute Fasciola infection . However , parasitological cure ( the absence of eggs in the stools ) was not reported during follow up . The difference in TCBZ susceptibility between juvenile and adult parasites has been previously described in an in vitro study with Fasciola hepatica infection [17] . However , this has not been thoroughly described in case series including patients with acute fascioliasis [32 , 33] . According to our results , 30 patients showed clinical evidence of the presence of TCBZ-resistant F . hepatica infection , which is considered a large number . They received a trial with NTZ at a dose of 500 mg twice daily for 7 days , that showed an overall efficacy of 36 . 6% ( 11/30 patients ) , based on the improvement of eosinophil counts and HFLs . NTZ has been widely used in the management of different parasitic infections with reportedly high efficacy and tolerability . The efficacy of NTZ against Fasciola has been studied in rabbits experimentally infected with F . gigantica . NTZ was found to be partially effective ( 47% ) against the juvenile stages of the parasite , but completely effective ( 100% ) against the adult stage [34] . A few clinical trials have been conducted on the efficacy of NTZ in the treatment of human fascioliasis with considerably variable efficacy . In Egypt , an open-label clinical study including 125 Egyptian patients with chronic fascioliasis demonstrated 97% clearance of F . hepatica eggs in the stool on day 30 after treatment with NTZ; the serological and eosinophilic patterns had also improved [35] . A second report from Egypt showed a slightly lower cure rate with NTZ ( 82 . 4% ) [36] . Similar results were observed in a study conducted on schoolchildren in Mexico that documented the efficacy rates of NTZ against chronic fascioliasis to be 94 . 0% and 100% after the first and second treatment courses , respectively [37] . A much lower efficacy rate was observed in a double-blinded placebo-controlled study in northern Peru , where 50 adults and 50 children infected with F . hepatica received a 7-day course of NTZ . Compared to the placebo group , 60% adults and 40% children were cured [10] . These results suggest that NTZ may be a reasonable option at least in the chronic stage of fascioliasis , and is a good alternative to TCBZ . Conversely , some studies have revealed a lack of efficacy of NTZ in 24 cases of liver fluke infection in Cuba [38] and in a patient with apparent TCBZ failure in the Netherlands [13] . Cabada and colleagues have reported that a cohort of 7 patients , infected by ingesting watercress in the Cusco region of Peru , had failed to respond to multiple courses of TCBZ in combination with NTZ [16] . The wide variances in fasciolid susceptibility to NTZ may be attributed to differences in geographical strains of Fasciola in various regions [16] . This indicates the urgent need for further controlled clinical trials to evaluate the efficacy of NTZ in the control of fascioliasis . Although TCBZ resistant fascioliasis has been widely described in livestock , the understanding of the mechanism of resistance to TCBZ remains incomplete , with a knowledge gap in terms of its capacity to spread and strategies for control [39] . It has been suggested that resistant fasciolid strains may have alterations in drug uptake , efflux , and detoxification , including the conversion of TCBZ sulfoxide into the less active forms . However , this has not been verified in large studies using other parasite strains . Poor response to TCBZ may also be attributed to its poor water-solubility and limiting drug concentration in the organs [40–42] . In contrast to veterinary medicine where other treatment options for Fasciola exist , there is no documented strategy for the management of TCBZ treatment failure in humans . To minimize the development of drug resistance , the use of synergistic drug combinations has been suggested [43] . However , this approach carries the risk of building up resistance to multiple drugs [44] . Although the small sample size has limited the scope of this study , to the best of our knowledge , this is the first report of TCBZ failure in humans with acute fascioliasis in Egypt . Further multicenter randomized studies including larger sample sizes are required to evaluate predictors of TCBZ failure . This will help to determine the optimum timing for repeating TCBZ after failure of the initial dose . Also , further research is urgently needed to find new therapeutic alternatives to TCBZ for controlling fascioliasis . In this first report of TCBZ failure in acute human fascioliasis in Upper Egypt , NTZ proved to be partially effective .
|
Fascioliasis is a neglected zoonosis with major public health implications in humans . Triclabendazole ( TCBZ ) is the drug of choice , but alternative approved drugs are necessary in cases of TCBZ failure . Nitazoxanide ( NTZ ) is an alternative used in such cases . However , the efficacy of NTZ in TCBZ-failure cases among patients in Egypt remains unclear . In this study , the efficacy of NTZ was evaluated in cases of TCBZ failure during an outbreak of human fascioliasis in Assiut governorate of Upper Egypt . This study enrolled 67 patients diagnosed with fascioliasis based on clinical , laboratory , and radiological findings . These patients were referred from the outpatient clinic in Manfalout locality of Assiut governorate in Egypt . All patients received TCBZ at recommended doses as initial treatment . Those failing to respond were treated with NTZ at standard doses; following therapy , lesions in the liver and high eosinophil counts were resolved in 30% and 6 . 7% patients , respectively , indicating an overall efficacy of 36 . 6% . Therefore , in this outbreak of human fascioliasis in Upper Egypt , NTZ was found to be partially effective in cases with TCBZ failure .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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2019
|
Evaluation of nitazoxanide treatment following triclabendazole failure in an outbreak of human fascioliasis in Upper Egypt
|
Human cytomegalovirus ( HCMV ) infects about 50% of the US population , is the leading infectious cause of birth defects , and is considered the most important infectious agent in transplant recipients . The virus infects many cell types in vivo and in vitro . While previous studies have identified several cellular proteins that may function at early steps of infection in a cell type dependent manner , the mechanism of virus entry is still poorly understood . Using a computational biology approach , correlating gene expression with virus infectivity in 54 cell lines , we identified THY-1 as a putative host determinant for HCMV infection in these cells . With a series of loss-of-function , gain-of-function and protein-protein interaction analyses , we found that THY-1 mediates HCMV infection at the entry step and is important for infection that occurs at a low m . o . i . THY-1 antibody that bound to the cell surface blocked HCMV during the initial 60 minutes of infection in a dose-dependent manner . Down-regulation of THY-1 with siRNA impaired infectivity occurred during the initial 60 minutes of inoculation . Both THY-1 antibody and siRNA inhibited HCMV-induced activation of the PI3-K/Akt pathway required for entry . Soluble THY-1 protein blocked HCMV infection during , but not after , virus internalization . Expression of exogenous THY-1 enhanced entry in cells expressing low levels of the protein . THY-1 interacted with HCMV gB and gH and may form a complex important for entry . However , since gB and gH have previously been shown to interact , it is uncertain if THY-1 directly binds to both of these proteins . Prior observations that THY-1 ( a ) interacts with αVβ3 integrin and recruits paxillin ( implicated in HCMV entry ) , ( b ) regulates leukocyte extravasation ( critical for HCMV viremia ) , and ( c ) is expressed on many cells targeted for HCMV infection including epithelial and endothelial cells , fibroblast , and CD34+/CD38- stem cells , all support a role for THY-1 as an HCMV entry mediator in a cell type dependent manner . THY-1 may function through a complex setting , that would include viral gB and gH , and other cellular factors , thus links virus entry with signaling in host cells that ultimately leads to virus infection .
Human cytomegalovirus ( HCMV ) infects about 50% of the US population and is the leading infectious cause of birth defects and the most important infectious agent in transplant recipients . In vivo , HCMV predominantly infects epithelial , endothelial , fibroblast , smooth muscle , and mononuclear cells including myeloid progenitors and dendritic cells [1 , 2] . Primary infection typically begins with virus replication in mucosal epithelium followed by leukocyte-associated viremia . Among more than 50 putative glycoproteins encoded by HCMV , gH/gL and gB are conserved in the herpesvirus family , and are required for HCMV entry into cells [3] . gH and gL interact with UL128-UL131 proteins to form a pentameric complex or with gO to form a trimer , that are important for infection of different cell types [4–6] . gB has been reported to bind to gH/gL , and functions as a fusogen [7 , 8] . In addition , gB binds to heparan sulfate proteoglycans [9–11] . HCMV initiates infection by attachment to cell surface heparan sulfate proteoglycans [12 , 13] followed by engagement of cellular receptors or entry mediators . Previous studies have identified several cellular proteins that may function at early steps of infection , including platelet-derived growth factor receptor-α ( PDGFR-α ) [14 , 15] , epidermal growth factor receptor ( EGFR ) [16] , DC-SIGN [17] , αVβ3 and β1 integrins [18 , 19] , and paxillin [20] . HCMV , like many other viruses , utilizes host molecules to facilitate entry in a cell type dependent manner . gB and gH interact with these cellular molecules [14 , 16–18 , 21 , 22]; however , it is not clear whether the interactions are direct or indirect through protein complexes that may include various viral and cellular components . Virus entry is not only limited to virion internalization and cell signaling is an integral part of the entry process [23] . Previous work has shown that HCMV induced activation of the Akt signaling pathway is required at an early step in virus entry [22] . HCMV utilizes PDGFR- α to facilitate entry and simultaneously induces phosphorylation of PDGFR- α when the virus infects fibroblasts , endothelial and epithelial cells . The virus activates EGFR when it infects monocytes , and employs integrins and paxillin at the beginning of infection . The activation of either PDGFR- α or EGFR in turn leads to activation of downstream cellular phosphatidylinositol 3-kinase ( PI3K ) , Src kinase and focal adhesion kinase ( FAK ) signaling pathways , and induces cytoskeletal rearrangements to create an intracellular environment to facilitate infection [14 , 20] . HCMV infects a broad spectrum of human cells ranging from epithelial and endothelial cells to hepatocytes and neuronal cells . This may reflect the capability of the virus to utilize multiple cellular molecules to gain entry depending on the type of cell . The observation that cells expressing neither PDGFR- α nor EGFR are still permissive for HCMV infection implies that the virus exploits additional host factors at an early step of infection [3 , 24] . In an attempt to identify other cellular proteins important for infection , we utilized 54 human cell lines from the NCI-60 panel of diverse tissue origins whose gene expression profiles have been extensively analyzed across multiple platforms [25–27] . A previous study showed that transcript-protein correlation in these cell lines is highly statistically significant [28] . In conjunction of bioinformatics analysis , this panel of cell lines has been a valuable screening tool for identifying host factors important for viral infection [29–33] . We investigated the susceptibility of these cell lines for HCMV and correlated infectivity with gene expression profiles for each of the cell lines using bioinformatics analysis . This approach allowed us to evaluate the contribution of individual host molecules to infection in the context of overall gene expression in the cells . We focused on membrane associated proteins since they are likely to be involved in the very early steps of virus infection . Using a series of loss-of-function , gain-of-function and ligand interaction analysis , and additional non-transformed cells , the biological function of one candidate protein was further validated . Here , we report that THY-1 has an important role in the early stages of HCMV infection in a diverse group of cell lines .
Prior studies to identify entry mediators for HCMV have been limited by the types of viruses and cell lines used . High passage strains of HCMV , deleted for the UL128-131 region , which are restricted to efficient growth in fibroblasts , have been predominately used to identify HCMV entry mediators [14 , 16 , 22] . In addition , previous studies defining HCMV entry used relatively few cell lines , and most studies focused on fibroblasts . Since HCMV utilizes different host molecules to infect specific types of target cells ( mainly endothelial , epithelial , and mononuclear cells in vivo ) , these more traditional approaches with one or only a few cell lines have limitations . To address the issue , we utilized a panel of 54 adherent cell lines of diverse origins from the NCI-60 panel whose molecular profiles have been extensively characterized at the DNA , RNA and protein levels , and integrated with each other by integromic analyses [26 , 34] ( S1 Table ) . We infected the cells with both fibroblast ( Towne-GFP ) ( a gift from Dr . H . Zhu , UMDNJ-New Jersey Medical School ) and epithelial/endothelial tropic ( BADrUl131-GFP and TB40E-GFP ) HCMV which express GFP ( gift from Dr . T . Shenk , Princeton University ) [4 , 35–37] . Two or three days post infection , susceptibility to HCMV was determined based on GFP positivity of the cells . For bioinformatics analyses , infection of each cell line with each virus was performed in at least three independent experiments and each time in triplicate wells . Infectivity was then determined by FACS analysis of GFP positive cells and the mean infectivity score was calculated by normalization using epithelial ( ARPE-19 ) cells for epithelial/endothelial tropic virus and fibroblasts ( MRC-5 cells ) for fibroblast tropic virus ( S2 Table ) . Correlations between HCMV infectivity and expression of each cellular gene were calculated using the COMPARE algorithm [38] and further detailed using MAPP software [30] . COMPARE utilizes gene expression profiling as determined by microarray analysis across multiple microarray platforms to identify genes that correlate ( based on the Pearson Correlation Coefficient ) with the experimentally determined HCMV infection profile [30 , 38] . The mean infectivity score and the expression level of each gene were computed and the Pearson Correlation Coefficient was determined . The highest rated membrane associated protein whose expression correlated positively with virus susceptibility was PDGFR-α , which has been shown to function in HCMV entry [14 , 15] . Transfection of MRC-5 cells with PDGFR-α specific siRNAs reduced HCMV infection ( S1A Fig ) . THY-1 was implicated as the next highest scoring membrane associated protein whose expression correlated positively with HCMV infectivity . Infectivity of both epithelial/endothelial and fibroblast tropic HCMV strains showed a positive correlation with THY-1 expression at a level similar to or higher than that of PDGFR-α ( Fig 1 ) . The correlation of THY-1 expression was statistically significant for both Towne-GFP ( P = 0 . 0002 , Pearson Correlation Coefficient 0 . 46 ) and TB40E-GFP HCMV ( P = 0 . 0004 , Pearson Correlation Coefficient 0 . 44 ) . Likewise , expression of PDGFR-α correlated with infection for Towne-GFP ( p<0 . 00001 , Pearson Correlation Coefficient 0 . 53 ) and TB40E-GFP HCMV ( p = 0 . 016 , Pearson Correlation Coefficient 0 . 29 ) . Similar correlations for THY-1 and PDGFR-α expression with infectivity were also observed for epithelial/endothelial tropic strain BADrUl131-GFP HCMV . To determine whether THY-1 is important for HCMV infection , we performed a series of loss-of-function experiments . First , we determined if soluble THY-1 ( a . a . 20–130 ) can block HCMV infection . Wild-type THY-1 is initially synthesized as a 161 amino acid peptide . Upon maturation , the signal peptide ( a . a . 1-19 ) is cleaved and the C-terminal a . a . 132–162 is replaced with a GPI anchor . A soluble form of THY-1 ( a . a . 20–130 ) exists in vivo and the recombinant form of THY-1 retains its biological function in binding integrins [39 , 40] . HCMV or control virus ( HSV-2-GFP or adenovirus-GFP ) was premixed with soluble THY-1-His protein or a control His protein ( soluble varicella-zoster virus gE-His ) at room temperature for 10 min , added to HS-578T cells for virus binding on ice for 60 min . Internalization was initiated by raising the temperature to 37°C for 60 min , and then non-absorbed virus was inactivated at low pH , and infectivity was quantified using GFP 3 days later . Compared with the control protein at each dose , soluble THY-1 protein reduced HCMV infectivity in a dose-dependent manner ( Figs 2A and S3 ) in adenocarcinoma cells , and inhibited infection in MRC-5 fibroblasts ( Figs 2B and S4 top ) . In contrast , it did not reduce HSV-2 infectivity ( Figs 2C and S4 bottom ) or adenovirus infectivity ( Figs 2D and S4 Bottom ) . Soluble THY-1 protein was required during the initial viral entry step to block HCMV infectivity , since addition of the protein after virus binding and internalization did not inhibit infectivity ( Fig 2A , last bar ) . In natural hosts HCMV infection likely occurs at a relatively low m . o . i . A review of studies of virus shedding from saliva of infants , children , and adults , often the source of transmitted virus , showed that the titer of virus in saliva ranged from 103 to 2 x 104 pfu/ml [41] . Therefore we infected the cells with titers ranging from 4 x 104 ( HS-578T ) to 1 x 105 pfu/ml ( MRC-5 ) , which corresponds to a relatively low m . o . i . ( 0 . 05 to 1 ) to try to replicate what may occur during natural infection . Furthermore , we used acid inactivation to limit the infection within the first 60 min to focus on the initial stages of virus infection and the most efficient pathways for viral entry ( Fig 2 ) . During the first 60 minutes after infection ( m . o . i . 0 . 05–1 with acid inactivation ) , about 2–10% of the cells were infected , which corresponds to about 20–35% of the cells if the same infection is allowed to continue for a prolonged time , i . e . without acid inactivation ( S5 Fig ) . Soluble THY-1 protein blocked over 90% of the infection that occurred within the first 60 min ( m . o . i . 0 . 05–1 ) at a dose of 0 . 5 μg/ml ( Fig 2A ) . In contrast , with a high m . o . i ( 4 , based on titration in MRC-5 cells ) 10-fold more soluble protein was required to block >90% of the infectivity ( during entry over 60 min with acid inactivation ) , and soluble THY-1 blocked infection less efficiently for the virus that enters with slower kinetics ( 75% reduction in infectivity without acid inactivation , S6 Fig ) . Next , we examined whether specific antibody 5E10 binds to cell surface THY-1 protein . NCI-60 cell lines SNB-19 ( glioblastoma ) and HS-578T ( adenocarcinoma ) , as well as primary human diploid ( MRC-5 ) fibroblasts all express THY-1 mRNA [34] ( Fig 3A ) , and THY-1 protein was detected on the surface of these cells ( Figs 3B and S1B ) . Both HS-578T and SNB-19 cells support productive HCMV infection and produce progeny virus ( S2 Fig ) , although HCMV cell-to-cell spread in SNB-19 cells is limited , especially with TB40E-GFP HCMV . To ascertain whether THY-1 specific antibody blocks HCMV infection , THY-1 or isotype control antibody was allowed to bind to the surface of HS-578T cells on ice for 60 min , the antibody mixture was removed from the cells , and HCMV was added on ice for 60 min to synchronize virus binding . To focus on the early steps of virus entry , the temperature was raised to 37°C for 60 min to allow virus entry , followed by low pH treatment to inactivate any virions that still remained on the cell surface or in the medium . After washing , the cells were then cultured for 6 hr before RNA extraction to quantify combined HCMV UL123 ( encodes IE1 ) and UL55 ( encodes gB ) RNA expression by RT-qPCR [42] or for 3 days to measure infectivity by FACS for GFP . Although UL55 is a late gene , UL55 transcripts start to appear at 4 hrs post-infection , and expression is not strictly dependent on new viral DNA synthesis [43 , 44] . In 4 independent experiments , quantitative RT-PCR showed that THY-1 specific antibody blocked expression of HCMV UL123 and UL55 genes , compared with isotype control antibody ( Fig 3C , P = 0 . 0002 for 4 independent experiments ) . Similar blocking result with THY-1 antibody was also seen when infectivity was assayed at 3 days post-infection by virus-encoded GFP ( Fig 3D , P = 0 . 0004 , 3 independent experiments ) . THY-1 specific antibody , but not isotype control , blocked HCMV infectivity in a dose-dependent manner ( Figs 3D and S7 ) . THY-1 antibody also blocked HCMV infection in primary MRC-5 cells ( Fig 3E ) . To confirm the loss-of-function findings observed with THY-1 specific antibody , we used THY-1 specific siRNAs to knockdown THY-1 expression in permissive cells , and analyzed the effect on HCMV infection . Nucleofection of cells with THY-1 specific siRNAs reduced THY-1 expression by over 90% compared with control siRNAs at the time of infection both at the mRNA ( Fig 4A ) and protein level ( S10A Fig and see section on THY-1 and Akt activation below ) . HCMV infectivity was reduced by 30–50% at 3 days post-infection based on FACS analysis for GFP ( Fig 4B ) ( P value <0 . 0001 , 12 independent experiments ) . However , THY-1 siRNAs knocked down cell surface THY-1 protein ( S10B Fig ) less effectively than total THY-1 protein ( S10A Fig ) . This might be due to increased stability of surface THY-1 protein when it is anchored into lipid rafts , and could contribute to the lower level of inhibition of HCMV infection with THY-1 siRNAs than with antibody or soluble protein ( see above ) . The impairment of HCMV infectivity following knockdown of THY-1 was observed in glioblastoma ( SNB-19 ) , adenocarcinoma ( HS-578T ) and MRC-5 cells infected with either epithelial/endothelial or fibroblast tropic HCMV . Since the infection protocol allowed only 60 min for virus entry before virus was inactivated by low pH , the reduction of infectivity occurred during initiation of HCMV infection . In contrast with SNB-19 and HS-578T cells which support HCMV infection and express THY-1 on their surface ( used above in loss-of-function experiments ) , SF-539 ( gliosarcoma ) cells express negligible levels of THY-1 mRNA or THY-1 protein on the cell surface ( Figs 3A and S1B ) , and are refractory to HCMV Towne infection . Molecular profiling of NCI-60 cells showed that SF-539 cells express comparable levels of PDGFR-α , EGFR , αVβ3 and β1 integrins as SNB-19 and HS-578T cells . Therefore , we used SF-539 cells for gain-of-function studies . pCMV-THY-1 or empty vector was transfected into SF-539 cells by nucleofection and 48 hr later the cells were incubated with Towne-GFP for 1 hr on ice , then at 37°C for 1 hr , followed by low pH to inactivate virus that had not entered the cells . RNA was extracted from the cells at the time of infection to monitor THY-1 expression and at 6 hrs post-infection to detect HCMV UL123 and UL55 expression . Quantitative RT-PCR showed that SF-539 cells transfected with control vector expressed very low levels of THY-1 mRNA , while cells transfected with pCMV-THY-1 expressed high levels of THY-1 mRNA ( Fig 4C ) . Expression of THY-1 from the pCMV-THY-1 plasmid enhanced HCMV infectivity of the cells ( Fig 4D , P <0 . 0001 , 7 independent experiments ) . Since the infection was restricted to the initial 60 min of viral inoculation , we conclude that exogenous expression of THY-1 enhances the initial stage of HCMV infection of cells . gB and gH/gL are essential for HCMV infection [3] . HCMV gB has a furin cleavage site that results in covalently bound N-terminal and C terminal fragments of about 55 kD each . gB has been reported to bind to gH and may form glycoprotein complexes with other components , including gO or UL128-131 [9 , 10 , 45] . We postulated that since THY-1 is important for HCMV infection , it might interact with one or more of these glycoproteins , either directly or as part of a complex . We incubatedanti-THY-1 or isotype control antibody with HCMV-infected and uninfected cell lysates , and separated the immune complexes by gel electrophoresis . Several protein bands were found in lysates from HCMV Towne infected MRC-5 cells immunoprecipitated with antibody to THY-1 , but not in lysates immunoprecipitated with isotype control antibody or in uninfected cells . Mass spectrometry of these unique bands identified gB and gH with a Mascot score of 1141 and 281 ( a score of 45 represents the significance threshold for individual peptide matches P <0 . 05 ) , with multiple peptide sequence coverage for both glycoproteins . In contrast , gM and gO were each identified by only a single peptide ( S3 Table ) . Since co-immunoprecipitation followed by Western blotting was inefficient for detecting proteins that interact with gB in infected cells , we constructed protein columns by binding THY-1-His protein , or control VZV gE-His protein to Talon beads , added lysates from HCMV-infected cells to the columns , eluted proteins bound to the columns , and immunoblotted the proteins with antibody to HCMV ICP8 or gB . Two different cell lysis buffers were used , PBS with 0 . 1% NP-40 [30] and 25 mM Tris , 15 mM NaCl and 0 . 1% NP-40 [46] . HCMV gB was detected in the infected cell lysate and in eluates from THY-1 protein columns , but not the control VZV gE protein column ( Fig 5A ) . Interestingly , THY-1 complexed with full length gB ( 160 kD ) , as well as its proteolytic cleavage products of 55 kD [47] . Purified THY-1 protein pulled down more 55 kD gB than full length gB . A previous study has shown the cleaved form of gB was more abundant than full length gB in infected cell lysate and in purified virions [48] . In contrast , the 135 kD HCMV ICP8 was detected in infected cell lysate , but not in eluates from THY-1 or control VZV gE protein columns ( Fig 5B ) . Similarly , gH was co-precipitated from infected cell lysate by purified THY-1 protein ( Fig 5C ) . These results suggest that THY-1 may form a complex with HCMV gB and gH in infected cells . Since gB and gH have been shown to form a complex , it is possible that THY-1 interacts directly with gB and that the interaction of THY-1 with gH is indirect and solely due to gH interacting with gB . Alternatively , THY-1 has been shown to bind to integrins , and gB and gH from several herpesviruses interact with integrins; thus , the interaction between THY-1 and gB and gH may be indirect and mediated through integrins . To further study the possibility of an interaction between THY-1 and the HCMV gB and gH glycoproteins [10] , MRC-5 cells were infected with HCMV AD169 ( which does not express GFP ) and live cell staining was performed with goat anti-THY-1 antibody and mouse monoclonal anti-gB , anti-gH , or isotype control antibody followed by anti-goat and anti-mouse fluorescent antibodies and confocal microscopy . THY-1 colocalized with gB ( Pearson Correlation Coefficient 0 . 88 where 1 . 0 is 100% colocalization [49] ( Fig 6A , row 1 ) and gH ( Pearson Correlation Coefficient 0 . 84 , Fig 6A row 2 ) . Incubation of MRC-5 cells with secondary antibody alone did not give background staining , goat anti-THY-1 did not cross react with secondary anti-mouse fluorescent antibody , and mouse anti-glycoprotein antibodies did not cross react with secondary anti-goat fluorescent antibody ( Fig 6A , row 3 ) . In HCMV- infected adenocarcinoma HS-578T cells , gB also colocalized with THY-1 ( Figs 6B and S11 ) . As a control , gB did not colocalize with cell surface protein ZO-1 ( Fig 6B ) . Interestingly , confocal microscopy with 3-D reconstruction of the cell surface showed that gB appeared to bind predominantly on top of THY-1 molecules on the plasma membrane ( Fig 7 ) . Although gB is conserved among human herpesviruses , HCMV gB ( AD169 strain ) and VZV gB ( Dumas strain ) share only 20% amino acid identity and 31% similarity . As an additional control , we co-transfected THY-1 with either HCMV gB or VZV gB , and performed confocal microscopy . HCMV gB colocalized with THY-1 at levels similar to that in infected cells , but VZV gB did not colocalize with THY-1 ( S11 Fig ) . These results suggest that THY-1 may form a complex with HCMV gB and gH in infected cells . Since glycoproteins gB and gH have been shown to form a complex , it is possibly that THY-1 interacts directly with gB and that the interaction of THY-1 with gH is indirect and solely due to gH interacting with gB . Alternatively , THY-1 has been shown to bind to integrins , and gB and gH from several herpesviruses interact with integrins , thus , the interaction between THY-1 and gB and gH may be indirect and mediated through integrins , Previous studies have shown THY-1 modulates the phosphatidylinositol 3-kinase ( PI3K ) signaling pathway [50] . Activation of the PI3K pathway is required for HCMV infection at the entry step [14 , 20 , 22] . Therefore , we analyzed the effect of THY-1 on the ability of HCMV to phosphorylate Akt , a downstream molecule in the PI3K pathway . Knock-down of THY-1 expression with specific siRNAs blocked HCMV-induced phosphorylation of Akt at 15 min post-infection and reduced HCMV infectivity within the first 60 min of infection ( Figs 8A and 8B and S12 ) compared with control siRNAs ( p = 0 . 01 , 6 independent experiments ) . These data suggest that HCMV engagement of THY-1 during the initial 15 min of infection contributes to HCMV signaling through the PI3K/Akt pathway . We then tested whether THY-1 antibody could block HCMV mediated Akt activation during entry . Binding of THY-1 antibody , but not isotype control antibody , to the cell surface inhibited Akt activation within 45 min after the incubation temperature was raised to 37°C to allow for HCMV internalization ( S9 Fig ) .
In spite of progress in the field of virus entry , our understanding of the interaction of viral and cellular proteins required for initiation of HCMV infection is still unclear . This may reflect the large number of HCMV glycoproteins and the ability of the virus to infect a wide variety of cell types . Previous studies of early events in HCMV infection were largely limited to a few cell lines . This imposed limitations for identifying host molecules that are important for infection , since virus entry is cell-type dependent . To address this issue , we studied HCMV infectivity in 54 cell lines with diverse genetic backgrounds . The extensive molecular profiling of each of these cell lines along with bioinformatics analysis allowed us to take an unbiased approach to study virus infection instead of screening for single molecules in isolation . The identification of THY-1 as a putative host determinant for HCMV infection in a large set of 54 cell lines , and the subsequent validation by a series of loss-of-function , gain-of-function , and glycoprotein interaction experiments in both malignant and primary cells strongly suggests that THY-1 has an important role in the initial stage of virus infection . THY-1 is expressed in many cell types both in vivo and in vitro , including epithelial and endothelial cells , smooth muscle cells , placenta , neurons , hepatocytes , and hematopoietic stem cells , the same cells that are susceptible to HCMV infection . Therefore , THY-1 likely facilitates HCMV entry in many cell types . On the other hand , THY-1 may not be required for infection of all cell types; instead , it functions in a cell type dependent manner . Other herpesviruses use different receptors to enter different cell types . HSV uses nectin-1 to enter neurons and HVEM to enter lymphocytes [51] . Some cell lines that express very low levels of THY-1 are still susceptible to HCMV infection , particularly at high m . o . i . or after prolonged virus inoculation . It is likely that HCMV enters cells through different pathways , either by direct fusion at the cell surface or by various endocytic pathways , especially when large amounts of virus are used in vitro . This is similar to the case of Lassa virus infection , in which the impairment of virus glycoprotein mediated entry imposed by deletion of host receptor glycosylated α-dystroglycan can be overcome by using high titer virus ( m . o . i > 0 . 5 ) , resulting in virus entry through an alternate pathway involving heparin sulfate , lysosome-resident protein , and pH-dependent endocytosis [52] . Previous studies have shown for other viruses entry dynamics are highly dependent on the m . o . i . Virus internalization occurs much more rapidly when a high m . o . i . ( m . o . i 10 ) is used , compared to a low m . o . i of 0 . 01–1 [53 , 54] . For HCMV , infection at low m . o . i . ( ≤ 0 . 01 ) resulted in different profiles of virus replication and signaling as compared with infection at higher m . o . i ( 0 . 1–3 . 0 ) [55–57] . In the current study , we used a combination of low m . o . i . ( between 0 . 05–1 ) and short time for infection ( 60 minutes followed by inactivation of virus remaining on the cell surface ) to focus on the most efficient entry pathway ( s ) . As shown in S5 and S6 Figs , only a fraction of the input virus entered cells within 1 to 2 hours at the low m . o . i . Nonetheless , a low m . o . i . is likely more representative of the virus to cell ratio present during natural infection . Since THY-1 is a major cargo protein of clatherin-independent endocytotic carriers [58] , it is possible that THY-1 leads virions into the cells by macropinocytosis . Many viruses down-regulate and internalize their receptors from the cell surface through endocytic pathways [59] . Previous studies have shown that THY-1 is down-regulated in fibroblasts [60 , 61] , as well as in mesenchymal stem cells [62] upon HCMV infection in a manner similar to that of PDGFR-α [63] . THY-1 is known to interact with cell proteins that facilitate HCMV entry . THY-1 engages αVβ3 integrin receptors and recruits paxillin [64] , and triggers protein kinase dependent signaling pathways such as PI3K and Src [50 , 65 , 66] . THY-1 was important for activation of Akt in virus-infected cells and activation of PI3K –Src pathway has been shown to be required for HCMV entry [14 , 20 , 22] . Our findings that THY-1 facilitates an early step of HCMV infection , and that down-regulation of THY-1 by siRNA or blocking THY-1 with antibody inhibits HCMV- induced PI3K-Akt activation within the initial 15–45 min of infection , suggests a pivotal role for THY-1 in the coupling of HCMV entry with host signaling , and supports observations that growth factor receptors ( PDGFR- α and EGFR ) engage integrin/paxilin pathways during HCMV infection [14 , 16 , 22 , 67] . THY-1 protein is localized in lipid rafts through its GPI anchor . Ligand-mediated clustering of THY-1 in cholesterol-rich microdomains is needed to trigger Src-dependent downstream signaling [68 , 69] . We hypothesize that THY-1 clustering might be induced by interactions between THY-1 and HCMV gB and/or gH , two molecules that have been reported to contribute to signaling during virus entry [22 , 70] . This is similar to observations that binding of Group B coxackievirus to its receptor decay-accelerating factor ( DAF ) , a GPI anchoring protein , induces DAF clustering to initiate signaling by Src family kinases [71] . We found that THY-1 interacts with both full length and 55 kD cleavage forms of gB , as well as with gH . Both full length and cleaved forms of gB are present on infected cells and virions [72] . Furthermore , THY-1 colocalizes with gB and gH in HCMV-infected cells . However , it is not clear whether THY-1 interacts with gB or gH directly or indirectly . Several studies have shown that exogenous HCMV gB and gH interact [10 , 73] . gH/gL have been postulated to function as receptor binding proteins , while gB may act as a fusogen; however , gB also binds to ligands and signaling molecules [8 , 74] . HCMV gB has been identified as a ligand for putative entry mediators , including integrins , PDGFR-α , and EGFR [14 , 16 , 22] . Like THY-1 , both EGFR and PDGFR-α have been shown to form a complex with αVβ3 integrin [75 , 76] , and are activated when they oligomerize after binding with ligands [69 , 77 , 78] . Therefore , THY-1 may be part of a multimolecular complex mportant for the initial phase of CMV infection and signaling ( that includes PDGFR- α , EGFR , integrins , paxillin , and viral glycoproteins ) . However , it is uncertain how THY-1 fits into this complex and the exact form and timing of interaction ( s ) between THY-1 , gB , and gH are unclear . Previous studies of HSV showed recruitment of other viral and host molecules to a complex after gD binds to its receptor . Since THY-1 interacts with several other cellular proteins , including integrins and is important in multiple signaling pathways , it is likely that THY-1 facilitates HCMV infection at an early stage as an entry mediator , rather than a receptor for a viral glycoprotein ( s ) . HCMV disseminates in leukocytes throughout the body after infecting mucosal epithelial cells , and induces production of inflammatory cytokines and increases permeability of the endothelium . This process is dependent on activation of the PI3K signaling pathway , which promotes extravasation of leukocytes into tissues [67 , 79 , 80] . Binding of THY-1 induces vascular permeability and regulates the extravasation of leukocytes during inflammation [81] . THY-1 is expressed in many types of cells that can be productively infected by HCMV as well as CD34+/CD38- stem cells , a putative cellular reservoir for latent infection [62 , 82] . Therefore , THY-1 may have a central role in mediating HCMV infectivity , coupling integrin/paxillin and leukocyte extravasation signaling , and linking the process of viral entry with signaling modulation of host cells that leads to the virus replication .
Human diploid fibroblast ( MRC-5 ) , retinal pigmented epithelial ( ARPE-19 ) cells , and CV1/ EBNA-1 cells were acquired from the American Type Culture Collection ( ATCC , Manassas , VA ) , and maintained in Minimum Essential Medium , F12 medium , or Dulbecco’s Modified Eagle Medium , respectively , with 10% FBS . HCMV antibodies used were monoclonal anti-gB ( Virusys , Taneytown , MD ) , monoclonal anti-gH ( US Biological , Swampscott , MA ) , rabbit anti-gH antibodies ( from Teresa Compton , University of Wisconsin and . David Johnson , Oregon Health & Science University ) , and mouse anti-ICP 8 antibody ( Novus , Littleton , CO ) . Monoclonal antibodies used to detect THY-1 or isotype control antibody were purchased from Novus ( Littleton , CO ) , Millipore ( Billerica , MA ) and BioLegend ( San Diego , CA ) . Polyclonal goat anti-THY-1 or rabbit anti-THY-1 were obtained from Novus and GeneTex ( Irvine , CA ) . Monoclonal antibodies for total and phosphorylated Akt were purchased from Cell Signaling Technology ( Boston , MA ) . Expression plasmids encoding HCMV gB and gH were kindly provided by Teresa Compton [21] . pCMV-THY-1 was purchased from Open Biosystems ( Huntsville , AL ) , and pCR2 . 1-GAPDH was a gift from Dr . Helene Rosenberg ( NIAID , NIH ) . Plasmid expressing VZV full length gB was constructed by PCR amplification of gB ORF from the Oka strain of VZV , cloned into pcDNA3 . 1 vector with a C-terminal V5 epitope tag , and verified by sequencing . BAC DNAs for epithelial/endothelial tropic HCMV strains BADrUl131-GFP and TB40E-GFP ( kindly provided by Thomas Shenk , Princeton University , NJ; TB40E-GFP is also referred to as GS1783TB40-GFP ) [37] were electroporated into ARPE-19 cells and the resulting viruses were propagated in ARPE-19 cells . Towne-GFP and AD169 , both fibroblast topic HCMV strains , were propagated in MRC-5 cells . Cell culture supernatants from virus-infected cells were centrifuged at 2000 x g for 30 min at 4°C , and the clarified supernatants were used as virus stocks or further partially purified by centrifugation through a 20% sucrose or sorbitol cushion with a JA25 rotor at 35000 x g at 4°C for 60 min and resuspended in growth medium [83 , 84] . GFP expressing adenovirus ( adenovirus-GFP ) and herpes simplex virus 2 ( HSV-2-GFP ) were used as controls [85 , 86] . 54 cell lines from the NCI-Frederick Tumor Cell Line Repository were purchased through Charles River Laboratories ( Frederick , Maryland ) and grown in RPMI-1640 medium with 10% FBS [34] . Cells with less than 20 passages after receipt were used in the study . Screening was performed based on previously published methods that have been used to identify other proteins important for the early stage of virus infection [29 , 30 , 32 , 87] . Briefly , cells were infected with GFP-expressing HCMV for 2–3 days , and susceptibility to HCMV was determined by FACS analysis based on GFP positivity , and normalized against infectivity for MRC-5 ( for fibroblast tropic virus ) or ARPE-19 ( for epithelial and endothelial tropic viruses ) cells . Bioinformatic analyses to determine correlations between HCMV infectivity and expression of each cellular gene were performed using the COMPARE algorithm and further detailed using MAPP software as described previously [30 , 38] . HCMV was added to cells on ice for 60 min for virus binding . The temperature was then shifted to 37°C for 60 min to allow virus entry . The cells were then treated with low pH citrate buffer ( sodium citrate 40 mM , potassium chloride 10 mM , sodium chloride 135 mM , pH 3 . 2 ) at room temperature for 3 min to inactivate any virus that had not yet internalized , washed twice , and cultured for either 6 hrs to detect viral encoded RNAs or 3 days to quantify GFP positivity in cells infected with HCMV expressing GFP . A low m . o . i . ( 0 . 05–1 ) was used for most virus entry experiments since this is likely what occurs during natural infection; a high m . o . i ( with a high percentage of cells infected ) has been shown to result in different kinetics of entry than a low m . o . i . [53 , 55 , 88] . GFP positivity was determined by FACS analysis using a BD FACSCalibur and data was analyzed with FlowJo software ( Tree Star , Ashland , OR ) . MRC-5 cells infected with HCMV at an m . o . i . of 5 for 3 days or uninfected control cells were lysed in buffer ( 25 mM Tris , 15 mM NaCl , 0 . 1% NP40 with or without 5mM EDTA ) as described previously [46] . Immunoprecipitation with anti-THY-1 antibody and protein A-Sepharose ( Sigma-Aldrich , St . Louis , MO ) was carried out at 4°C overnight . After extensive washing , proteins were separated in SDS-PAGE gels under reducing conditions and visualized by Coomassie Blue or silver staining . Specific bands were excised and subjected to mass spectrometry for protein identification ( Research Technologies Branch , NIAID , NIH ) . Soluble THY-1-His protein , or VZV gE-His control protein , was bound to Ni-NTA or Talon columns at 4°C for 2 hr followed by extensive washing with PBS . HCMV-infected or uninfected cell lysates were centrifuged at 2000 x g at 4°C for 30 min , and the supernatant was added to columns and incubated at 4°C overnight with rotation . Columns were washed with PBS using a peristaltic pump , and eluted with 250mM imidazole . Samples were concentrated by centrifugation at 1600 x g in an Amicon Ultra centrifugal filter unit ( 3000 MWCO ) , separated in SDS-PAGE gels , transferred to nitrocellulose membrane , and immunoblotted with antibodies . Total RNA was extracted using an RNeasy Mini Kit ( Qiagen , Valencia , CA ) following the manufacturer’s instructions . To eliminate DNA contamination , RNA was treated with DNase I ( Roche Applied Science , Indianapolis , IN ) and purified a second time with an RNeasy Mini Kit . Quantitative real-time RT-PCR was performed using One-step RT-PCR Master mix reagent ( Applied Biosystems , Carlsbad , CA ) with a 7500 Real Time PCR machine . Primers and probes for detection of HCMV immediate-early gene UL123 and late gene UL55 were described previously ( Boeckh et al . , 2004 ) . Primers ( 5’- GTTAGGCTGGTCACCTTCTG , 5’- GAGATCCCAGAACCATGAACC ) and probe ( 5’- AGACTGTTAGCAGGAGAGCGATGC ) for THY-1 were located in exon 1 . Primers and probe for GAPDH were purchased from Applied Biosystems ( Carlsbad , CA ) . Serial dilutions of HCMV Bac DNA , THY-1 plasmid , or human GAPDH plasmid were used to generate standard curves , and copy numbers of THY-1 and HCMV RNAs were normalized to copy numbers of human GAPDH amplified from the same wells . DNA contamination was monitored by performing PCR amplification without reverse transcriptase . THY-1 specific siRNA SmartPools ( M-015337-00 ) and non-specific control pools ( Duplex-13 ) , THY-1 single siRNA oligos with targeting sequences CAACUUCACCAGCAAAUAC ( THY-1-02 ) and GGACUGCCGCCAUGAGAAU ( THY-1-04 ) , and non-targeting single oligo #4 were obtained from Dharmacon ( Lafayette , CO ) . Cells were transfected with siRNAs ( 125 pmol per 2 x 106 cells ) using nucleofection ( Amaxa , Gaithersburg , MD ) for 48 hr before infection or harvesting . DNA corresponding to THY-1 amino acids 20–130 with a C-terminal ( His ) 6 tag was amplified by PCR from plasmid pCMV-THY-1 ( using primers 5’-CAGAAGGTGACCAGCC and 5’-GCTCAGAGACAAACTGGTCAAG , and cloned into pDC409 [89] . The THY-1 insert in the resulting plasmid , pDC409-THY-1 ( 20–130 ) -His , was completely sequenced . THY-1-His soluble protein was expressed in CV1/EBNA 1 cells and purified with a Ni-NTA column ( Invitrogen , Grand Island , NY ) or Talon resin ( Clontech , Mountain View , CA ) , eluted with 250 mM imidazole , dialyzed against PBS at 4°C overnight , and concentrated with an Amicon Ultra centrifugal filter unit ( 3000 MWCO ) ( Millipore , Billerica , MA ) . Filtrates derived from this filter unit with the same buffer composition , but lacking THY-1 protein , were used as a negative control for experiments . Soluble varicella-zoster virus gE with a C-terminal ( His ) 6 tag , gE-His [46] , was used as an additional control in soluble THY-1-His protein experiments . Cells were fixed in methanol/acetone ( 1:1 ) at -20°C for 5 min . After washing in PBS , blocking buffer ( 4% BSA and 10% normal goat serum in PBS ) was added for 1 hr before incubation with mouse monoclonal anti-HCMV gB or gH , and goat anti-THY-1 for 60 min on ice , followed by anti-mouse Alexa-488 or anti-goat Alexa-594 ( Invitrogen , Grand Island , NY ) on ice for 60 min . For cell surface staining , live cells were treated with blocking buffer on ice for 30 min before incubation with primary and secondary antibodies . After antibody staining , cells were fixed with 2% paraformaldehyde , and mounted with DAPI-Fluoromount-G ( Southern Biotech , Birmingham , AL ) . Confocal imaging was performed with a Leica SP5 X-WLL microscope .
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Human cytomegalovirus ( HCMV ) is an important human pathogen that infects about half the US population and is a major cause of birth defects and morbidity in transplant recipients . Despite extensive research , much is still unknown regarding how the virus enters cells . We identified THY-1 , a protein on the surface of many different cell types susceptible to CMV infection , as having an important role for facilitating virus infection . We found that antibody to THY-1 or soluble THY-1 protein blocked HCMV infection in multiple cell types , suggesting that THY-1 might serve as a potential therapeutic target to reduce infection . Expression of exogenous THY-1 increased susceptibility of cells to HCMV infection . We showed that THY-1 has an important role in a host signaling pathway that is initiated when HCMV infects cells . Furthermore , we found that THY-1 interacted with HCMV glycoproteins that initiate entry of virus into the cell . THY-1 is known to interact with several host cell proteins important for infection and is expressed on numerous types of cells that can be infected by HCMV . Thus , we have identified THY-1 as a molecule that has an important role in the initial stage of HCMV infection .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[] |
2015
|
THY-1 Cell Surface Antigen (CD90) Has an Important Role in the Initial Stage of Human Cytomegalovirus Infection
|
The causes and mechanisms of evolutionary diversification are central issues in biology . Geographic isolation is the traditional explanation for diversification , but recent theoretical and empirical studies have shown that frequency-dependent selection can drive diversification without isolation and that adaptive diversification occurring in sympatry may be an important source of biological diversity . However , there are no empirical examples in which sympatric lineage splits have been understood at the genetic level , and it is unknown how predictable this process is—that is , whether similar ecological settings lead to parallel evolutionary dynamics of diversification . We documented the genetic basis and the evolutionary dynamics of adaptive diversification in three replicate evolution experiments , in which competition for two carbon sources caused initially isogenic populations of the bacterium Escherichia coli to diversify into two coexisting ecotypes representing different physiological adaptations in the central carbohydrate metabolism . Whole-genome sequencing of clones of each ecotype from different populations revealed many parallel and some unique genetic changes underlying the derived phenotypes , including changes to the same genes and sometimes to the same nucleotide . Timelines of allele frequencies extracted from the frozen “fossil” record of the three evolving populations suggest parallel evolutionary dynamics driven at least in part by a co-evolutionary process in which mutations causing one type of physiology changed the ecological environment , allowing the invasion of mutations causing an alternate physiology . This process closely corresponds to the evolutionary dynamics seen in mathematical models of adaptive diversification due to frequency-dependent ecological interactions . The parallel genetic changes underlying similar phenotypes in independently evolved lineages provide empirical evidence of adaptive diversification as a predictable evolutionary process .
The causes and mechanisms of diversification are central issues in evolutionary biology . Explanations that involve the splitting of an ancestral population into geographically or otherwise isolated populations ( allopatric diversification ) have historically been favored because of theoretical difficulties with sympatric diversification ( i . e . , diversification without isolation ) [1]–[5] . In the last 15 years , though , two major developments have increased the attractiveness of sympatric explanations . First , models of sympatric diversification have largely overcome earlier theoretical objections , showing that sympatric diversification can occur due to frequency-dependent selection under a wide range of conditions [6]–[9] . Second , empirical evidence from both laboratory experiments [10]–[19] and field studies [20]–[23] suggests that diversification can occur in sympatry , sometimes on time scales of hundreds of generations , and that such diversification may be an important source of biological diversity . Sympatric diversification can be driven by frequency-dependent selection in a process called adaptive diversification and under conditions that may be quite general [7]–[9] , [24] . This process can be described by the theoretical framework of adaptive dynamics [6] , [25] , [26] . A crucial component of this framework is the concept that the environment a population experiences , and that drives its evolutionary dynamics , depends in part on the phenotypic distribution of the population itself and the resulting ecological dynamics . Adaptive diversification occurs through evolutionary branching [6] , a process in which selection drives a population to a point in phenotype space at which selection becomes disruptive . At this point , the population diverges into two lineages , which may continue to diverge . In general , the problem of adaptive diversification and speciation is 2-fold: on the one hand , one wants to identify the ecological conditions that lead to disruptive selection and evolutionary branching , and on the other hand , one wants to understand the mechanisms interrupting gene flow between ecologically diverging subpopulations . Both of these aspects of adaptive diversification have been studied extensively in the theoretical literature ( e . g . , [7]–[9] ) . Here we experimentally address the first of these issues using asexual organisms , in which mating does not lead to recombination between diverging subpopulations , and which are therefore ideally suited to study the ecological conditions generating the frequency dependence necessary for adaptive diversification . Indeed , adaptive diversification has been documented in microbial evolution experiments [11] , [12] , [27]–[31] in which well-mixed populations of Escherichia coli bacteria founded with a single genotype repeatedly evolve two metabolically distinct phenotypes . When grown in well-mixed serial batch cultures in medium with glucose and acetate as carbon sources , E . coli cells preferentially metabolize glucose and excrete acetate until the glucose is depleted and then undergo a diauxic switch to acetate consumption [32] . In several populations evolving in these conditions for more than 1 , 000 generations , two coexisting phenotypes emerged that differ in their diauxic lag—that is , in the time required to switch to acetate metabolism: the slow switcher ( SS ) has a longer diauxic lag than that of the fast switcher ( FS ) [11] , [28] . These two phenotypes reflect a tradeoff in carbohydrate metabolism: SS strains grow more quickly than FS strains when glucose is abundant , but are unable to efficiently catabolize acetate , while FS strains continue to grow rapidly on acetate after glucose is depleted [28] . The evolution of the FS and SS phenotypes in multiple replicate lines is a striking example of convergence at the phenotypic level , suggesting a deterministic adaptive process . However , the evolutionary branching predicted by adaptive dynamics models necessarily involves changing selective pressures . Therefore , the similar outcomes of diversification across replicate populations are qualitatively different from parallel adaptation to a fixed adaptive landscape . Rather , in this case , the entire process of genetic change leading to environmental change and new selective pressures that in turn cause further genetic change has occurred in parallel . This suggests that not only the outcome of evolution is parallel but the evolutionary dynamics as well . In spite of phenotypic evidence for adaptive diversification , there is limited information available on the genetic changes underlying this process . In fact , to our knowledge there are no examples of sympatric diversification for which the underlying genetics have been fully described . In the FS and SS example , the degree to which the similar , independently evolved phenotypes reflect similar underlying genetics in different populations is unknown . This has implications for the genotype–phenotype map: Are there few genetic ways to produce FS and SS phenotypes or many ? Also unknown is the degree to which the similar evolutionary outcomes reflect similar evolutionary dynamics; the results of previous studies suggest that the degree of similarity in the type , order , and timing of adaptive changes across independently evolving populations varies widely ( e . g . , [33]–[35] ) . This in turn has implications for the degree of determinism in the evolutionary dynamics: Are there many paths or few that lead to similar phenotypic ( and possibly genetic ) outcomes ? And are the changing selective pressures predicted by adaptive dynamics models reflected in genetic changes leading to new selective pressures that in turn cause further genetic change ? If such a pattern is present in multiple replicate lines , this would provide evidence that not only the outcome of evolution is predictable , but the evolutionary dynamics as well . To trace the dynamics of genetic change underlying adaptive diversification , we combined sequencing of FS and SS clones isolated near the end of the evolution experiment with sequencing of whole-population samples from time points in the frozen ( “fossil” ) record of the experiment . We sequenced two FS clones , two SS clones , and 16 time point samples for each of three replicate evolution experiments ( called populations 18 , 19 , and 20 [28] ) . Sequencing of SS and FS clones allowed us to identify mutations associated with the phenotypes of interest , and sequencing of whole-population samples from the fossil record of the experiments allowed us to trace the origin , increase , and ( occasionally ) extinction of these and other mutations . Finally , comparing these results across three independently evolved populations allowed us to assess the degree to which a similar ecological setting led to similar evolutionary dynamics and outcomes ( i . e . , the degree of determinism ) .
Sequencing the SS and FS clones revealed striking similarities in the genetic changes underlying the derived phenotypes across the three replicate populations ( Figure 1 ) . Each of the SS clones carried a mutation in spoT , a deletion of part or all of the ribose operon ( rbs ) , and a mutation in nadR ( Figure 1 ) . One or two additional mutations appeared in some SS clones , but these were not shared between clones . No mutations were fixed in any of the three replicate populations , and in no case was any specific genetic change shared between FS and SS clones . In population 19 , the two SS clones did not share any mutations ( Figure 1b ) , indicating that they evolved independently from the ancestral strain ( although each clone has a mutation in spoT , nadR , and rbs ) . Thus , the six sequenced SS clones represent four separate origins of the SS phenotype , all of which evolved parallel changes to the same three loci . Each of the FS clones carried 6–10 mutations relative to the ancestral strain , most of which were shared between the two clones from each population ( Figure 1 ) . Assuming a single origin for each mutation , we infer that these shared mutations occurred before the two sequenced clones last shared a common ancestor . Phenotypically , the FS type represents a novel metabolic strategy , while the SS type is more similar to the ancestral strain [11] , [27] , [28] , [30] , and this difference is reflected in the underlying genetics . In all three populations , the FS clones are more genetically distant from the ancestor than the SS clones ( paired t test , n = 4 independent comparisons , two-tailed p = 0 . 0008 ) . FS clones from different populations are also more genetically dissimilar than SS clones from different populations: in contrast to spoT , rbs , and nadR in the SS clones , there were no genes that carried mutations in the FS clones from all three populations . Timelines of allelic invasions in the SS and FS lineages are shown in Figures 2–4 . Figure 2 summarizes the evolutionary dynamics unfolding in each of the three evolution experiments , and Figures 3 and 4 show the frequencies of the mutations found in the various SS and FS endpoint clones over time . These timelines suggest that each ecotype affected the other's evolution by altering the available ecological opportunities . In all three evolving populations , nonsynonymous SS-associated spoT and rbs mutations were the first to reach high frequency and likely increased the degree of specialization on glucose [36] , [37] . In population 18 , for which the timeline of metabolic phenotypes has been documented [28] , the rapid rise of these mutations corresponds very well with the increase in the mean switching lag shown in Figure 1B of Spencer et al . [28] . Similarly , in population 20 , SS bacteria were present by generation 200 [31] . In both cases , spoT and rbs were the only SS-associated mutations present when the SS phenotype was first detected , so one or both of these mutations must have caused the SS phenotype . It is known that spoT mutations can confer a substantial advantage by reducing the lag phase before exponential growth on glucose and by increasing the maximum growth rate on glucose , both of which presumably occur through partial deactivation of the stringent stress response [37] , [38] . This may in turn make it harder for the cells to switch to acetate consumption after glucose is exhausted , and hence cause the SS phenotype . Due to an IS150 element immediately upstream of the rbs operon , deletions of all or part of rbs occur at high frequency ( ∼5×10−5 per cell generation ) in the ancestral E . coli strains used in our evolution experiments and provide a ∼1%–2% fitness advantage in glucose minimal medium [36] . Since rbs deletions were also the first mutations to occur in two of the three FS lineages ( Figure 1b , c ) , it is likely that rbs deletions alone do not cause either the SS or the FS phenotype , but rather that rbs deletion mutants were a common genetic background early in the experiment and that the mutations causing the SS and most FS phenotypes occurred on this background . By generation 342 , the frequency of SS-associated spoT and rbs mutations was high ( >65% ) in all three populations ( Figure 3 ) . If either or both of these mutations are responsible for an increase in acetate lag ( as must be the case in population 18 ) , their increased frequency would have caused a change in the daily regime of nutrient concentrations in the experimental environment , namely that more acetate was available later in the growth phase . The first FS-associated mutations began to rise in frequency at this time ( Figures 2 and 4 ) . This wave of invasion involved a different set of genes in each population , but some evidence of parallelism is apparent here as well: the mutations increasing at this time included an identical insertion in the yfbV/ackA intergenic region in populations 18 and 19 , and different mutations affecting the ptsG gene in populations 19 and 20 . In all three populations , the first FS-associated mutations to reach appreciable frequency included ones in or upstream of genes related to acetate utilization and excretion and glucose metabolism . These mutations appeared either in the remaining ancestral genetic background or in rbs deletion mutants and led to coexistence between the SS and FS lineages that persisted until the end of the evolution experiments . These early FS-associated mutations occurred upstream of ackA in populations 18 and 19 , in iclR in population 18 , in pta in population 20 , and in or upstream of ptsG in populations 19 and 20 ( Figure 2 ) . The timing of these invasions , which in all three populations only reached appreciable frequencies after SS-associated mutations had reached high frequency , is consistent with FS-like phenotypes evolving as an adaptation to the novel ecological niche of greater acetate availability generated by increased glucose specialization of the SS . These early FS invasions thus generated the basic SS-FS-polymorphism that persisted to the end of the evolution experiment . Experimental evidence demonstrates that the long-term coexistence of FS and SS is due to frequency-dependent interactions [28]–[31] . Again , in population 18 the correspondence with phenotypic change is conspicuous: clones with a short acetate lag were first detected around the same time ( ca . generation 500 , Figure 1B in Spencer et al . [28] ) at which the first three FS-associated mutations reached appreciable frequency: a nonsynonymous substitution in yijC , an insertion upstream of ackA ( yfbV/ackA+T ) , and a 10 bp deletion in iclR ( Figures 2 and 4 ) . Thus one or more of these must have produced the FS phenotype . By the same logic , one or more of the four FS-associated mutations present in population 20 when FS were first detected at generation 200 ( rbs , pta , ptsG , and yceA ) must be sufficient to produce the FS phenotype . The functions of some genes in the initial FS invasions suggest their involvement in similar phenotypic changes across populations . The yfbV/ackA insertion in populations 18 and 19 affects a potential transcriptional recognition sequence of the global fermentation activator arcA upstream of ackA [39] , suggesting that this mutation affects ackA expression , and hence acetate metabolism . In population 20 , a mutation in pta rose in frequency at about the same time ( Figure 4c ) , and all six sequenced FS clones bear one of these two mutations . Since ackA and pta catalyze subsequent reactions in the pathway of acetate utilization and excretion ( acetate↔acetylphosphate and acetylphosphate↔acetyl-CoA , respectively ) , these two mutations may have similar metabolic effects . The function of ackA as an important regulator of acetate metabolism and the independent origin of the identical yfbV/ackA mutation in populations 18 and 19 strongly suggest that this intergenic substitution is at least partially responsible for the reduced acetate lag in the FS clones ( although FS in population 20 has a different genetic basis ) . Similarly , iclR is a regulator of the acetate operon aceBAK , and in an experimental population not included in this study , an insertion in iclR acting as a stop codon was previously shown to be partly responsible for the FS phenotype by derepressing the acetate operon [27] . This suggests that the iclR deletion in population 18 has contributed to the FS phenotype as well . Finally , yijC , a repressor of genes involved in fatty acid biosynthesis [38] , could play a role in the FS phenotype by altering the relative amounts of acetyl-CoA used in fatty acid biosynthesis and in the citric acid cycle . In population 20 , a mutation in ptsG was one of the first FS-associated mutations to invade ( Figure 4c ) , while in population 19 , an IS186 insertion sequence appeared in the intergenic region upstream of ptsG around the same time , potentially disrupting its transcriptional regulation . The enzyme encoded by ptsG , a glucose-specific PTS permease , is involved in the uptake of glucose and its transport across the cell membrane [40] , and disruption or down-regulation of these functions would be consistent with the FS phenotype . After FS mutations had risen to intermediate frequencies ( >0 . 15 ) , several SS-associated nadR mutations appeared at detectable frequencies in each of the three populations ( Figures 1 , 2 , and 5; Text S1 ) . The proliferation of these mutations ( ≥5 in each population ) after generation 500 is striking since no nadR mutations were present at detectable frequency before this time . nadR plays an important role in many metabolic pathways , including growth on carbohydrates [41] , [42] , and the observed mutations show a surprising degree of parallelism . The highest-mean frequency nadR mutation in population 20 ( nadR-290 ) was identical to that in 19-SS1 in population 19 , and a different mutation in the same codon was present in population 18 . All three populations also included a mutation in codon 294 of nadR , and this was identical between populations 18 and 20 ( Figure 5a , c ) . Thus , a different pair of mutations in these two codons is found in each of the three populations , though each mutation is shared by two populations . The nadR mutation found in both SS clones from population 18 was only detected in a single Illumina read in the time point samples ( at generation 482 ) , indicating that it was present at very low frequency . The presence of such a low-frequency mutation in both sequenced clones suggests that it had a phenotypic effect ( since we preferentially selected clones that were clearly of the SS phenotype; see Materials and Methods ) . The protein encoded by nadR has both enzymatic and regulatory roles in the NAD biosynthetic pathway and plays important roles in glycolysis and the citric acid cycle . The presence of nadR mutations in all six sequenced SS clones and none of the six sequenced FS clones strongly suggests that these mutations are adaptive for the SS , but not the FS , phenotype . It is interesting to note that mutations in nadR were found in 12 of 12 experimental E . coli populations after 20 , 000 generations of evolution in glucose minimal medium [42] , and that one of these was identical to the nadR-290 mutation in populations 19 and 20 . In populations 18 and 20 , invasion by SS-associated nadR mutants was followed by rapid increases in frequency of a second set of FS-associated mutations ( Figure 2 ) . In population 18 , a spoT mutation identical to that in FS from population 20 ( spoT-414 ) increased in frequency only to be replaced by another spoT mutation ( spoT-369 ) that had previously been present at very low frequency . In population 20 , the second set of FS-associated mutations included one in a global regulator ( arcA ) known to increase acetate consumption [31] . It is likely that the FS-associated arcA mutation in population 20 affects the expression of ackA; if so , one of the phenotypic effects of this mutation may be similar to that of the yfbV/ackA insertion in populations 18 and 19 . This would explain why this mutation has a larger impact on SS clones than on FS clones [31]: if the primary phenotypic effect of the arcA mutation is to alter the rates of acetate utilization and/or excretion , the FS-associated pta mutation may have made this effect at least partially redundant in population 20 . In addition to the spoT mutations associated with FS and SS clones , one other mutation in spoT was present at ≥20% frequency at some time in each of the three populations ( Figure S1 ) . In populations 18 and 20 , this mutation was lost by the end of the experiment . In population 19 this spoT mutation increased in frequency near the end of the experiment as the spoT mutation associated with 19-SS1 underwent a corresponding decline . The transient spoT mutation in population 18 was identical to that associated with the FS clones in population 20 ( Figure S1a , c ) , and hence is likely to be FS-associated . This indicates that mutations in the stringent response can be adaptive for either the SS or the FS phenotype [43] . The phenotype associated with the spoT-316 mutation in population 20 is not known . Several other mutations not associated with any of the FS and SS clones were present at detectable frequencies in each of the three fossil records ( Figure S2 ) . A complete list of detected mutations and the samples in which they were found is shown in Table S1 .
Microbial evolution experiments are a powerful approach to understanding evolutionary dynamics , combining controlled conditions with the capability for experimental replication to allow strong inferences of causation . In addition , rapid reproduction allows laboratory experiments lasting hundreds or thousands of generations , and cryopreservation allows direct comparisons between ancestors and descendants . The recent rapid advance of nucleic acid sequencing technologies has made whole-genome sequencing feasible for both single microbial strains and whole populations containing a variety of strains . The combination of microbial evolution experiments and next-generation sequencing technologies provides an unprecedented opportunity to observe the temporal dynamics of evolutionary change across the entire genome [44] , [45] . Replicating this approach in multiple independent populations can tell us whether adaptive sympatric diversification in independent populations involves similar genetic mechanisms and similar evolutionary dynamics . Our results revealed both shared and unique genetic mechanisms underlying the evolution of pairs of metabolically distinct ecotypes in different populations . In some cases , similar phenotypes had mutations in different genes ( e . g . , the wecF , uppS , and arcA mutations in the FS clones from populations 18 , 19 , and 20 , respectively; no mutations in these genes were detected in either clones or time point samples in the other populations ) . In some cases , mutations affected different codons of the same gene , as in the distinct spoT and nadR mutations found in the SS clones from all three populations . We also observed different changes to the same codon ( e . g . , codons 290 and 294 of the nadR gene; Figures 2 and 5 ) . Finally , we found four examples of identical genetic changes in different populations: spoT-414 ( populations 18 and 20; Figure 2 ) , yfbV/ackA ( 18 and 19; Figure 2 ) , and two nadR codons ( 290 identical in populations 19 and 20 , Figure 2; 294 identical in 18 and 20 , Figure 5 ) . Of the 45 mutations shown in Figure 1 , 21 ( 47% ) occurred in a nucleotide , codon , or gene that also had a mutation associated with the same ecotype in another population . The pattern of genetic invasions evident in the fossil records also revealed strikingly similar evolutionary dynamics: in all three evolving populations , SS-associated spoT and rbs mutations were the first to invade , followed by FS-associated mutations affecting acetate and glucose metabolism , followed by SS-associated mutations in nadR , and finally additional FS-associated mutations . In spite of several mutations showing evidence of strong positive selection , such as the SS-associated spoT mutations in all three populations , no mutation was fixed in any of the three populations . Many mutations that increased rapidly after their initial appearance later declined in frequency yet were then maintained in the populations at intermediate frequencies . Apart from genetic drift , two separate ( but not mutually exclusive ) processes could explain the repeated and parallel invasions and long-term coexistence observed in these three populations . We do not consider genetic drift as an explanation because the large effective population sizes make drift implausible for allele frequency changes greater than a fraction of 1% from one time point sample to the next ( see Materials and Methods ) . Clonal interference , which involves the coexistence of two or more beneficial mutations on different genetic backgrounds , is one potential explanation . This process allows long transient polymorphisms to be maintained in asexual populations because several different and almost equally beneficial mutations can be present in different subpopulations [46]–[48] . Thus , clonal interference is expected to lead to longer fixation times , elevated levels of polymorphism , and generally more complex evolutionary dynamics in asexual populations such as the ones studied here . One probable example of clonal interference is the replacement of spoT-414 by fecI/insA-25 , spoT-369 , and wecF-244 within the FS lineage in population 18 . Around generation 700 , the spot-414 mutation appeared on the FS background and began to rapidly invade , while the fecI/insA-25 and spoT-369 mutations remained at low frequency . Before the spoT-414 mutation could reach fixation within the FS lineage , though , the wecF-244 mutation appeared and quickly replaced all other FS lineages , including that with spoT-414 . Another possible explanation for long-term coexistence is the coevolution of diverging phenotypes through environmental feedbacks and frequency-dependent selection . In this scenario , the adaptive landscape changes as metabolic changes in one subpopulation create a new niche , which another subpopulation evolves to fill . Since the only source of environmental change over the course of the experiments was the bacteria themselves , any such changes in the selective regime must have been generated by changes in the genetic , and hence metabolic , makeup of the bacterial populations . Such environmental feedback generates frequency dependence and is at the core of the theory of adaptive diversification [6]–[9] . An example of environmentally mediated negative frequency dependence is the interaction between the SS lineage and the wecF-244 containing FS lineage in population 18: the wecF-244 mutation invaded the FS lineage rapidly , indicating a strong selective advantage . In the absence of any frequency-dependent interactions , such an advantageous mutation would continue to invade , going quickly to fixation unless another even more advantageous mutation appeared ( as in the clonal interference scenario ) . In this case , though , neither of these explanations is viable: after quickly fixing within the FS lineage , the wecF-244 mutation leveled off ( or even declined in frequency ) in the absence of any new mutations . Taken by themselves , most of our results could be explained by either clonal interference or reciprocal niche construction . Since both processes can explain the long-term coexistence of multiple lineages , it can be difficult to distinguish between them . However , the populations in this study have also been the subject of numerous previous studies , and this prior work aids substantially in interpreting the current results . When this additional information is taken into account , it is clear that although clonal interference may explain some of the observed dynamics , it is unlikely to explain all of them . The main reason for this is that we already know from previous experimental analyses that the coexistence between the SS and FS ecotypes involves frequency dependence , at least in populations 18 and 20 ( e . g . , [28]–[31] ) . In particular , the polymorphisms between SS and FS lineages that we observed arising early on in the evolution experiments are maintained by selective forces favoring rare ecotypes . For population 20 , [31] has explicitly shown the action of frequency dependence throughout the fossil record in invasion experiments with SS and FS strains extracted at various time points . In addition , Spencer et al . [28] have already argued in detail why clonal interference is unlikely to be the main driver for the pattern of evolutionary branching observed in population 18 , which is one of the populations used for the present study . Clonal interference may have played a role in generating some of the polymorphisms observed within the SS and within the FS lineages , and in the timing of the rise of various mutations . Overall , however , it seems clear that the basic coexistence between the SS and FS ecotypes are not due to clonal interference , but to frequency-dependent ecological interactions . Indeed , similar evidence has led to the conclusion that a polymorphism in one of R . Lenski's long-term experimental lines , Ara-2 [18] , [49] , evolved as a result of niche construction [15] , [50] . It is a hallmark of frequency dependence that one type's abundance creates the niche for another type's invasion . Although we cannot rule out clonal interference , the sequence of alternating invasions observed in the fossil records of our experimental lines is consistent with this process of reciprocal niche construction . In particular , as is apparent from Figures 3 and 4 , the rise of the first FS mutations consistently following in the wake of the establishment of first SS mutations is conspicuous , and so is the rise of the SS-associated nadR mutations following the appearance of the first FS mutations . We note that the limited replication of this study prevents many rigorous statistical tests , so that many of our results can only be described qualitatively , not quantitatively . With the continuing rapid decline in the cost of sequencing data , it is quickly becoming feasible to carry out studies similar to ours with higher temporal resolution and across larger numbers of populations , which will make rigorous statistical analyses possible . Nevertheless , it seems unlikely that the consistent pattern of alternating invasions observed in our three lines is due to chance alone , and given that the endpoint FS and SS strains coexist due to frequency dependence , it is tempting to conclude that the patterns of invasion reflect the action of frequency-dependent selection in the course of the evolution experiment . The observed diversification should then be viewed in the light of the theory of adaptive diversification due to frequency-dependent interactions [9] . It is worth noting that much ( but not all ) of this theory is based on the assumption of many mutations of small effect , and the basic theoretical phenomenon of evolutionary branching in particular is an essentially continuous process in phenotype space [6] , which moreover is often presented as a symmetric pattern of diversification . In contrast , in our experimental lines diversification is obviously due to a few mutations of large effect , and the pattern of diversification is asymmetric in phenotype space [28] . However , many aspects of the theory of adaptive diversification are robust to introducing large mutational effects , and asymmetric evolutionary branching is entirely feasible [9] . Therefore , our experimental results can be seen as proof of this robustness , and as providing a full description of adaptive diversification at the genetic level , revealing parallel evolutionary dynamics , and thus a high degree of determinism , in the sympatric origin and subsequent divergence of ecologically distinct lineages .
We isolated clones from frozen samples of populations 18 and 19 from day 156 of the evolution experiment of Spencer et al . [28] . Frozen samples were inoculated into 10 mL of the growth medium , grown overnight at 37°C with shaking , and spread onto agar plates . We arbitrarily chose 10 small colonies and 10 large colonies from each population and measured their growth profiles over 24 h as described in Spencer et al . [28] . From each population , we chose two large colonies with unambiguous SS growth profiles and two small colonies with unambiguous FS growth profiles for sequencing . For population 20 , we used previously isolated clones [30] , also from day 156 of the experiment . In this experiment , replicate populations were founded from isogenic lines of E . coli B and cultured in well-mixed condition for 183 d ( ∼1 , 230 generations ) with daily ( ∼6 . 7 generations ) transfers to fresh medium ( Text S1 ) . Populations 18 and 20 were initiated with REL606 , and population 19 with REL607 [51] . REL606 and REL607 perform similarly in the growth environment of the evolution experiment [28] , [51] , [52] . For the time point samples , we chose 16 time points corresponding to days 0 , 6 , 12 , 19 , 30 , 40 , 51 , 61 , 72 , 82 , 96 , 111 , 124 , 138 , 156 , and 183 of the evolution experiment for a total of 48 time point samples . We sequenced paired ends of fragments of genomic DNA samples from 12 clones ( 2 SS and 2 FS from each of three populations ) and 48 time point samples ( 16 time points from each population ) on an Illumina HiSeq 2000 using standard procedures . The paired t test reported for number of mutations in FS versus SS compared the mean number of mutations in FS clones to that in SS clones from the same population , considering only genealogically independent comparisons ( one each for populations 18 and 20 , two for population 19 , since there were two independent origins of SS in this population ) . Paired-end sequencing was performed on an Illumina HiSeq 2000 at the University of British Columbia's Biodiversity Research Centre . The clonal samples were prepared with the Illumina TruSeqTM DNA Sample Preparation Kit , and the time point samples with the NEXTflex DNA Sequencing Kit and DNA Barcodes by Bioo Scientific ( Austin , TX ) . We used CASAVA 1 . 8 ( Illumina , Inc . , San Diego , CA ) to demultiplex sequencing reads by barcode and generate files in FASTQ format [53] for use in all downstream analyses . All FASTQ files were deposited in the NCBI short read archive ( accession: SRP017657 ) . We identified SNPs and small ( ≤4 bp ) indels and estimated their frequencies in the time point samples using both the main public server and local instances of Galaxy ( details below ) [54]–[56] . To identify larger indels and estimate their frequencies in the time point samples , we used BreSeq version 0 . 16 [57] . The sequence [58] of the ancestral strain REL606 ( GenBank accession number NC_012967 . 1 ) was used as the reference for all mutation screens . FASTQ files were first filtered for quality , retaining only those reads with ≤5 bases with quality scores <20 . Reads were aligned to the reference genome using BWA version 0 . 5 . 9-r16 [59] with default settings and treating the reads as single-end , and variants were identified using SAMTools version 0 . 1 . 12-r862 [60] . For the 60 sequenced samples ( 12 clones and 48 time points ) average coverage ( over the 4 , 629 , 812 bp of the reference genome ) ranged from 72× to 2 , 500× . For all 60 samples , >99% of the genome was covered by >30 aligned reads . We report the frequencies of all variants that both appear in more than one time point sample ( within the same population ) and rise to at least 5% frequency in one or more of the samples . We also report the frequencies of variants that are found in the clonal samples , regardless of their frequency in the time point samples . Variants supported by a single read at a given time point are not reported unless supported by multiple reads in the next time point . We estimated the frequencies of large deletions ( >4 bp ) by manually inspecting all reads in which ≥10 bp matched each side of the deleted region . In a few cases , we were able to determine linkage between nearby mutations by examining individual Illumina reads that spanned both loci . To distinguish changes in allele frequency due to selection from those due to drift , we assume an effective population size ( Ne ) of 3 . 3×107 , as estimated for E . coli grown in similar conditions [51] . Under the Wright-Fisher model [61] , [62] , drift is a Markov chain , which generates a variance in allele frequency of pq/Ne after one generation ( for haploids ) . After t generations , the variance is pq ( 1 – et/Ne ) . If we assume p = q = 0 . 5 ( which yields the fastest drift ) , the variance after 82 generations ( the average time separating our time point samples ) is 6 . 21×10−7 ( s . d . = 7 . 88×10−4 or 0 . 08% ) . Using the normal approximation of the binomial , the probability that drift causes an allele frequency change ≥1% from one time point sample to the next is less than 1×10−12 . Thus , even accounting for multiple tests , the possibility that any of the changes in allele frequency that we discuss are caused solely by drift is remote .
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The causes and mechanisms of evolutionary diversification are central issues in biology . There is well-established theory that predicts that adaptive diversification can arise because of ecological interactions between individuals , such as competition or predation , but there are no empirical examples in which this process has been observed at the genetic level . We documented the genetic basis of adaptive diversification resulting from competition for resources in populations of the bacterium Escherichia coli . The populations diversified into two coexisting ecotypes representing different physiological adaptations . We found that similar but independently evolved phenotypes often shared mutations in the same gene and , in four cases , shared identical mutations at the same nucleotide position . Timelines of allele frequencies extracted from the frozen “fossil record” of three evolving populations showed parallel evolutionary dynamics , suggesting that mutations causing one type of physiology changed the ecological environment and allowed invasion of mutations causing an alternate physiology . The results provide empirical evidence of adaptive diversification as a predictable evolutionary process .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"biology"
] |
2013
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Parallel Evolutionary Dynamics of Adaptive Diversification in Escherichia coli
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The herpesvirus proteins HSV-1 ICP27 and HVS ORF57 promote viral mRNA export by utilizing the cellular mRNA export machinery . This function is triggered by binding to proteins of the transcription-export ( TREX ) complex , in particular to REF/Aly which directs viral mRNA to the TAP/NFX1 pathway and , subsequently , to the nuclear pore for export to the cytoplasm . Here we have determined the structure of the REF-ICP27 interaction interface at atomic-resolution and provided a detailed comparison of the binding interfaces between ICP27 , ORF57 and REF using solution-state NMR . Despite the absence of any obvious sequence similarity , both viral proteins bind on the same site of the folded RRM domain of REF , via short but specific recognition sites . The regions of ICP27 and ORF57 involved in binding by REF have been mapped as residues 104–112 and 103–120 , respectively . We have identified the pattern of residues critical for REF/Aly recognition , common to both ICP27 and ORF57 . The importance of the key amino acid residues within these binding sites was confirmed by site-directed mutagenesis . The functional significance of the ORF57-REF/Aly interaction was also probed using an ex vivo cytoplasmic viral mRNA accumulation assay and this revealed that mutants that reduce the protein-protein interaction dramatically decrease the ability of ORF57 to mediate the nuclear export of intronless viral mRNA . Together these data precisely map amino acid residues responsible for the direct interactions between viral adaptors and cellular REF/Aly and provide the first molecular details of how herpes viruses access the cellular mRNA export pathway .
All herpesviruses replicate in the host cell nucleus and therefore utilise the host cell's protein transcription and translation apparatus , while at the same time suppressing the correspondent cellular processes [1]–[5] . Crucially , non-spliced viral mRNA is directed into the cellular mRNA export machinery , thus bypassing the stringent cellular controls which normally ensure that only fully processed mRNA is exported from the nucleus to the cytoplasm . In an uninfected cell , the process of mRNA export is closely connected with mRNA processing and splicing , which in turn are coupled with transcription . Cellular mRNA export involves the assembly of a multi-protein transcription and export ( TREX ) complex containing the RNA export factor REF/Aly; this signals that processing is complete and the cellular mRNA is ready to be exported via a TAP/NXF1-mediated interaction with the nuclear pore [6]–[8] . TAP forms a heterodimer with p15 and binds nucleoporins via central and C-terminal UBA-like domains [9] . REF/Aly provides a crucial link between mRNA and TAP: the binding of mRNA and TAP to REF are mutually-exclusive . TAP binding to REF-mRNA complex triggers transfer of RNA from REF to TAP . While REF is bound , it switches TAP into a high-affinity binding mode for RNA [10] . Once the ribonucleoprotein complex reaches the nuclear pore , REF dissociates and the mRNA is transported to the cytoplasm [11] . It is also possible that other cellular mRNA export factors may fulfil a role similar to that of REF/Aly [12]–[14] . Unlike cellular mRNA , the herpesvirus mRNA is often unspliced , therefore it cannot acquire export marker proteins using the normal pathway , via coupled transcription , splicing and export . To facilitate the efficient export of intronless viral mRNA all herpesviridiae produce a multi-functional adaptor protein [15] that shuttles between the nucleus and cytoplasm [3] , [4] , [16] , and bridges between the viral mRNA and components of the TREX complex such as REF/Aly , thus marking viral mRNAs for export via TAP/NFX1 [17] , [18] . In Herpes Simplex Virus type I ( HSV-1 ) the infected cell protein 27 ( ICP27 ) acts as the adaptor [3] , [19] . In Herpesvirus Saimiri ( HVS ) , the prototype γ-2 herpesvirus with close similarity to human Kaposi's Sarcoma-associated herpesvirus ( KSHV ) , this role is carried out by the ORF57 protein [4] , [20]–[22] . The regions of ICP27 and ORF57 involved in REF binding have been studied by analysing the effects of polypeptide truncations . For ICP27 it has been inferred as amino acids ( aa ) 104–138 [19] , [23] . Recent in vivo studies suggested that the RGG box aa 138–152 , which is involved in viral mRNA binding [2] , [24]–[26] , is also involved in REF/Aly interactions [27] . However , earlier in vitro data indicate that the RGG region does not bind REF directly [19] . In ORF57 the interactions with REF and with viral mRNA were localised within aa 8–120 [22] , [28] , [29] . Thus the identified regions of ICP27 and ORF57 apparently perform a similar function ( REF/Aly and viral mRNA binding ) , however these regions lack any obvious sequence similarity which would highlight a common REF-binding motif . Moreover , it was not known whether ICP27 and ORF57 bind REF in a similar way . A number of previous studies used deletion mutants of REF to locate viral binding sites [22] , [30] , [31] , however in the absence of structural information at that time , these mutations inadvertently perturbed the spatial structure of REF . The solution structures of murine Aly containing only the folded RRM domain [32] and the functional fragment of REF2-I which contained both the RRM and N-terminal domains ( residues 1–155 ) have since been determined and characterised [33] . The REF2-I RRM domain at the surface-exposed area of α-helices 1 and 2 contains overlapping secondary binding sites for TAP and UAP56/DDX39; in the free form this binding site is shielded by loose binding of the N-terminal helix [33] . Additionally , this RRM has a non-canonical secondary RNA-binding site comprised of the loop regions [33] . The site of viral adaptor binding however remained unknown , making it difficult to understand how the assembly of the viral mRNA-protein complex is achieved . Here we apply NMR spectroscopy to explore the binding of ICP27 and ORF57 with REF at a residue-level resolution and report a side-by-side comparison of the essential peptide fragments of ORF57 and ICP27 required for binding with REF . We demonstrate that the REF recognition site of ICP27 is very short but highly specific . The atomic resolution structure of REF RRM domain bound with the fragment of the viral protein adaptor is presented . The respective REF-binding site on ORF57 is longer and includes several weaker points of contact . The two viral proteins however bind at the same site on the REF RRM domain , which overlaps with the secondary TAP-binding site . The identified key residues of ORF57 for its interaction with REF are confirmed by side-directed mutagenesis and ex vivo studies .
To confirm the position of REF-binding domains within ICP27 and ORF57 and to minimise the size of constructs for more detailed NMR mapping , a series of fragments derived from HSV-1 ICP27 were screened for binding to GST-REF2-I using pull down assays ( Fig . 1 ) . The binding of ICP27 aa 1–138 ( ICP271–138 ) was essentially the same as that of the full-length protein , whereas ICP271–103 and ICP27139–512 showed no binding ( Fig . 1B ) , confirming aa 104–138 contain the REF interaction site in vitro , in agreement with previous studies [19] , [23] . The GST fusion of ICP27103–138 was found to interact similarly with full-length REF1–218 , REF1–155 and REF54–155 under the given conditions , but only weakly with REF1–70 . These data indicate aa 104–138 of ICP27 are necessary and sufficient for interaction with REF ( Fig . 1C ) . The REF-binding fragment of ORF57 aa 8–120 identified previously [22] similarly interacted with the same fragments of REF ( Fig . 1D ) . Unlike an earlier study [22] , the REF54–155 construct used here does not perturb the structure of the RRM domain [33] . These experiments showed that the main binding sites for both viral proteins are located within the REF54–155 construct . To compare the mode of interaction of ICP27 and ORF57 with REF in more detail , NMR chemical shift mapping of backbone amides of 15N-labelled REF1–155 and REF54–155 was carried out ( see Supporting Information available online , Fig . S1 ) , by adding unlabelled ICP271–138 or ORF578–120 ( Fig . S2 ) and monitoring signal shifts in 1H-15N correlation spectra . The sequence-specific signal assignment of REF in free form [34] was used to identify amino acids affected by binding . This indicated that while there may be a weak transient interaction with the N-terminal region of REF , especially for ORF57 , the main interaction site is located in the REF RRM domain . The similar pattern of residues showing changes in chemical shifts induced by ICP27 and ORF57 indicated that both viral proteins bind REF on the same site ( Supporting Information , Fig . S1E ) . No significant changes were observed in the 1H-15N correlation spectra of 15N-labelled REF156–218 upon addition of ICP271–138 or ORF578–120 , confirming that the REF C-terminal domain is not involved in binding with these viral protein constructs ( Fig . S1F ) . These initial studies thus confirm ICP27 and ORF57 bind REF in a similar manner . To identify which amino acids of ICP27103–138 and ORF578–120 bind REF54–155 , the sequence-specific backbone assignment of free and bound forms of all these constructs was completed . Titrations were performed using additions of non-labelled polypeptides to 15N-labelled constructs , while monitoring spectral changes in 1H-15N correlation spectra . ICP27103–138/ORF578–120 was added to REF54–155 , and vice versa . This enabled the mapping of interaction sites on all proteins at a residue-level resolution . The values of heteronuclear 15N{1H} NOE were also measured to identify the parts of polypeptide chains with altered mobility due to binding ( data overview on Fig . 2 , with the more detailed data included in the Supporting Information ) . Titration of REF with ICP27103–138 confirmed that this short peptide interacted with REF in the same manner as the longer ICP271–138 construct , and also in a similar manner as ORF578–120 . The viral protein binding site on REF RRM was mapped to α-helices 1 and 2 plus the adjacent loop regions ( Fig . 2A and Fig . S3 ) . The converse titration showed that only a short section of ICP27103–138 , namely aa 104–112 , displayed chemical shift changes and decreased mobility , whereas the rest of the peptide remained flexible in complex ( Fig . 2C and Fig . S4 ) . Similarly , addition of REF54–155 caused significant changes in signal positions and signal broadening , along with decreased mobility , primarily within a short section of residues 103–120 of ORF578–120 ( Fig . 2B and Fig . S5 ) , the rest of the peptide was only weakly affected by binding . The REF-binding site of ORF57 thus appears to be significantly longer than that of ICP27 , however both viral peptides bind to the same site on REF ( Figs . 3A , B ) . Unlike the ICP27103–138 -REF54–155 complex , in the ORF578–120 - REF54–155 complex a number of signals are broadened beyond detection , indicating that the latter complex is in the intermediate chemical exchange regime and hence is not suitable for atomic-resolution structural studies . To obtain a detailed view of the ICP27103–138 interaction with REF54–155 we determined the atomic-resolution structure of this complex ( Fig . 4A–G ) . The structure of the complex is well-defined owing to a large number of intra- and inter-molecular NOEs observed and assigned ( Table 1; also Fig . S6 ) . In agreement with the chemical shift mapping data , the viral peptide binds as a linear chain along the cleft formed by two α-helices on the surface of the RRM domain , which largely preserves its structure . However in the bound state the α-helix 1 of REF is shifted by approximately 3 Å ( Fig . 4C ) . This shift causes some rearrangements within the looped regions , especially aa 136–146 . These changes are accompanied by a noticeable decrease in mobility within the residues 86–90 , 93–99 , 132 and 137–145 as evidenced by 15N{1H} NOE data ( Fig 2A ) . The shift in α-helix 1 exposes the sidechain of F98 for interaction with W105 of the peptide , and brings closer the sidechains of a hydrophobic patch composed of L94 , Y135 , V138 , L140 and M145 ( Fig . 4D , E ) . The upper edge of α-helix 1 contains a negatively charged patch of D90 , E93 and E97 ( Fig . 4F ) . The extended region aa 104–109 of ICP27 sitting along the REF cleft is followed by a loose bend at 109–112 which makes additional contacts with REF and points the remainder of the peptide chain away from the site . The region aa 114–138 remains flexible and hence does not participate in binding , in agreement with a lack of intermolecular NOEs and absence of signal shifts . From a structural perspective , three ICP27 residues appear most important for the interaction , forming a recognition triad ( Fig . 4E ) . The sidechain of W105 makes hydrophobic contacts with F98 of REF and also with the aliphatic part of the R107 sidechain of ICP27 . R107 forms salt bridges with the acidic residues of REF α-helix 1 ( E93 and/or E97 , the latter is the most likely binding partner in light of the decrease in mobility observed ) . L108 fits into a hydrophobic pocket composed of REF residues V86 , L94 , Y135 , V138 , L140 , M145 . Additionally V104 may also play a role in stabilising the complex , by forming hydrophobic contacts with the aliphatic parts of K130 and K133 of REF . The sidechain of S106 is solvent exposed and does not appear to directly bind REF . The ICP27 binding site shows a surprising degree of complementarity to REF , with a very short sequence used for highly specific recognition . Herpes simplex virus ( HSV ) causes common infections in humans that occur on the mouth and lips , including cold sores and fever blisters . Although murine REF2-I protein employed in this study is commonly used as a model to study mRNA export , potentially there may be differences in the way ICP27 recognises its native partner Aly , the human orthologue of murine REF . Here we explored this issue in detail . A sequence alignment of murine REF2-I , murine Aly ( mAly ) and human Aly ( hsAly ) ( Fig . 5A ) show very high level of homology within the RRM domains . Specifically there are seven amino acid substitutions between murine REF2-I and human Aly ( Fig . 5A ) . However , only one of these substitutions lies within a binding site ( Fig . 5B and C ) , namely V138 ( which is a phenylalanine in human Aly ) . This conservative substitution is positioned on the periphery of the hydrophobic pocket that contacts L108 of ICP27 . Molecular modelling of the structure of human Aly bound to ICP27 was performed to see how significantly the binding interface with ICP27 is affected by the differences in sequence ( Fig . 5D and E ) . The modelling results show that the increase in hydrophobic sidechain volume of the V138F mutation could be readily accommodated by the movement of the sidechain of M145 ( Fig . 5E ) . All other amino acid substitutions were positioned away from the binding interface . Comparison of modelled hsAly-ICP27 and experimental murine REF-ICP27 solution structure showed a heavy atom backbone RMSD of only 0 . 04 Å , with the architecture of ICP27 binding site maintained in both homologues . Therefore we conclude that ICP27 can bind to human Aly in the same manner as to murine REF2-I . The characteristic triad , Trp followed shortly by Arg and then by a hydrophobic residue , is also found in the REF-binding region of ORF57 , and bears distant similarity to the sequences of some other viral protein adaptors ( Table 2 and Fig . S2 ) . To probe the specificity of recognition , 12 synthetic peptides were tested for binding with REF54–155 ( see Table 2 ) . The first set of peptides was derived from ICP27 and included WT ICP27103–112 and its three single point mutants W105A , R107A and L108A , plus a shorter WT ICP27103–110 peptide with two arginines removed . The second set was derived from HVS ORF57 and included WT HVS-ORF57103–120 , and its W108A , R111A and V112A mutants , along with a shortened peptide WT HVS-ORF57105–115 designed to probe the minimal binding region of ORF57 for REF . Additionally , two peptides were chosen from other viral proteins with apparent sequence similarity but containing some variations in the triad residues , to test how well these can bind REF in our experiments . We used sequences from Varicella-zoster virus ( VZV ) ORF4108–119 ( Tyr instead of Trp ) and Kaposi's sarcoma-associated herpesvirus ( KSHV ) ORF57100–110 ( Tyr instead of Trp , and Lys instead of Arg ) . No prior data was available whether this VZV-ORF4 fragment binds to the RRM domain of REF . For KSHV-ORF57 a different region was previously implicated in binding with REF [35] , [36] , therefore the peptide KSHV-ORF57100–110 was not expected to interact and was used here as a negative control . A separate titration of each peptide was carried out under the same sample conditions . Increasing amounts of peptide were added to a 15N-REF54–155 sample , achieving binding saturation whenever possible . Throughout these titrations amide chemical shift changes were monitored to assess the relative binding affinity of these peptides for REF and simultaneously map their binding sites . Estimates of dissociation constants were obtained for each peptide , and for the longer viral adaptor fragments ( Table 2 ) . The WT ICP27 peptides 103–112 and 103–110 showed very similar binding characteristics to the longer aa103-138 construct , confirming that this peptide comprises the entire binding site ( Fig . S3 ) . The mutant peptide W105A showed reduced affinity to REF54–155 but still bound with similar chemical shift change pattern ( Fig . 3D and Fig . S3 ) . A reduction in affinity was more pronounced in the L108A mutant , with the R107A mutation virtually abolishing the binding . For the HVS peptides , ORF57103–120 bound with affinity comparable to ORF578–120 , whereas affinity was decreased approximately two orders of magnitude in the shortened fragment WT-ORF57105–115 . This agrees with the NMR mapping data that a longer sequence from ORF57 ( residues 103–120 ) is involved in REF binding . The ORF57 mutant peptides R111A and V112A showed significantly reduced affinity for REF54–155 , whereas the W108A mutant showed virtually no interaction . The VZV-ORF4108–119 peptide bound only weakly to REF54–155 , whereas the KSHV-ORF57100–110 peptide used here as a negative control did not bind noticeably to REF ( Table 2 ) . These latter two viral adaptors lack the signature Trp residue , and additionally in KSHV-ORF57 the Arg within the triad is replaced by Lys . As a further control , we also checked if binding of the viral peptides is specific to the RRM domain of REF , or if it can occur with RRMs of other proteins as well . The proteins SF2 [37] and 9G8 [38] bind TAP/p15 and have roles in splicing and mRNA export somewhat similar to that of REF/Aly . They also contain an RRM domain and are therefore structurally homologous to REF/Aly . To test if the same ICP27 motif could interact with these RRM domains , we added a 5-fold excess of WT ICP27103–112 peptide to 15N-labelled SF2 [37] and 9G8 [38] . However no significant spectral changes and hence no binding was observed ( Fig . S1 ) . These experiments confirmed that the recognition of the REF RRM domain by viral adaptor proteins is highly specific , and the isolated peptides ICP27103–112 , ICP27103–110 and ORF57103–120 are able to bind REF as efficiently as longer fragments of these viral proteins . Recently it had been suggested that phosphorylation of S114 of ICP27 [39] may affect its interaction with REF . In the structure obtained here , this Ser is situated right on the edge of the binding interface . In order to probe the possible effect of its phosphorylation on the interaction with REF , the mutant ICP27103–138 S114E was produced to mimic the presence of the negative charge on the sidechain . Titration of 15N-labelled REF54–155 with unlabelled ICP27103–138 S114E revealed binding to the same site on REF ( Fig . S3 ) and KD estimation showed that the affinity was only marginally different from the wild type ICP27103–138 construct ( Table 2 ) . To determine if the S114E mutation had any effect on the structure of the ICP27 construct used , we assigned and compared the fingerprint 1H-15N correlation spectra of 15N-labelled ICP27103–138 S114E mutant with that of the WT . The spectra overlaid well for all residues apart from residue 114 itself and its immediate sequential neighbours . According to 15N{1H} NOE measurement , both peptides were flexible in the free form , hence no structural changes were detected due to mutation . Titration with unlabeled REF54–155 indicated that the signals from the same region ( aa 104–112 ) as WT ICP27 are most perturbed , with only a relatively small signal shift observed for E114 itself . These data suggest that there are no significant changes in direct binding of ICP27 to REF RRM in the mutant which mimics phosphorylation of S114 . To confirm the functional significance of critical residues within the REF binding site identified in ORF57 by chemical shift mapping experiments and analysis of synthetic peptide binding , a series of co-immunoprecipitation experiments were carried out using wild type and mutant forms of GFP-tagged full-length ORF57 and endogenous Aly in human cells ( Fig . 6 ) . Mutants were chosen that target the candidates for the recognition triad , as well as selected residues in the binding site and within the vicinity . All tested mutations within the proposed main binding site caused a significant decrease in ORF57-Aly affinity ( namely , W108A , double R111A+V112A and R119A+R120A , and also triple W108A+R111A+V112A mutations , Fig . 6 ) . The double mutants R79A+V80A and R94A+I95A situated outside the main binding site caused only a marginal if any decrease in Aly binding . These data corroborate the chemical shift mapping results and analysis of binding of synthetic peptide mutants , indicating that the main REF/Aly interaction site on ORF57 encompass aa 103–120 , and confirms that triad residues W108 , R111 and V112 of ORF57 , in addition to R119 and R120 , are important for the recognition of REF/Aly within the context of the functional full-length protein . Similar co-immunoprecipitation experiments were performed using wild type and mutant forms of full-length ICP27 , specifically mutating W105A , R107A+L108A and W105A+R107A+L108A . Results demonstrate that all three mutants showed a significant reduction in Aly binding , again corroborating data obtained by chemical shift mapping and analysis of binding of synthetic peptide mutants ( Fig . 7 ) . The co-immunoprecipitation experiments for both ORF57 and ICP27 confirm that the REF-binding sites characterized here in detail using shorter polypeptide constructs are also functionally important for the interaction of these proteins with Aly/REF in their full-length native forms . The functional importance of ORF57 residues within REF-binding site were also measured via an ex vivo assay for cytoplasmic accumulation of an HVS ORF47 reporter mRNA ( Fig . 8 ) , using wild type and mutant ORF57 proteins , as previously described [36] , [40] . As such , the cytoplasmic accumulation detected in this assay reflects the ability of ORF57 to form an export competent ribonucleoprotein particle . Human 293T cells were transfected with pORF47 ( a plasmid expressing the late intronless ORF47 mRNA ) in the presence of wild type or mutant ORF57 proteins . After 24 hours RNA was extracted from cytoplasmic fractions and levels assessed by qRT-PCR . The mutation of residues directly implicated in the REF/Aly interaction , namely W108A , R111A+V112A and R119A+R120A , and also W108A+R111A+V112A , all substantially reduced the efficiency of the mRNA cytoplasmic accumulation . In addition , mutations of residues outside the primary REF-binding site were tested . Mutation R94A+I95A also similarly reduced cytoplasmic accumulation , whereas R79A+V80A caused only a marginal decrease . R94 is situated just outside the main REF-binding site and is part of the nuclear localization signal , and the observed effect can be possibly explained by its involvement in the interaction with viral mRNA and/or perturbed nuclear localization . The small effect of R79 substitution may be due to possible changes in mRNA binding . The results of these ex vivo experiments confirm the functional importance of individual residues identified by NMR for specific binding in the context of native Aly and full-length ORF57 . Moreover , the results suggest that these individual residues critical for the HVS ORF57 – REF/Aly interaction are also required to enable efficient cytoplasmic accumulation of viral mRNA in our assay . This confirms the functional significance of ORF57 – REF/Aly interaction for ORF57-mediated nuclear export of viral intronless transcripts , leading to recruitment of other hTREX proteins [40] and TAP .
The use of NMR with short optimised constructs of REF , HSV-1 ICP27 and HVS ORF57 has allowed the precise determination of the residues important for the recognition of viral proteins by the cellular mRNA export factor REF . Despite the lack of obvious sequence similarity , both viral proteins bind on the same main site , along the cleft formed by the two α-helices in the RRM domain of REF . Our data shows that for ICP27 a short but highly specific amino acid sequence 103–110 is required and sufficient for REF-binding ( with residues 105 , 107 and 108 being critical ) . This region is immediately followed by a nuclear localization sequence ( NLS ) aa110-137 [41] , without a significant overlap between the two . Within the ORF57 protein , the REF-interaction sequence is significantly longer and includes aa 103–120 . The REF interaction sites of both ICP27 and ORF57 proteins contain a recognisable triad pattern , a Trp shortly followed by an Arg-Leu/Val pair , which proved to be essential for REF binding . Mutation of these critical triad residues both in ICP27 and in ORF57 significantly reduced binding with REF . The insertion of an additional residue within this triad ( as in the case of ORF57 ) distorts the complementarity of the binding interface and likely necessitates the presence of additional compensating contacts ( i . e . , via R119 and R120 ) and hence a longer recognition site . This is supported by chemical shift mapping , effect of peptide truncation on Kd and a change in REF binding for the R119 , 120A double mutant . The critical REF recognition residues were first identified and characterized in detail using relatively short protein constructs , confirming high specificity of detected interactions . It was however important to show that these REF recognition sites also work in the full-length native proteins . Here we demonstrate that the mutations of residues from recognition triads significantly reduced binding between full-length viral ICP27 and ORF57 and human Aly in co-immunoprecipitation assays , confirming functional significance of detected binding sites for proteins in their native form in nearly physiological conditions , both for ORF57 and ICP27 . The REF recognition site on ICP27 involves residues 103 to 110 ( possibly extended to 112 ) and in our experiments it is entirely sufficient for highly specific binding with REF in vitro . Based on the interpretation of in vivo experiments , recently it had been suggested that phosphorylation of S114 [39] or modifications within the RNA-binding RGG motif aa 138–152 [27] affect the ICP27 interaction with REF . In the structure presented here , S114 is positioned very close to the binding site , but not immobilised upon binding . In principle , one can envisage that phosphorylation of this residue can make an additional favourable Coulombic contact with K133 and/or K136 of REF , immobilizing phosphoserine and strengthening the complex further . We have checked this hypothesis here by using a S114E mutant as a phosphoserine mimic . Both WT-ICP27103–138 and ICP27103–138S114E interact with REF with similar KD , the mutant interacts only marginally stronger ( Table 2 ) . This insignificant change in affinity observed in our experiments and the position at the periphery of the REF-binding motif suggests that it is unlikely that modifications of S114 can provide a direct stringent control of the REF-ICP27 interaction . This agrees with the observation that the S114A mutant still co-immunoprecipitates with REF/Aly [39] . Similarly , the RNA-binding RGG motif ( aa 138–152 ) is positioned sequentially away from the specific REF-binding motif . Modifications in this RGG motif are unlikely to have a direct effect on ICP27-REF binding . The effects of ICP27 modifications outside the main 103–110 site on REF binding recently observed in vivo [27] , [39] can be alternatively explained by trapping the mutated ICP27 in complexes upstream of the pathway , as suggested by [39] . Additionally , modifications within the RGG region of ICP27 may affect binding with RNA; this could indirectly affect ICP27-REF affinity if the RNA bridges the two proteins . Further experiments , which take into account cellular availability of modified ICP27 for interaction with REF/Aly and the bridging role of mRNA , are needed to reconcile the in vivo and in vitro data . Here we have presented the first atomic-resolution structure of the complex between the fragment of archetype viral signature protein , ICP27 , and the cellular export factor REF2-I . The ICP27 peptide binds on the α-helical side of the RRM domain , along the crevice between α-helices . The position of this peptide is defined by the presence of multiple unambiguous NOE contacts , which in particular pinpoint the position of the W105 and L108 of ICP27 ( Fig . S6D and Fig . S7 ) and therefore align the peptide along the crevice . The corresponding 3D structure of human Aly bound to ICP27 is currently unknown , but within the ICP27 binding site the two proteins differ by just one amino acid residue in position 138 , with Phe for Aly and Val for REF2-I . This site is situated on the periphery of the hydrophobic patch which interacts with L108 of ICP27 ( Fig . 5 ) . Comparative modelling of human Aly suggested the mutation could be easily accommodated without disrupting the interaction , therefore the complex between human Aly and ICP27 is likely to be structurally very similar to the one between REF2-I and ICP27 determined here . This modelling provides a molecular level insight into how the ICP27 protein from Herpes Simplex virus may interact with human Aly , to facilitate the nuclear export of herpesviral intronless mRNA , an essential prerequisite for virus replication . The previous examples of peptides bound on the α-helical side of RRM-type domains differ from the structure described here . The U2AF homology motifs ( UHM ) have been shown to recognize a Trp residue which is preceded by a stretch of basic residues [42]–[44] . In the UHM-type of recognition , the signature Trp sidechain of the peptide is inserted into the hydrophobic pocket formed mainly by the looped regions , with the bound peptide running almost perpendicular to the crevice between the two α-helices ( Fig . 4H , I ) . The characteristic Arg-X-Phe motif situated in the loop shortly after α-helix 2 is the defining signature of UHMs and is the key to Trp recognition [43] . The RRM of REF2-I clearly lacks this motif , and therefore does not belong to UHM class . Moreover , the similar hydrophobic pocket in the REF RRM is occupied by Leu108 of ICP27 , and not by Trp ( Fig . 4G–I ) . Interestingly , the presence of the Trp appears not to be as crucial as the other triad residues involved in ICP27 recognition , as its mutation reduces binding only one order of magnitude ( Table 2 ) . Residues more important for ICP27 binding are Arg107 and Leu108 . Unlike in UHM recognition , in the REF - ICP27 complex the Trp makes contacts mainly with the top of α-helix 1 , and middle part of α-helix 2 . Both the abundant NOE contacts ( Figs . S6 and S7 ) and relative perturbations caused by the W105A mutation ( Fig . 3C , D ) , all consistently indicate that the mode of ICP27 binding with REF is different from peptide recognition by UHMs . Recently another apparently similar complex between PTB-RRM2 and Raver1 peptide has been described by NMR and modelling [45] , where a crucial Leu-Leu pair of the LLGxxP motif is inserted in the binding pocket in the loops adjacent to α-helix 2 . In this modelled complex the peptide also has a different orientation , compared with our structure based on direct NOE restraints , and interacting motifs have little similarity . Therefore , the structure presented here displays another , previously undescribed , mode of peptide-RRM recognition , adding to the previously recognized diversity of RRM-ligand interactions [46] . Previously , the position of viral mRNA binding sites on ORF57 has been loosely mapped to aa8-120 [22] , [28] , [29] . As the REF binding site aa103-120 is situated within the same fragment , it is not clear yet whether RNA and REF/Aly binding to ORF57 occurs concurrently or cooperatively . Our further studies are aimed at clarifying this . In the case of ICP27 , the viral mRNA binding site is situated within the RGG region shortly following the REF-binding site . One can therefore anticipate that ICP27 brings and introduces the viral mRNA to REF/Aly , which can bind both ICP27 ( via RRM domain ) and viral mRNA ( via N- and C-termini ) simultaneously , ensuring a multi-contact interaction interface . Here we demonstrated that point mutants in positions 108 , 111 , 112 , 119 and 120 that reduce the ORF57 - REF/Aly interaction also dramatically decrease the ability of ORF57 to promote the nuclear export of intronless viral mRNA . Therefore these residues are functionally important for mRNA export , likely by directly mediating recruitment of REF/Aly . The ability of ORF57 and homologues to interact with export adapter proteins , such as REF/Aly , and possibly functional homologues such as UIF [13] , is therefore likely to be essential for the formation of an export competent ribonucleoprotein particle . This in turn is essential for efficient viral mRNA nuclear export and subsequent virus replication , as we have previously demonstrated that recruitment of the complete hTREX complex to viral intronless mRNAs is essential for both HVS and KSHV lytic virus replication [29] , [35] . Similarly , mutations of ICP27 residues in positions 105 , 107 and 108 have also been shown here to decrease the interaction between full-length ICP27 and human Aly . Further experiments are needed to confirm the effect of mutations of recognition triad residues on the viral mRNA export mediated by ICP27 . The functional role of the REF/Aly binding regions in ICP27 export to the cytoplasm have been studied previously by deletion of polypeptide fragments . Specifically , ICP27 deletions 64–108 ( d2-3 ) and 109–138 ( d3-4 ) were used and interpreted as mutants perturbing interaction with REF/Aly [17] . The current work suggests that in fact only the first of these two deletions affected the REF/Aly recognition triad . In the second d3-4 construct the main REF/Aly binding site was completely preserved , while the NLS was perturbed . This may explain why the d3-4 mutant maintained efficient export of ICP27 to the cytoplasm [17] – the interaction of this construct with REF/Aly was in reality possible . Moreover , the deletion constructs said to be lacking the REF/Aly binding site and used to demonstrate the absence of REF/Aly bridging between ICP27 and TAP/NXF1 [17] , in fact , inadvertently preserved this site . In view of the detailed data presented here on the exact point mutations ( residues 105 , 107 and 108 ) which will perturb interactions with REF/Aly without affecting the NLS aa110-137 , further functional studies may be warranted to reconsider the suggested diminished roles of the ICP27 - REF/Aly interaction in cytoplasmic export of ICP27 , and of REF/Aly in mediating interactions with TAP/NXF1 [17] . Such studies however should consider the possibility that other adaptor proteins [12]–[14] may substitute the function of REF/Aly in vivo once the ICP27 – REF/Aly interaction is blocked , complicating the analysis . Additional experiments are also required to assess and map interaction of ICP27 with functional homologues of REF/Aly such as the recently identified UIF protein [13] , to explore the role of alternative pathways . Regardless of how essential the REF-viral protein interaction appears from siRNA evidence [14] , the recruitment of the ubiquitously-present cellular export factor Aly/REF to viral ICP27/ORF57 can be envisaged as a highly useful pathway linkage , increasing an overall efficiency of viral mRNA export , due to the ability of this export factor to remodel TAP triggering high affinity RNA - TAP interactions [10] . The main interaction site for TAP on REF is an N-terminal arginine rich motif; however , the REF RRM also contributes to TAP interactions [10] , [33] and this secondary site overlaps with the site recognised by ICP27 and ORF57 . Therefore TAP recruitment is likely to lead to remodelling of the viral ribonucleoprotein complex . Although the partial displacement of the viral adaptor fragment from the surface of RRM of REF upon TAP binding may be possible , the complete displacement of the viral proteins from the ribonucleoprotein complex seems unlikely since a ternary complex of REF - TAP and ORF57/ICP27 assembles in vitro [19] , [22] . Further studies are required to establish how the viral mRNA export complex is remodelled during export and which proteins contact the viral mRNA directly at each point in the export pathway .
Constructs REF1–155 , REF54–155 , ICP271–138 and ORF578–120 , expressed in pET24b ( Novagen ) vector , were produced as described previously [33] , with additional purification on a Superdex 75 ( GE Healthcare ) column ( GF buffer: 20 mM phosphate , 150 mM NaCl , 50 mM L-Arg/L-Glu/β-mercaptoethanol and 10 mM EDTA , pH 6 . 2 ) . Proteins SF2 and 9G8 were purified as described previously [37] , [38] . ICP27103–138 WT and S114E peptides were expressed as GST-fusions in a pGEX-6P-1 plasmid , and cleaved by PreScission protease on GSH resin according to standard protocol ( GE Healthcare ) . Eluted peptide was supplemented with 5 mM DTT and protease inhibitor cocktail ( Roche ) , and exchanged into GF buffer using an Amicon pressure cell with 1 k MWCO membrane via a series of dilutions/concentrations . A Sephacryl S-100 HR ( GE Healthcare ) gel filtration column was used to purify the peptide further . Peptide was >95% pure according to tricine-SDS-PAGE . GST or GST protein fusions were first immobilised on 30 µl slurry glutathione-coated beads ( GE Healthcare ) before 8 µl 35S-radiolabelled proteins synthesised in rabbit reticulocytes ( Promega ) were added to the binding reactions in RB100 buffer ( 25 mM HEPES pH 7 . 5/100 mM KOAc/10 mM MgCl2/1 mM DTT/0 . 05% Triton X-100/10% glycerol ) in presence of 10 µg/ml RNAse A . Washed and eluted protein complexes were resolved on 15% SDS-PAGE stained with Coomassie blue and analysed by PhosphoImage . To analyse the effect of HVS ORF57 and HSV-1 ICP27 point mutations on Aly/REF binding , co-immunoprecipitation were performed as previously described [47] , [48] . Human 293T cells were transfected with wild type GFP-ORF57 or GFP-ICP27 and respective mutants , generated using the QuickChange II site-directed mutagenesis kit ( Stratagene ) , using Lipofectamine 2000 ( Invitrogen , Paisley , UK ) , as per the manufacturer's instructions . Briefly , after 24 hours , cell lysates were harvested , precleared with Protein A agarose for 1 hour at 4°C and then incubated with polyclonal GFP-specific antibody for 2 hours at 4°C . Protein A agarose was added to the cell lysates and incubated for a further 3 hours at 4°C . The agarose was washed 3 times to remove unbound protein . Western blot analysis was then performed using an Aly-specific antibody and GFP-specific monoclonal antibody as a loading control . Densitometry analysis was then performed on 3 independent experiments using the ImageJ software . 293T cells were transfected with ORF57 or the respective mutants in the presence of the pORF47 reporter mRNA as previously described [49] . Cytoplasmic ORF47 mRNA levels were then assessed by qRT-PCR as previously described [36] . Briefly , after 24 hours , cells were lysed in 200 µl of PBS 1% Triton-X 100 ( v/v ) containing 40 U of RNAse Out ( Invitrogen ) , and cytoplasmic fractions isolated using Trizol ( Invitrogen ) as previously described [36] . Total RNA ( 1 µg ) from each fraction was reverse transcribed using Superscript II ( Invitrogen ) and 10 ng of cDNA used as template in SensiMixPlus SYBR qRT-PCR reactions ( Quantace ) . qPCR was performed using the Rotor-Gene Q 5plex HRM Platform ( Qiagen ) , with a standard 3-step melt program ( 95°C melt for 30 sec , 60°C annealing for 15 secs , 72°C extension for 20 secs ) . Following confirmation that qPCR efficiency was comparative between ORF47 and the reference mRNA ( GAPDH ) , quantitative analysis was performed using ΔΔcT analysis as previously described [36] . All experiments were carried out at 30°C on Bruker DRX600 , DRX700 and Varian Inova 800 MHz spectrometers equipped with cryoprobes . The weighted chemical shift changes of amide signals δCS caused by complex formation were measured as , where ΔδH and ΔδN were changes in proton and nitrogen chemical shifts , respectively . Standard triple-resonance experiments were used to assign spectra of ICP27103–138 , ORF578–120 and REF54–155 in their free and bound states . Additionally , carbon-detection experiments ( CON , CaCO , CbCaCO , CbCaCO ( N ) , CbCaNCO ) were used as an aid to the ORF57 assignment . Spectra were processed using NMRpipe [50] and Topspin 2 . 1 ( Bruker ) and analysed using Sparky ( University of California ) . Distance restraints obtained from 3D 15N- and 13C edited NOESY-HSQC experiments ( τm 120 ms ) and dihedral restraints from TALOS [51] were used in structure calculations by CYANA [52] . Additionally , intermolecular contacts were unambiguously identified using 13C edited , 12C-filtered NOESY-HSQC ( τm 150 ms ) spectra acquired on Varian Inova 800 MHz spectrometer . In this experiment only NOE crosspeaks between 1H-13C moieties of 13C , 15N-labelled REF and 1H ( 12C ) of unlabelled ICP27 peptide were observed [53] , [54] . A final ensemble contained 20 structures with lowest target function values . Images were generated using Pymol ( DeLano Scientific ) . For the REF - ICP27 complex , structure coordinates and experimental constraints have been deposited into the Protein Data Bank and chemical shifts in the BioMagResBank ( access numbers 2kt5 and bmr16683 respectively ) . Other chemical shift assignments deposited in the BioMagResBank are: free ICP27103–138 bmr16696 , free REF54–155 bmr16697 , and ORF578–120 bmr16698 ( both free and bound to REF54–155 ) . Unlabelled synthetic peptides were obtained from Peptide Protein Research Ltd ( UK ) . The synthetic peptide sequences used were from Varicella-zoster virus ORF4108–119 ( AAY57694 ) , Kaposi's sarcoma-associated herpesvirus ORF57100–110 ( YP_001129410 ) , Herpesvirus Saimiri ORF57103–120 & 105–115 ( CAC84353 ) , Herpes simplex virus 1 ICP27103–110 & 103–112 ( AAF43147 ) . Dissociation constants ( KD ) were derived by monitoring chemical shift changes in 1H-15N correlation spectra of 100 µM 15N-REF54–155 as a function of increasing peptide concentrations , and fitting data to the standard equation [55] . For very weak binding peptides where chemical shift changes were too small to obtain a curve for fitting , a lower limit estimate of KD was obtained by comparisons of the magnitude of chemical shift change observed relative to those of stronger complexes . Comparative modelling of the human Aly – ICP27 complex was performed using Swiss-PdbViewer [56] and the lowest energy conformer of the REF - ICP27 complex as a template . Mutations A75G , D107H , D119N , R125K , K136N , V138F and D146N ( which reflect the differences between murine REF2-I and human Aly within the RRM domain ) were introduced . All mutations except V138F involved solvent exposed sites and did not cause steric clashes . For the V138F substitution , a conformation was chosen that minimised the number of steric clashes while orientating the aromatic sidechain towards the hydrophobic core of REF . An energy minimization was conducted to remove the remaining steric clash with the ε-methyl of M145 , resulting in a change in the M145 side chain rotamer , and virtually no movement of the backbone ( heavy atom backbone RMSD of 0 . 04 Å ) .
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When invading host cells , herpes viruses highjack cellular components to allow them to replicate . It has been long recognized that each herpes virus has a specific signature adaptor protein which , among other functions , inserts viral mRNA into the cellular mRNA nuclear export pathway , enabling production of viral proteins by the host cell . This process has been extensively studied in vivo and in vitro , but despite many efforts , the molecular and structural mechanisms of key interactions between viral adaptors and cellular mRNA export factors have not been described . Here we present the first atomic-resolution structure of the key complex between the archetypal viral adaptor ICP27 ( from Herpes simplex virus 1 ) and the cellular mRNA export factor REF , responsible for introducing viral mRNA into the cellular nuclear export pathway . We demonstrate that despite the absence of obvious sequence similarity , the adaptor protein ORF57 from a different herpes virus ( Herpesvirus saimiri ) binds REF in the same site and in a similar way . We have identified and studied amino acid residues responsible for REF recognition . Together the data provide the first molecular insight into how herpesviral signature proteins recognize cellular proteins , obtaining access to the cellular mRNA export machinery .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Materials",
"and",
"Methods"
] |
[
"computational",
"biology/macromolecular",
"structure",
"analysis",
"biophysics/macromolecular",
"assemblies",
"and",
"machines",
"molecular",
"biology/rna-protein",
"interactions",
"biochemistry/experimental",
"biophysical",
"methods",
"biophysics/biomacromolecule-ligand",
"interactions",
"molecular",
"biology/mrna",
"transport",
"and",
"localization",
"biochemistry/biomacromolecule-ligand",
"interactions",
"biochemistry/macromolecular",
"assemblies",
"and",
"machines"
] |
2011
|
Structural Basis for the Recognition of Cellular mRNA Export Factor REF by Herpes Viral Proteins HSV-1 ICP27 and HVS ORF57
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Genotype-phenotype relationships can vary extensively among members of a species . One cause of this variation is circuit diversification , the alteration of gene regulatory relationships among members of a species . Circuit diversification is thought to be a starting point for the circuit divergence or rewiring that occurs during speciation . How widespread is circuit diversification ? Here we address this question with the fungal pathogen Candida albicans , which forms biofilms rich in distinctive hyphal cells as a prelude to infection . Our understanding of the biofilm/hyphal regulatory network comes primarily from studies of one clinical isolate , strain SC5314 , and its marked derivatives . We used CRISPR-based methods to create mutations of four key biofilm transcription factor genes–BCR1 , UME6 , BRG1 , and EFG1 –in SC5314 and four additional clinical isolates . Phenotypic analysis revealed that mutations in BCR1 or UME6 have variable impact across strains , while mutations in BRG1 or EFG1 had uniformly severe impact . Gene expression , sampled with Nanostring probes and examined comprehensively for EFG1 via RNA-Seq , indicates that regulatory relationships are highly variable among isolates . Our results suggest that genotype-phenotype relationships vary in this strain panel in part because of differences in control of BRG1 by BCR1 , a hypothesis that is supported through engineered constitutive expression of BRG1 . Overall , the data show that circuit diversification is the rule , not the exception , in this biofilm/hyphal regulatory network .
Each species has broad properties that define its members , yet individuals present diversity that reflects the events of their lineage . Although some phenotypic differences between individuals arise from single allelic differences or gene acquisitions , the vast majority represent the interplay of multiple genetic and epigenetic differences [1 , 2 , 3] . Natural variation has been measured through assays of biological phenotypes such as fitness , disease susceptibility , or cellular differentiation , and through molecular phenotypes such as the expression of sets of genes . The impact of natural variation is also manifested in genetic background effects on the phenotypes of defined mutations . Comparison of large scale gene knock-out or knock-down collections in pairs of Saccharomyces cerevisiae [4 , 5] and Caenorhabditis elegans [6] strains has shown that genetic background effects are widespread , affecting single gene loss-of-function phenotypes for up to 20% of genes . The implication of such studies , as proposed by Gasch and colleagues , is that network relationships between genes may vary considerably among representatives of the same species [7] . The clearest example to date in fungi of species-level natural variation in network architecture comes from Chin et al . , who studied adherence in two strains of S . cerevisiae [8] . A MAP Kinase pathway ( fMAPK ) is required for adherence and expression of the adhesin gene FLO11 in strain Σ1278b but not in strain S288c . Crosses between the strains indicated that the regulation of fMAPK-dependence is genetically complex , though a cloning-based rescue strategy defined one modifier locus , RPI1 , that specifies a transcription factor . Rpi1 can bypass the fMAPK pathway through its ability to bind to the 5' region of FLO11 , an ability enabled by the RPI1 allele of S288c and abolished by the RPI1 allele of Σ1278b [8] . Therefore , these two representatives of the same species rely upon distinct signaling pathways—either an fMAPK-dependent pathway or an Rpi1-dependent pathway—to control expression of FLO11 and , ultimately , adherence [8] . Chin et al . hypothesized that the natural variation in regulatory relationships that they observed within a species , which they call "circuit diversification , " is a precursor to the evolutionary rewiring and circuit divergence that is observed between species . How prevalent is circuit diversification among members of a species ? What is the extent of its impact ? Here we use the fungal pathogen Candida albicans to address these questions . We focus on two well characterized virulence traits: its ability to grow as hyphae and to produce a biofilm [9 , 10] . Hyphae are tubular arrays of cells that can be hundreds of microns in length , and hypha-associated genes specify adhesins , hydrolases , and the toxin Candidalysin that together cause tissue damage [10 , 11] . Biofilms are multicellular surface-bound communities that produce an extracellular matrix and are recalcitrant to antimicrobial treatment [12] . Biofilms of C . albicans are rich in hyphae , and genetic studies indicate that biofilm production depends upon hyphae in vitro and in animal infection models [12] . Biofilm formation is connected to virulence because biofilm on implanted medical devices is a major source of infection [12] . Our understanding of C . albicans biofilm formation comes primarily from studies of one clinical isolate , strain SC5314 , and its derivatives CAI-4 , BWP17 , and SN152 , whose markers facilitate genetic manipulation . Among the most well characterized biofilm regulators are the transcription factors ( TFs ) Efg1 , Bcr1 , Ume6 , and Brg1 ( [13 , 14 , 15 , 16 , 17 , 18]; reviewed in [19] ) . A deletion mutation affecting any one can cause a biofilm defect , depending upon the precise growth conditions . All four TFs are also required under many conditions for normal hyphal formation , expression of hypha-associated genes , and virulence in animal models . These TFs are interconnected through their control of overlapping sets of target genes and of one another's expression [19] . Because biofilm production and hyphal formation have been extensively characterized , this network provides a valuable starting point for an appraisal of natural variation . Uniform network architecture may prevail among C . albicans isolates , or circuit diversification may prevail . We test these possibilities through analysis of four different single gene deletion mutations in five different C . albicans clinical isolates . Our results show that the gene expression impact of regulatory network defects is highly variable among strains , and thus argue that circuit diversification is widespread .
Our studies employed five C . albicans clinical isolates: SC5314 ( clade 1 ) , P76067 ( clade 2 ) , P57055 ( clade 3 ) , P87 ( clade 4 ) , and P75010 ( clade 11 ) [20 , 21] . SC5314 is a dermatological isolate and is the standard laboratory strain for most molecular and genetic studies; P76067 , P57055 , and P75010 are bloodstream isolates; P87 is an oral isolate . These strains were chosen to represent the major clades of clinical isolates and thus to capture the range of genetic diversity . Biofilm production was assayed at the end of a 24 hr incubation in RPMI+serum medium at 37 degrees . These conditions induce biofilm formation strongly in strain SC5314 ( Fig 1 , left column , and S1 Fig ) . Biofilm depth , visualized by confocal microscopy , was substantial for strains SC5314 and P76067 , intermediate for strains P57055 and P87 , and minimal for strain P75010 ( Fig 1 , left column , and S1 Fig ) . These results indicate that biofilm production varies among this set of isolates . Confocal imaging was used to assay for presence of hyphae in biofilms . Side-view ( Fig 1 , left column ) and apical ( Fig 2 , left column ) confocal projections revealed presence of abundant hyphae in the four strong and intermediate biofilms . No hyphae were evident in the minimal biofilm produced by strain P75010 . These results are consistent with the conclusion from extensive mutant analysis in the strain SC5314 background that hyphal formation is required for biofilm formation [19] . We also assayed hyphal formation by each strain under planktonic growth conditions ( 4 hr , RPMI+serum medium , 37 degrees ) . The strong and intermediate biofilm formers produced abundant long hyphae ( Fig 3 , left column ) . The intermediate biofilm forming strain P57055 produced slightly unusual hyphae; many had bends at ~20 micron intervals . The minimal biofilm forming strain P75010 yielded infrequent hyphae under these conditions . Quantitative measurements confirmed these qualitative impressions: hyphae were less abundant , and hyphal unit cell lengths were smaller , in strain P75010 than in the strong and intermediate biofilm formers ( S2 Fig ) . These assay results indicate that production of planktonic hyphae correlates with production of biofilm hyphae in this panel of strains . To assess natural variation in genetic control over biofilm production , we created deletion mutations for each of the biofilm regulatory genes BCR1 , UME6 , BRG1 , and EFG1 in all five strains . Mutants were assayed for biofilm production under RPMI+serum growth conditions . A bcr1Δ/Δ mutation had little impact under these conditions on biofilm production by the two strong biofilm formers , strains SC5314 and P76067: mutant biofilm depth ( Fig 1 ) and hyphal content ( Fig 2 ) were comparable to those of the respective wild-type strains . However , we noted regional separation of the basal and upper biofilm layers in these mutants ( Fig 1 ) . In contrast , a bcr1Δ/Δ mutation impaired biofilm production by the two intermediate biofilm formers , strains P57055 and P87: biofilm depth and hyphal content were severely reduced ( Figs 1 and 2 ) . A bcr1Δ/Δ mutation had little effect on the weak biofilm former , strain P75010 ( Figs 1 and 2 ) . Pannanusorn et al . , in pioneering studies of a set of Candida parapsilosis clinical isolates , also observed that impact of bcr1Δ/Δ mutations was highly strain-dependent in that species [22] . Our results indicate that BCR1 is dispensable for biofilm production in some C . albicans strain backgrounds and essential for biofilm production in others . A ume6Δ/Δ mutation had broad effects on biofilm production: it caused a partial or severe impairment in all of the strong and intermediate biofilm former backgrounds . Biofilm depth ( Fig 1 ) and hyphal content ( Fig 2 ) were reduced . Biofilm disruption by the ume6Δ/Δ mutation was particularly severe in the intermediate biofilm former P57055 , perhaps due to the absence of biofilm hyphae ( Fig 2 ) . A ume6Δ/Δ mutation had little measurable effect on the weak biofilm former P75010 ( Figs 1 and 2 ) . These results show that Ume6 functional impact varies with strain background , as is the case with Bcr1 . Both brg1Δ/Δ and efg1Δ/Δ mutations caused severe impairment of biofilm production in the strong and intermediate biofilm formers . Biofilm depth was reduced to ~20 microns ( Fig 1 ) , and hyphal content was nearly or entirely eliminated ( Fig 2 ) . The mutations had little effect on the already weak biofilms formed in the strain P75010 genetic background . These results show that Brg1 and Efg1 have broad functional impact on phenotype that varies minimally with strain background . We also assayed the effect of each mutation on production of planktonic hyphae . The results ( Fig 3 and S3 Fig ) correlated generally with production of biofilm hyphae ( Fig 2 ) . Reconstituted derivatives of all mutants , in which one or two copies of the deleted gene were re-introduced , regained hyphal formation ability comparable to the respective wild-type strains ( S4 Fig ) . Interestingly , P75010 derivatives that carried the BRG1 and EFG1 alleles from SC5314 displayed increased hyphal production compared to P75010 ( S4 and S5 Figs ) . These results support the conclusion that the magnitude of impact on phenotype of several of the transcription factors varies with strain background . Results above indicate that several biofilm regulatory mutations vary in phenotypic severity among the clinical isolates . To explore this conclusion at the level of gene expression , we conducted Nanostring profiling of each wild-type and regulatory mutant strain . Growth conditions were identical to those for the hyphal induction assays . RNA levels were measured for 181 genes , including 60 genes that have been connected through function or expression to hyphae or biofilms . RNA levels in each mutant were compared to the respective wild type in order to calculate fold changes ( S1 Table ) . The results revealed that gene regulatory relationships are strongly contingent upon strain background . One indication of regulatory variation across strains comes from a count of the number of significantly up- or down-regulated genes in each mutant strain compared to their respective wild-type strains ( Table 1 ) . For example , in the SC5314 strain background , there were 23 genes whose RNA levels were altered significantly ( ≥2-fold , FDR = 0 . 1 ) by a bcr1Δ/Δ mutation . In the P57055 background , there were 58 genes whose RNA levels were altered significantly by a bcr1Δ/Δ mutation . Across all backgrounds , only 12 genes responded consistently to a bcr1Δ/Δ mutation ( "Common" column , Table 1 ) . The overall lack of concordance presented by bcr1Δ/Δ mutations was recapitulated by the other mutations: the number of responsive genes varied by a factor of 2 among strain backgrounds , and the number of shared responsive genes ( "Common" ) was fewer than half of the number of responsive genes in any background . A similar outcome was observed if only the criterion of an FDR = 0 . 1 was applied without a fold-change requirement ( S2 Table ) . These results indicate that there is substantial variation in regulatory relationships within the C . albicans species . Extensive variation is also seen in the architecture of the biofilm/hyphal regulatory network defined by the mutants and their gene expression impact ( Fig 4 ) . Some genes that are annotated to hyphal formation , such as CHT2 and SOD5 , varied considerably with respect to strain background in their dependence on specific TFs ( Fig 5 ) . The variable response of CHT2 was particularly noteworthy because its 5' region is bound by Bcr1 and Brg1 as shown by overlapping binding peaks centered approximately 2250 bp upstream of the start codon [16] , an indication that it is a direct target of those two TFs . Interestingly , among all five isolates , no SNPs were identified in Bcr1 and Brg1 motifs in this region . An additional illustration of network variation comes from the regulation of the TF genes BRG1 and UME6 ( Figs 4 and 5 ) . In the two strong biofilm formers , SC5314 and P76067 , Bcr1 is not required for expression of BRG1 and UME6 . In the intermediate and weak biofilm formers , Bcr1 is required for expression of both BRG1 and UME6 . These dependency relationships provide a possible explanation for the greater impact of the bcr1Δ/Δ mutation on gene expression and biological phenotypes in the intermediate biofilm formers than in the strong biofilm formers ( Table 1; Figs 1–3 ) . Overall , these results indicate that regulatory network architecture is strongly contingent upon strain background . In addition , the observation that many genes are dependent upon a TF in one strain background but not another is evidence for circuit diversification among these strains . We distilled gene expression changes into a common network of regulatory relationships that are shared among all five strains ( Fig 4; S1G Table ) . In the 181 assayed genes , 60 were annotated to GO terms related to hyphae or biofilm . Compared to regulatory relationships determined solely in SC5314 , a larger proportion of the relationships defined by this common network were with these hyphae or biofilm annotated genes ( p = 0 . 014 , Fisher's exact test ) . The common network also trended toward enrichment for direct targets of the TFs ( p = 0 . 083 compared to SC5314 , Fisher's exact test ) as defined by ChIP-Seq experiments [16 , 23] . These observations suggest that the common target genes found in diverse strains may give clearer functional insight into their regulators than the target genes found in any one strain . For a genome-wide view of regulatory relationships among strains , we carried out RNA-Seq analysis of the five clinical isolates and their efg1Δ/Δ derivatives ( S3 Table ) . Each clinical isolate was compared with its corresponding efg1Δ/Δ mutant in order to define Efg1-responsive genes . The gene expression impact of the efg1Δ/Δ mutation varied considerably among clinical isolates ( Table 2 ) . The number of Efg1-responsive genes ranged from 523 ( P76067 ) to 864 ( SC5314 ) . Approximately 15–27% of the genes that responded to Efg1 in any one strain did not respond in any of the other four strains ( Fig 6B ) . Many additional genes were Efg1-responsive only in a subset of genetic backgrounds ( Fig 6B ) . Overall , these genome-wide data support the concept that gene expression targets vary considerably among C . albicans species representatives , and indicate that circuit diversification frequently affects Efg1 target genes . Gene expression profiles converged on 177 core Efg1-responsive genes ( 21–34% of total ) that were up- or down-regulated in efg1Δ/Δ mutants of every strain background ( Fig 6B ) . These core Efg1-responsive genes included 138 Efg1-activated genes ( i . e . , down-regulated in efg1Δ/Δ mutants ) and 39 Efg1-repressed genes ( i . e . , up-regulated in efg1Δ/Δ mutants ) . Core Efg1-activated genes were enriched for the GO term biofilm formation ( p = 4 . 86e-07 ) ( Fig 6A and 6C; S4 Table ) . This enrichment was greater than observed with the Efg1-activated genes of any individual strain ( Fig 6A and 6C; S4 Table ) . Core Efg1-repressed genes were enriched for GO terms that include cell surface ( p = 6 . 94e-07 ) and cell wall ( p = 6 . 78e-07 ) ( S4 Table ) . This enrichment was comparable to that observed with individual strains . We found that 24% of core Efg1-responsive genes were direct Efg1 targets , based on chromatin immunoprecipitation data [16 , 23] , whereas 16–22% of Efg1-responsive genes in individual strains were direct targets ( Table 2 ) . Compared to the proportion of direct targets among all SC5314 Efg1-responsive genes , the proportion of direct targets among core Efg1-responsive genes was greater ( p = 0 . 036 , Fisher's exact test ) , though it only trended toward greater in comparisons to some other strains . Overall , these observations indicate that core Efg1-responsive genes align well with what is known about Efg1 function . The Efg1-activated genes of several strains were enriched for carbohydrate metabolic functions ( Fig 6A and 6C , S6 Fig ) , which are mainly glycolytic genes , as expected from prior studies [24] . However , there was no enrichment for these functions in the core Efg1-activated gene set . Their exclusion from core genes is based on properties of one strain , P76067 . Examination of individual gene expression responses shows that these genes display less dependence on Efg1 for expression in strain P76067 compared to the other strains ( S3 Table ) . Therefore , the impact of Efg1 on carbohydrate metabolic genes behaves as a quantitative trait among C . albicans isolates . The unique Efg1-responsive genes in each strain ( S3 Table ) ranged from 97 ( strain P57055 ) to 234 ( strain SC5314 ) . They were roughly split between Efg1-activated and -repressed genes ( Fig 6B ) . We found only minor enrichments for GO terms among most of these gene sets , and no significant enrichment at all among the SC5314 strain-specific Efg1-responsive genes . Although these genes do not share distinguishing GO assignments , there are prospective functionally relevant genes among them . For example , the SC5314 efg1Δ/Δ mutation leads to significantly reduced expression of SUN41 , which is required for biofilm formation [25 , 26] . Therefore , strain-specific Efg1-responsive genes may contribute to the mutant phenotype , but they do not reveal broad pathways that respond to Efg1 in a strain-specific manner . The BCR1-BRG1 relationship provides a simple illustration of circuit diversification: BCR1 is required for BRG1 expression in intermediate but not strong biofilm formers ( Figs 4 and 5 ) . We hypothesized that this regulatory difference was the reason that BCR1 is required for biofilm production by intermediate but not strong biofilm formers under our assay conditions . Specifically , reduced BRG1 expression may contribute to the biofilm defect of bcr1Δ/Δ mutants in intermediate biofilm formers , while constitutive BRG1 expression may permit biofilm production by bcr1Δ/Δ mutants in strong biofilm formers . This hypothesis predicts that constitutive BRG1 expression will permit biofilm production in a bcr1Δ/Δ mutant in an intermediate biofilm former . We tested this hypothesis with strain P57055 , an intermediate biofilm former that transforms efficiently . We fused one allele of BRG1 with the TDH3 promoter in P57055 BCR1/BCR1 BRG1/BRG1 and bcr1Δ/Δ BRG1/BRG1 strains to create BRG1/TDH3-BRG1 derivatives . We then compared four strains of genotypes BCR1/BCR1 BRG1/BRG1 , bcr1Δ/Δ BRG1/BRG1 , BCR1/BCR1 BRG1/TDH3-BRG1 , and bcr1Δ/Δ BRG1/TDH3-BRG1 . Using Nanostring , we confirmed that BRG1 RNA levels were Bcr1-dependent in the BRG1/BRG1 strains and Bcr1-independent in the BRG1/TDH3-BRG1 strains ( Fig 7A ) . Although the TDH3 promoter is often used for overexpression , in this case it did not yield greatly elevated BRG1 expression . As predicted by the hypothesis , biofilm production was also Bcr1-dependent in the BRG1/BRG1 strains and Bcr1-independent in the BRG1/TDH3-BRG1 strains ( Fig 7C ) . As a further functional test of the hypothesis , we examined planktonic hyphal formation . In the P57055 background , the bcr1Δ/Δ mutant had reduced length of hyphal cell compartments and a reduced ratio of hyphae to yeast cells ( Fig 7B and 7D ) . In the P57055 BRG1/TDH3-BRG1 derivatives , the bcr1Δ/Δ mutant did not display these phenotypes ( Fig 7B and 7D ) . Therefore , the phenotypic impact of a bcr1Δ/Δ mutation in the P57055 background depends upon the BCR1-BRG1 regulatory relationship . What is the mechanism behind divergent dependence of BRG1 expression on Bcr1 ? One hypothesis is that the cis regulatory elements of BRG1 alleles may contain SNPs that allow Bcr1-independent BRG1 expression in some strains but not others . We tested this hypothesis by constructing P57055 bcr1Δ/Δ mutant strains carrying BRG1SC5314 or BRG1P57055 alleles at the MDR1 locus . These alleles contained 1642 bp of the BRG1 upstream region and 712 bp of the BRG1 downstream region . Ectopic expression of BRG1SC5314 and BRG1P57055 in this manner complemented the hyphal formation defect of a P57055 brg1Δ/Δ mutant strain , demonstrating that the cis contexts captured in these regions were sufficient for BRG1 expression and function ( S7A Fig ) . However , ectopic expression of BRG1SC5314 or BRG1P57055 in the P57055 bcr1Δ/Δ mutant failed to rescue hyphal formation ( S7B Fig and S5 Table ) . Furthermore , strains expressing BRG1SC5314 were not significantly different from strains expressing BRG1P57055 in hyphal formation capacity . We conclude then that the cause of Bcr1-independent BRG1 expression in SC5314 does not lie solely in cis regulatory element SNPs carried in these allelic segments .
Our studies address whether genetic regulatory relationships are uniform within the species C . albicans . We approached the problem through measurement of biological phenotypes and gene expression changes that result from mutations in each of four TF genes in the biofilm/hyphal regulatory network . Two of the TF gene mutations , bcr1Δ/Δ and ume6Δ/Δ , had variable phenotypic impact among the strains . These mutations also had variable gene expression impact; an outcome that might have been predicted from phenotypic variation . The other two TF mutations , brg1Δ/Δ and efg1Δ/Δ , had uniform phenotypic impact , yet still had highly variable gene expression impact . These observations argue that circuit diversification–variation in regulator-target relationships within a species–is prevalent for this biofilm/hyphal regulatory network . The traits we examined , biofilm production and hyphal formation , are known to vary quantitatively among C . albicans isolates [20 , 21 , 27 , 28 , 29] . Hence it seemed reasonable that gene expression impact of key biofilm/hyphal regulators would vary as well . We were nonetheless struck by the extent of strain-specific gene expression changes we observed; only about half of the gene expression response to a mutation in any one strain was shared among the other four strains . The fact that even the mutation with the strongest and most uniform biological phenotypes , efg1Δ/Δ , caused variable gene expression impact across strains is especially noteworthy , because large scale dual-strain comparisons of loss-of-function defects have relied on biological phenotypes [4 , 5 , 6] . Our results argue that biological phenotype measurements may underestimate the difference in impact of a mutation in two different strains . What sorts of variation do we see in TF-target gene relationships ? Regulation of SOD5 , BRG1 , and UME6 ( Fig 5 ) represents one frequent pattern: expression of each is down-regulated in a mutant , such as bcr1Δ/Δ , in some strains but not others . Analogous observations were made with expression of S . cerevisiae FLO11 and its control by the fMAPK pathway by Chin and colleagues [8] . The regulation of CHT2 is more complex , for example in its response to Efg1 . It is up-regulated in an efg1Δ/Δ mutant in SC5314 , as shown previously [30] , but it is down-regulated in efg1Δ/Δ mutants of other strains . Efg1 is known to function as an activator at some promoters and a repressor at others [31 , 32] in strains derived from SC5314 . However , our results raise the possibility that Efg1 may function as a repressor or an activator at a single promoter , depending upon the strain background . These examples illustrate strain-dependent differences in TF-target gene relationships that are indicative of circuit diversification . Variation in biofilm/hyphal network architecture has clear functional impact , as illustrated by strain differences in the BCR1-BRG1 relationship . A bcr1Δ/Δ mutation had little effect on biofilm production or BRG1 expression in two strong biofilm formers , and caused a severe defect in both biofilm production and BRG1 expression in two intermediate biofilm formers . Because BRG1 was required for biofilm production in all strains , we considered that differences in BCR1-dependence of biofilm production may arise from differences in BCR1-dependence of BRG1 expression . This hypothesis was supported by the finding that constitutive BRG1 expression eliminated BCR1-dependence of biofilm production in an intermediate biofilm former . Prior studies have shown that Bcr1 and Brg1 have considerable functional overlap: among 252 direct Bcr1 target genes identified by ChIP-seq , 194 are Brg1 direct targets as well [16] . Overlap of target genes may be the reason that BCR1 is required for biofilm formation only when BRG1 levels are low . We cannot find strain differences in the Bcr1 binding sites upstream of BRG1 . Furthermore , cis-regulatory elements of the BRG1SC5314 allele were not sufficient for BRG1 function in the P57055 bcr1Δ/Δ mutant strain . We infer that variation in the BCR1-BRG1 relationship arises from differences in trans-acting factors that can compensate for absence of Bcr1 . This inference is consistent with the conclusion from many studies the bulk of gene expression variance between individuals arises from differences in trans-acting gene products [1] . Glycolytic genes provide an example of a functionally related group of genes that vary in strength of connection to biofilm regulator Efg1 ( Fig 6 , S6 Fig ) . In most strains , the efg1Δ/Δ mutation caused a severe reduction in glycolytic gene expression . In contrast , in strain P76067 the efg1Δ/Δ mutation caused a mild reduction in glycolytic gene expression . Inspection of the RNA-Seq data shows that expression of GAL4 , an activator of glycolytic genes [33] , is strongly reduced in most efg1Δ/Δ mutants but only mildly reduced in the P76067-derived efg1Δ/Δ mutant . Efg1 does not bind directly to the GAL4 upstream region [16 , 23] . Therefore , this example of circuit diversification also seems to arise from differences in activity of trans-acting factors that , in this case , compensate for absence of Efg1 . Our data provide the first view of C . albicans natural variation from the perspective of gene expression profiles , and several manifestations of strain variation are evident . For example , compared to SC5314 , all isolates had significantly increased RNA levels for various cell wall-related genes ( S6C Table ) . Also , higher BCR1 and BRG1 RNA levels among isolates correlate with lower RNA levels for ribosome-related genes ( S6A Table ) . These correlations may reflect natural variation in TOR pathway activity , which is known to promote ribosome biogenesis and inhibit Bcr1-dependent adhesin expression [34] . Although high resolution trait mapping is not yet feasible for C . albicans , a candidate gene-based approach could unravel the causes for these strain differences and their functional consequences . A valuable practical application of multi-strain analysis is the distillation of a common set of genetic regulatory relationships . This outcome was suggested by our small-scale Nanostring profiling , but was most clearly documented through genome-wide analysis of Efg1-responsive genes . Specifically , the common Efg1-activated gene set was significantly enriched for biofilm-related genes , and trended toward enrichment for direct Efg1 target genes , compared to any individual strain's Efg1-activated genes . The common Efg1-repressed gene set was enriched for cell-surface related genes , an enrichment that was not found among Efg1-repressed gene sets for individual strains . These outcomes argue that multi-strain analysis of mutants is significant both for the validation of conclusions across multiple species representatives , and for its ability to narrow a panel of responsive genes to those with a strong connection to relevant biological processes .
The following C . albicans clinical isolate strains were obtained through BEI Resources , NIAID , NIH: Candida albicans , Strain P76067 , NR-29442; Candida albicans , Strain P57055 , NR-29439; Candida albicans , Strain P87 , NR-29453; Candida albicans , Strain P75010 , NR-29437 . All strains and mutants were maintained in 15% glycerol stocks stored at -80°C . Prior to all experiments , strains were grown on YPD ( 2% Bacto Peptone , 2% dextrose , 1% yeast extract ) for 2 days at 30°C , and then cultured overnight in liquid YPD at 30°C with shaking . Transformants were selected on YPD + 400 μg/ml nourseothricin or complete synthetic media ( CSM ) ( 2% dextrose , 1 . 7% Difco yeast nitrogen base with ammonium sulfate and auxotrophic supplements ) . For phenotypic assays , strains were grown in liquid RPMI-1640 Media ( Sigma-Aldrich , Inc . , St . Louis ) adjusted to pH 7 . 4 and supplemented with 10% fetal bovine serum ( Atlanta Biologicals , Inc . , Flowery Branch ) . A full list of the strains used in this study is provided under supplemental files ( S7 Table ) . All primers and plasmids used in this study are provided under supplemental files ( S8 Table ) . We previously demonstrated that the use of repeat flanked selectable markers allowed for CRISPR-Cas9 induced marker excision in subsequent manipulations [35] . To adapt the NAT1 marker for marker recycling with this method , we generated vectors containing NAT1 inserted respectively at the BamHI ( pMH05 ) and XmaI ( pMH06 ) restriction sites in the plasmid YEp24 backbone [36] . To generate plasmid pMH05 , the NAT1 marker was amplified from plasmid pNAT [37] using primers “BamHI_YEp24_H+AdapN/F” and “BamHI_YEp24_H+AdapN/R” . An aliquot of plasmid YEp24 was then digested with BamHI , and digest products were transformed alongside the NAT1 PCR product into the Saccharomyces cerevisiae strain BJ8918 with selection on synthetic media lacking uracil to allow gap repair of the digested YEp24 vector with the NAT1 PCR product [38] . The resulting vector was recovered from Ura+ transformants using a Zymoprep Yeast Plasmid Miniprep II Kit ( Zymo Research , Irvine ) and correct integration of NAT1 at the BamHI restriction site was verified by PCR . To generate plasmid pMH06 , the NAT1 marker was amplified from plasmid pNAT using primers “XmaI_YEp24_H+AdapN/F” and “XmaI_YEp24_H+AdapN/R” . An aliquot of plasmid YEp24 was then digested with XmaI , and digest products were transformed alongside the NAT1 PCR product into the Saccharomyces cerevisiae strain BJ8918 with selection on synthetic media lacking uracil to allow for gap repair of the digested YEp24 vector with the NAT1 PCR product . The resulting vector was recovered from Ura+ transformants using a Zymoprep Yeast Plasmid Miniprep II Kit and correct integration of NAT1 at the XmaI restriction site was verified by PCR . To increase the number of available markers , HIS1 was deleted in strains P76067 , P57055 , P87 , P75010 , and SC5314 using the transient CRISPR-Cas9 system [37] . Each strain was transformed with approximately 1 μg Cas9 DNA cassette , 1 μg CaHIS1 sgRNA DNA cassette , and 3 μg his1Δ::r3NAT1r3 repair template . The Cas9 DNA cassette was amplified by PCR from plasmid pV1093 as previously described [37 , 39] . The CaHIS1 sgRNA DNA cassette was generated using split-joint PCR using previously described protocols with the primers “CaHIS1 sgRNA/F” and “CaHIS1 SNR52/R” [37] . The his1Δ::r3NAT1r3 repair template was constructed in two sections using previously described protocols [35] . The first section was amplified from plasmid pMH05 using primers “HIS1 del rNATrBamHI/F” and “NAT1 CRIME/R” . The second section was amplified from plasmid pMH06 using primers “NAT1 CRIME/F” and “HIS1 del rNATrXmaI/R” . Recombination between these two sections yields the full length his1Δ::r3NAT1r3 repair template following transformation . Transformants were selected for nourseothricin resistance , and subsequently replica plated onto CSM lacking histidine to screen for a His- phenotype . Deletion of HIS1 in candidate transformants was verified by PCR from genomic DNA using primers “CaHIS1 Check/F” and “CaHIS1 Check Int/R” for absence of the HIS1 ORF , and using primers “CaHIS1 Check/F” and “NAT1 Check/R” for presence of the NAT1 marker at the his1Δ locus . To delete BCR1 , the his1Δ strains of each background were transformed with approximately 1 μg Cas9 DNA cassette , 1 μg BCR1-2 sgRNA DNA cassette , 1 μg NAT1-2 sgRNA DNA cassette , and 3 μg bcr1Δ::r1HIS1r1 repair template . Inclusion of the NAT1-2 sgRNA DNA cassette targets a Cas9 mediated double stranded break to the repeat flanked NAT1 marker at the his1Δ::r3NAT1r3 locus . The segment of vector YEp24 backbone between BamHI and XmaI constitutes the repeats flanking the NAT1 marker . We refer to these repeats as “r3” . The BCR1-2 sgRNA DNA cassette was generated using split-joint PCR with the primers “sgRNA/F BCR1-2” and “SNR52/R BCR1-2” . The NAT1-2 sgRNA DNA cassette was generated using split-joint PCR with the primers “sgRNA/F NAT1-2” and “SNR52/R NAT1-2” . The bcr1Δ::r1HIS1r1 repair template was generated in two parts . The first was amplified from plasmid pMH01 using primers “HIS1 CRIME/F” and “BCR1 del KpnI-rHIS1r/R” , and the second was amplified from plasmid pMH02 using primers “BCR1 del SapI-rHIS1r/F” and “HIS1 CRIME/R” . Recombination between the direct repeats excises the marker , rendering the strain nourseothricin sensitive and leaving only a single copy of the repeat ( r3 ) at the recycled locus [35] . Transformants were selected on CSM medium lacking histidine , and replica plated onto YPD + nourseothricin plates to screen for nourseothricin sensitivity . Candidate colonies were further genotyped by PCR using primers “BCR1 check up/F” and “BCR1 check int/R” for absence of the BCR1 ORF , and using primers “BCR1 check up/F” and “CdHIS1 Check Int/R” for presence of the HIS1 marker at the bcr1Δ locus . To delete UME6 , the his1Δ strains of each background were transformed with approximately 1 μg Cas9 DNA cassette , 1 μg UME6 sgRNA DNA cassette , 1 μg NAT1-2 sgRNA DNA cassette , and 3 μg ume6Δ::r1HIS1r1 repair template . The UME6 sgRNA DNA cassette was generated using split-joint PCR with the primers “sgRNA/F UME6” and “SNR52/R UME6” . The ume6Δ::r1HIS1r1 repair template was generated in two parts . The first was amplified from plasmid pMH01 using primers “HIS1 CRIME/F” and “UME6 del KpnI-rHIS1r/R” , and the second was amplified from plasmid pMH02 using primers “UME6 del SapI-rHIS1r/F” and “HIS1 CRIME/R” . Transformants were selected on CSM media lacking histidine , and replica plated onto YPD + nourseothricin plates to screen for nourseothricin sensitivity . Candidate colonies were further genotyped by PCR using primers “UME6 check up/F” and “UME6 check int/R” for absence of the UME6 ORF , and using primers “UME6 check up/F” and “CdHIS1 Check Int/R” for presence of the HIS1 marker at the ume6Δ locus . To delete BRG1 , the his1Δ strains of each background were transformed with approximately 1 μg Cas9 DNA cassette , 1 μg BRG1 sgRNA DNA cassette , 1 μg NAT1-2 sgRNA DNA cassette , and 3 μg brg1Δ::r1HIS1r1 repair template . The BRG1 sgRNA DNA cassette was generated using split-joint PCR with the primers “sgRNA/F BRG1” and “SNR52/R BRG1” . The brg1Δ::r1HIS1r1 repair template was generated in two parts . The first was amplified from plasmid pMH01 using primers “HIS1 CRIME/F” and “BRG1 del rHISr-KpnI/R” , and the second was amplified from plasmid pMH02 using primers “BRG1 del rHISr-SapI/F” and “HIS1 CRIME/R” . Transformants were selected on CSM media lacking histidine , and replica plated onto YPD + nourseothricin plates to screen for nourseothricin sensitivity . Candidate colonies were further genotyped by PCR using primers “BRG1 check up/F” and “BRG1 check int/R” for absence of the BRG1 ORF , and using primers “BRG1 check up/F” and “CdHIS1 Check Int/R” for presence of the HIS1 marker at the brg1Δ locus . Transformations to delete BRG1 yielded no colonies in the P87 background using this method . To isolate brg1Δ mutants in this background , a repair template with extended homology was employed . This cassette was generated in two pieces , using PCR from the genomic DNA of an SC5314 brg1Δ::r1HIS1r1 strain . Primers “BRG1 FarUp/F” with “HIS1 CRIME/R” were used for the first piece , and “HIS1 CRIME/F” and “BRG1 FarDown/R” were used for the second piece . To delete EFG1 , the his1Δ strains of each background were transformed with approximately 1 μg Cas9 DNA cassette , 1 μg EFG1-2 sgRNA DNA cassette , 1 μg NAT1-2 sgRNA DNA cassette , and 3 μg efg1Δ::r1HIS1r1 repair template . The EFG1 sgRNA DNA cassette was generated using split-joint PCR with the primers “sgRNA/F EFG1” and “SNR52/R EFG1” . The efg1Δ::r1HIS1r1 repair template was generated in two parts . The first was amplified from plasmid pMH01 using primers “HIS1 CRIME/F” and “EFG1 del rHIS1r-KpnI/R” , and the second was amplified from plasmid pMH02 using primers “EFG1 del rHIS1r-SapI/F” and “HIS1 CRIME/R” . Transformants were selected on CSM media lacking histidine , and replica plated onto YPD + nourseothricin plates to screen for nourseothricin sensitivity . Candidate colonies were further genotyped by PCR using primers “EFG1 check up/F” and “EFG1 check int/R” for absence of the EFG1 ORF , and using primers “EFG1 check up/F” and “CdHIS1 Check Int/R” for presence of the HIS1 marker at the efg1Δ locus . To generate strains constitutively expressing BRG1 , a NAT1-pTDH3 cassette containing flanking homology to the BRG1 upstream region was amplified using primers “BRG1 OE/F” and “BRG1 OE/R” from plasmid CJN542 [40] . The P57055 WT and P57055 bcr1Δ mutant were then transformed with 3 μg of this NAT1-pTDH3 cassette , 1 μg of Cas9 , and 1 μg of P-BRG1 sgRNA DNA cassette . The P-BRG1 sgRNA cassette was generated using split-joint PCR with primers “sgRNA/F P-BRG1” and “SNR52/R P-BRG1” . Transformants were selected on YPD + nourseothricin plates for the resistant phenotype , and were genotyped by PCR using primers “BRG1 Check Up/F” and “BRG1 Check Int/R” for the presence of one copy of the native BRG1 promoter , and “NAT1 CRIME/F” and “BRG1 Check Int/R” for presence of the NAT1-pTDH3 cassette in the BRG1 promoter region . To validate the construction of our TF deletion mutants , we reintroduced a copy of the SC5314 allele of each TF at the TF deletion locus using our concatemer assembly method [41] . A BCR1 cassette was amplified from SC5314 genomic DNA using primers “BCR1 check up/F” and “BCR1 3’R->pNAT 5’/R” , containing concatenating homology to a NAT1 marker . The SC5314 BCR1 allelic segment amplified by these primers contains 277 bp of the BCR1 upstream region and 399 bp of the BCR1 downstream region . A NAT1 marker was then amplified from pNAT using “pNAT for adap/F” and “pNAT 3’R->BCR1down/R” . As no colonies were recovered from the P75010 using these cassettes , A NAT1 marker with extended homology was amplified from strain MH351 gDNA using “pNAT for adap/F” and “BCR1 fardown/R” . A UME6 cassette was amplified from plasmid pSG1-UME6 ( provided by K . Lagree ) containing a SC5314 UME6 allele using primers “UME6 Check Up/F” and “UME6 3’R->pNAT 5’/R” , containing concatenating homology to a NAT1 marker . The SC5314 UME6 allelic segment amplified by these primers contains 403 bp of the UME6 upstream region and 399 of the UME6 downstream region . A NAT1 marker was then amplified from pNAT using “pNAT for adap/F” and “pNAT 3’R->UME6down/R” . A BRG1 cassette was amplified from plasmid pCW1071 containing a SC5314 BRG1 allele using primers “BRG1 Check Up/F” and “BRG1 3’R->pNAT 5’/R” , containing concatenating homology to a NAT1 marker . The SC5314 BRG1 allelic segment amplified by these primers contains 407 bp of the BRG1 upstream region and 400 bp of the BRG1 downstream region . A NAT1 marker was then amplified from pNAT using “pNAT for adap/F” and “pNAT 3’R->BRG1down/R” . An EFG1 cassette was amplified from plasmid pCW861 containing a SC5314 EFG1 allele using primers “EFG1 Check Up/F” and “EFG1 3’R->pNAT 5’/R” , containing concatenating homology to a NAT1 marker . The SC5314 EFG1 allelic segment amplified by these primers contains 153 bp of the EFG1 upstream region and 401 bp of the EFG1 downstream region . A NAT1 marker was then amplified from pNAT using “pNAT for adap/F” and “pNAT 3’R->EFG1down/R” . The TF-containing cassette and corresponding NAT1 marker were transformed into the respective TF deletion mutant in all clinical isolate backgrounds , with approximately 2 μg of the TF-containing cassette , 2 μg of the NAT1 marker cassette , 1 μg of Cas9 , and 1 μg of r1 sgRNA DNA cassette . The r1 sgRNA DNA cassette was generated using split-joint PCR with primers “sgRNA/F r1” and “SNR52/R r1” . Heterozygosity or homozygosity at the edited TF locus was determined using the presence or absence of an r1 scar [35 , 41] using PCR genotyping with the corresponding “TF Check Up/F” and “r1 check int/R” primers . To construct BRG1 ectopic expression strains , we replaced the MDR1 ORF with varying BRG1 alleles using our concatemer assembly method [41] . A cassette containing 1642 bp of BRG1 upstream sequence , the BRG1 ORF and 712 bp of BRG1 downstream sequence was amplified from SC5314 genomic DNA using primers “BRG1 1641 5’F->MDR1 up/F” and “BRG1 712 3’R->pNAT 5’/R” , containing concatenating homology to a NAT1 marker . A NAT1 marker was then amplified from pNAT using “pNAT for adap/F” and “pNAT 3’R->MDR1 down/R” . The same process was performed with P57055 genomic DNA . The BRG1SC5314 or BRG1P57055 containing cassettes and NAT1 marker cassette were transformed alongside Cas9 and MDR1 sgRNA DNA cassettes into the P57055 bcr1Δ/Δ mutant and P57055 brg1Δ/Δ mutant strains . Approximately 2 μg of the BRG1 containing cassette , 2 μg of the NAT1 marker cassette , 1 μg of Cas9 , and 1 μg of MDR1 sgRNA DNA cassette were included in each transformation mix . The MDR1 sgRNA DNA cassette was generated using split-joint PCR with primers “sgRNA/F MDR1-5” and “SNR52/R MDR1-5” . Integration of either BRG1 allele at the MDR1 locus was determined using PCR genotyping with the primers “MDR1 check up/F” and “BRG1 check int/R” . Heterozygosity or homozygosity of BRG1 integration was determined using PCR genotyping with the primers with the primers “MDR1 check up/F” and “MDR1 check int/R” . To assay biofilm formation , strains were inoculated to an OD600 of 0 . 5 from overnight cultures into 2 ml of RPMI + 10% serum containing a 1 . 5 cm x 1 . 5 cm silicone square ( Bentec Medical Inc . , Woodland ) in the wells of an untreated 12 well plate . The cells were then incubated in an incubator shaker at 37°C for 90 minutes with mild shaking ( 60 rpm ) to allow for adherence to the silicone square , and following initial adhesion , were washed of non-adherent cells by brief immersion in 2 ml PBS then reintroduced into a new well containing fresh 2 ml of RPMI + 10% serum . Biofilms were then allowed to grow for 24 hours in an incubator shaker at 37°C with mild shaking ( 60 rpm ) , before being washed of media and fixed for one hour using a solution of 4% formaldehyde and 2 . 5% glutaraldehyde in PBS . Silicone squares from biofilm assays that were not fixed for confocal imaging were soaked in distilled water and agitated to remove the bulk of any adherent biofilm material . Several passes of scrubbing then rinsing in distilled water were then used to remove any remaining adherent material . Silicone squares were then subsequently dried and autoclaved for re-use . To ensure reproducibility , recycled squares were used in all assays in the P57055 background . Fixed biofilms were stained overnight with Concanavalin A , Alexa Fluor 594 conjugate ( Life Technologies ) diluted to 25 μg/ml in PBS . Biofilms were then washed once more in PBS to remove any excess dye , then transferred to glass scintillation vials and index matched through subsequent passages through 100% methanol , 50:50 methanol and methyl salicylate solution , and 100% methyl salicylate . Biofilms were then imaged using a slit-scan confocal optical unit on a Zeiss Axiovert 200 microscope with a Zeiss 40x/0 . 85 NA oil immersion objective . The index matching and imaging are described in greater detail by Lagree et al . [42] . To assay hyphal formation , strains were inoculated to an OD600 of 0 . 5 from overnight cultures into 5 ml of RPMI + 10% serum in glass test tubes . Cells were then grown for 4 hours at 37°C in a roller drum for vigorous agitation . Cells were then collected by centrifugation and fixed with 4% formaldehyde for 15 minutes . Fixed cells were then washed twice in PBS and stained with Calcofluor-white . Stained cells were then imaged using a slit-scan confocal optical unit on a Zeiss Axiovert 200 microscope with a Zeiss C-Apochromat 40x/1 . 2 NA water immersion objective . Results were then quantified using two metrics: length of hyphal units and ratio of hyphal units to yeast cells . To quantify the length of hyphal units , the distances between septa on hyphae were measured using ImageJ . At least 50 inter-septal distance measurements were taken from 3 separate 112 μm x 83 . 5 μm fields of view . Hyphal units and yeast cells were then counted using the same fields of view to obtain the ratio of hyphal units to yeast cells . For all RNA extractions , strains were inoculated from overnight cultures into 25 ml of RPMI + 10% serum to an OD600 of 0 . 2 . Cells were then grown for 4 hours with vigorous shaking ( 225 rpm ) in an incubator shaker then harvested by vacuum filtration and quickly frozen at -80°C until RNA extraction . Three cultures of each strain were grown to provide three biological replicates for Nanostring and RNA-Seq experiments . RNA extraction and NanoString analysis was performed according to previously published methods [43] . Cell disruption was achieved mechanically using Zirconia beads ( Ambion , Fisher Scientific , Waltham ) , and extraction was performed using a 25:24:1 phenol:chloroform:isoamyl alcohol method combined with a Qiagen RNeasy Mini Kit ( Qiagen , Venlo , Netherlands ) . 25 ng of extracted RNA was added to a nanoString codeset mix and incubated at 65°C for 18 hours , before further binding and washing on a nanoString nCounter Prep Station and scanning on an nCounter digital analyzer . Raw counts were normalized against average total counts with background subtraction . Statistical significance in differential expression was assessed using the Benjamini-Hochberg procedure at a FDR of 0 . 1 . RNA-Seq was performed on the same RNA samples prepared for Nanostring . Five micrograms of total RNA was incubated with 2 units of TurboDNAse ( Invitrogen ) in a 50 ul reaction for 15 minutes at 37 degrees C . The RNA was purified by acid phenol-chloroform extraction , and the supernatant containing the RNA was purified over a column and eluted into 15 ul of nuclease free water . Two micrograms of total RNA was used as input for the Lexogen mRNA sense kit v2 . The kit was used according to the manufacturer’s instructions for shorter amplicons . Eleven cycles of PCR were performed , incorporating unique barcode indices on each library . The resulting thirty libraries were pooled evenly and subjected to one lane of Illumina sequencing ( Novogene ) , resulting in an average of 16 million reads per library . Raw fastq reads were trimmed using cutadapt ( v 1 . 9 . 1 ) ( DOI: https://doi . org/10 . 14806/ej . 17 . 1 . 200 ) , with options “-m 42 -a AGATCGGAAGAGC” to remove Illumina 3’ adapter sequence and “-u 10 -u -6” to remove the Lexogen random priming sequences , according to the Lexogen’s instructions . Trimmed reads were mapped using tophat ( v 2 . 0 . 8 ) [44] with options “–no-novel-juncs” and “-G” to align to the C . albicans SC5314 reference genome assembly 22 annotation gff file . Primary alignments were selected using samtools ( v 0 . 1 . 18 ) [45] with options “view -h -F 256” . Gene counts were created using “coverageBed” from bedtools ( v 2 . 17 . 0 ) [46] with option “-S” to count stranded alignments ( as Lexogen reads are reverse complement ) . The SC5314 release 22 is a phased diploid assembly . RNA-Seq reads mapped to the two alleles of each gene were combined for further analysis . Differential expression was assessed using DEseq2 ( v 1 . 22 . 1 ) [47] in R ( v 3 . 5 . 1 ) using default options ( alpha = 0 . 05 ) . Images were compiled and any adjustments were performed in ImageJ [48] . Single guide RNA sequences were checked for specificity using Cas-OFFinder software [49] . Network graphs were constructed using Cytoscape software [50] . Analyses were performed with Graphpad Prism version 8 . 00 ( Graphpad Software , Inc . , La Jolla ) . Venn diagrams were constructed using Venn Diagrams software ( http://bioinformatics . psb . ugent . be/webtools/Venn/ ) .
|
Much of what we know about microbial pathogens is derived from in-depth analysis of one or a few standard laboratory strains . This statement is especially true for the fungal pathogen Candida albicans , because most studies have centered on strain SC5314 and its genetically marked derivatives . Here we examine the functional impact of mutations of four key biofilm regulators across five different clinical isolates . We observe that functional impact of the mutations , based on biological phenotypes and gene expression effects , varies extensively among the isolates . Our results support the idea that gene function should be validated with multiple strain isolates . In addition , our results indicate that a core regulatory network , which comprises regulatory relationships common to multiple isolates , may be enriched for functionally relevant genes .
|
[
"Abstract",
"Introduction",
"Results",
"Discussion",
"Methods"
] |
[
"biofilms",
"medicine",
"and",
"health",
"sciences",
"pathology",
"and",
"laboratory",
"medicine",
"gene",
"regulation",
"pathogens",
"microbiology",
"mutation",
"fungi",
"experimental",
"organism",
"systems",
"molecular",
"biology",
"techniques",
"fungal",
"pathogens",
"research",
"and",
"analysis",
"methods",
"mycology",
"mutant",
"strains",
"artificial",
"gene",
"amplification",
"and",
"extension",
"animal",
"studies",
"medical",
"microbiology",
"gene",
"expression",
"microbial",
"pathogens",
"molecular",
"biology",
"yeast",
"candida",
"eukaryota",
"phenotypes",
"polymerase",
"chain",
"reaction",
"genetics",
"biology",
"and",
"life",
"sciences",
"yeast",
"and",
"fungal",
"models",
"organisms",
"candida",
"albicans"
] |
2019
|
Circuit diversification in a biofilm regulatory network
|
In order to better assist medical professionals , this study aimed to develop and compare the performance of three models—a multivariate logistic regression ( LR ) model , an artificial neural network ( ANN ) model , and a decision tree ( DT ) model—to predict the prognosis of patients with advanced schistosomiasis residing in the Hubei province . Schistosomiasis surveillance data were collected from a previous study based on a Hubei population sample including 4136 advanced schistosomiasis cases . The predictive models use LR , ANN , and DT methods . From each of the three groups , 70% of the cases ( 2896 cases ) were used as training data for the predictive models . The remaining 30% of the cases ( 1240 cases ) were used as validation groups for performance comparisons between the three models . Prediction performance was evaluated using area under the receiver operating characteristic curve ( AUC ) , sensitivity , specificity , and accuracy . Univariate analysis indicated that 16 risk factors were significantly associated with a patient’s outcome of prognosis . In the training group , the mean AUC was 0 . 8276 for LR , 0 . 9267 for ANN , and 0 . 8229 for DT . In the validation group , the mean AUC was 0 . 8349 for LR , 0 . 8318 for ANN , and 0 . 8148 for DT . The three models yielded similar results in terms of accuracy , sensitivity , and specificity . Predictive models for advanced schistosomiasis prognosis , respectively using LR , ANN and DT models were proved to be effective approaches based on our dataset . The ANN model outperformed the LR and DT models in terms of AUC .
Approximately 240 million individuals are infected worldwide by schistosomiasis , with an estimated 3 . 31 million disability-adjusted life years lost as a result of the disease [1–4] . Further , one meta-analysis and several scientific reports have suggested that global burden caused by schistosomiasis may be several times higher[3] . This concern mainly comes from the following reasons . The first reason is that the low sensitivity schistosomiasis diagnostic methods and insufficient investment of health resources may result in underdiagnosis of schistosomiasis in epidemic areas . The second reason is that the value of disability weight ( DW ) of schistosomiasis might be set too low ( 0 . 005–0 . 006 ) in the calculation of DALY value , which is similar to those for disorders such as moderate discolouration of the face ( facial vitiligo ) [5] . The third reason is that whether infected with schistosomiasis was set as the only healthy outcome in the estimation of DALY value rather than considering disparity in different clinical stages of schistosomiasis ( acute , chronic , advanced ) . Fourth , the disparity in different schistosome germline was also not taken into account for the pathological process varies greatly among Schistosoma mansoni , Schistosoma haematobium and Schistosoma japonicum . Nevertheless , Schistosomiasis was still regarded as one of the most important neglected tropical diseases worldwide . In China , schistosomiasis has been endemic in 12 provinces and municipalities [6] . Currently , the prevailing regions endemic for schistosomiasis are located in the lake and marshland regions , such as Hunan , Hubei , Jiangxi , Jiangsu , and Anhui , and in the hilly and mountainous regions , such as in Yunnan and Sichuan . However , other regions , such as Fujian , Guangdong , Shanghai , Zhejiang , and Guangxi have successfully fulfilled the criteria for interrupting schistosomiasis transmission since 1985[7] . Hubei province is one of the five lake and marshland schistosomiasis endemic regions which located in the middle and lower regions of the Yangtze River [8] . In addition , Hubei has the largest area of the freshwater snail Oncomelania hupensis , which is the only intermediate host of Schistosoma japonicum . Moreover , Hubei has the highest rates of schistosomiasis transmission in China [9] . By 2015 , Hubei had 9098 ( 29 . 50% of China’s total cases ) documented cases of advanced schistosomiasis , ranking Hubei first in all schistosomiasis endemic provinces in China [10] . Advanced , or late-stage schistosomiasis japonica can be regarded as an extreme form of chronic schistosomiasis , which is more serious than the advanced hepatosplenic disease of Schistosoma mansoni infection found in Africa and the Americas [11] . According to ‘Diagnostic Criteria for Schistosomiasis’ ( WS261-2006 ) , one of health industry standards in People's Republic of China provided by National Ministry of Health , the advanced schistosomiasis case is defined as a patient with schistosomiasis who develops portal hypertensive syndromes of liver fibrosis , severe growth disorders or significant colon granulomatous hyperplasia . Due to repeated or mass infection of schistosome cercariae , without thorough and timely treatment , patients can evolve into advanced schistosomiasis usually after 2 to 10 years of pathological development process . Clinical symptoms of advanced schistosomiasis include ascites , splenomegaly , portal hypertension , gastro-esophageal variceal bleeding , granulomatous lesions of the large intestine , and serious growth retardation [12 , 13] . Advanced schistosomiasis japonica is much more common in highly endemic areas , because repeated , heavy exposure to cercariae means that early-stage chronic cases may not be effectively treated in routine control programs . The eggs of S . japonicum retained in the intestine and liver tissue stimulate a granulomatous response , leading to continuous fibrosis of the periportal tissue and developing a pipestem fibrosis . Although down-modulation of the granulomatous response , which could prevent further chronic morbidity after 2–5 years or more , parasite-induced periportal fibrosis may progress to cause obstruction of the portal vessels and damage to the liver parenchyma , leading to development of advanced schistosomiasis . Mortality eventually results from bleeding of the upper gastrointestinal tract , spontaneous bacterial peritonitis , and hepatic failure , among other factors . Based on its major symptoms , advanced schistosomiasis japonica in China represents a widespread , serious health burden , and has been classified into four clinical sub-types , namely ascites , megalosplenia , colonic tumorous proliferation , and dwarfism [14 , 15] . Predictive models used in disease prognosis studies can answer the following questions such as the seriousness of the patient’s condition and whether can be cured . Also it can be used to guide clinical treatment and help to select the right medical decision-making . Therefore , the predictive model is of great significance . Specifically , the predictive model can be used to understand the trends and consequences of a disease and help clinicians make treatment decisions and determine the urgency of treatment . The model can be applied to study the various influencing factors that affect the prognosis of the disease and assess the effectiveness of a treatment . Logistic regression ( LR ) model is a probabilistic non-linear regression model . As a popular multivariate analysis method , it is widely used to study the relationship between dichotomous observations and some influencing factors . In epidemiology , LR model is always used to explore the risk factors of a disease , predict the probability of a disease occurring based on risk factors and so on . For example , to explore the risk factors for gastric cancer ( GC ) , you can choose two groups of people , a GC group and a non-GC group with different signs and lifestyles . The dependent variable here is gastric cancer ( "yes" or "no" ) , while independent variables can covers a lot , such as age , gender , eating habits , Helicobacter pylori infection . The arguments in the model can be either continuous or categorized . By logistic regression analysis , we can get a general understanding of which factors are risk factors for GC . ANN model is a mathematical model that simulates the structure of the human brain and the way of information transmission . It consists of a set of interconnected “neurons” linked with weighted connections . The model was constructed by an input layer , a hidden layer and an output layer . The input layer contains neurons that receive input data available for analysis ( e . g . various demographical , clinical or laboratory data ) , and output layer contains neurons that export different values . ANN can learn through examples and associate each input with the corresponding output by modifying the weight of the connections between neurons . The output value is compared with the expected output . If there is a discrepancy between these two values , an error signal is generated and then a back propagation ( BP ) method is applied to alter the weight of the connections between neurons to decrease the overall error of the network . As learning proceeds , the error between the ANN output and the expected output decreases until a minimum is reached . The process was called convergence of the network . After these two training processes , the ANN can generate outputs ( prognosis ) from new input data based on the knowledge accumulated during training , which is regarded as inference process . Thus , after training , the ANN can make predictions on data sets never seen before or identify patterns . There are some similar studies . A study demonstrated that the ANN model is a more powerful tool in determining the significant prognostic variables for gastric cancer ( GC ) patients , compared to the Cox proportional hazard regression ( CPH ) model [16] . In another study , the ANN model was shown to be more accurate in predicting 3-month mortality of acute-on-chronic hepatitis B liver failure ( ACHBLF ) than Model for end-stage liver disease ( MELD ) based scoring systems [17] . In addition to these examples , a trained ANN performs at least as well as physicians in assessments of visual fields for the diagnosis of glaucoma in a ophthalmology research [18] . The decision tree ( DT ) is a machine learning model , composed of decision rules based on optimal feature cutoff values that recursively split independent variables into different groups to predict an outcome in a hierarchical manner . The principle of DT is similar to that of variance discomposition in ANOVA . The basic purpose is to divide the research population into several relatively homogeneous subgroups through some attribute values . The values of internal variables in each subgroup are highly consistent , and the corresponding variations ( impurities ) fall in different subgroups as far as possible . All DT model algorithms follow this principle , which is different from ANOVA by definition of variation ( impurity ) , such as P values , variance in ANOVA and information entropy , G1NI coefficients , deviance in DT . Some examples are also provided . A simple , clinically relevant DT model was developed and validated to reliably discriminate patients at high and low risk of death using routinely available variables from the time of diagnosis in unselected populations of patients with malignant pleural mesothelioma ( MPM ) [19] . Another simple decision tree can provide a quick assessment of the severity of the chronic obstructive pulmonary disease ( COPD ) by using variables commonly gathered by physicians , as measured by the risk of 5-yr mortality [20] . The DT modeling based on C4 . 5 algorithm which was applied to predict prostate cancer risk in another study showed different interaction profiles by race [21] . Traditional LR model is the most popular predictive among different classification methods because the effects of each factors in LR model could be quantitatively explained and an approximately estimate of the relative risk ( OR ) could be derived easily . However , whether the data could fit the model requires that the data satisfy a given condition and the collinearity and interaction between the variables cannot be solved . ANN model possesses strong ability to solve such problems and has no limitation on the distribution of data . It is generally believed that the ANN model is better than LR model for the disease with many pathogenic factors and complicated relationships among these factors . The DT model also generally considers the interaction between the variables , and it shows a clear screening process in the form of a tree . Compared with the OR value of LR model , the DT model is more conducive for clinicians' understanding . Therefore , the aim of this study was to compare the performance of three predictive models ( ANN , LR and DT ) for the prognosis of advanced schistosomiasis cases , along with a 10-fold cross-validation technique . The performance of the predictive models was evaluated according to the area under the receiver operating characteristic curves ( AUC ) , accuracy , sensitivity , and specificity .
The study was approved by Research Ethics Committee in Tongji Medical College of Huazhong University of Science and Technology . The methods of the present study were put into effect according to the approved protocols . All participants in this study were adults . Note: Though a child from Xingzi county , Jiangxi Province had ever been reported to diagnosed as advanced schistosomiasis[22] , such case is exceedingly rare and never been reported in Hubei . In general , all the advanced schistosomiasis patients are adults . The participants read the investigation purpose statement and signed informed consents . All data were anonymized and handled confidentially . Schistosomiasis surveillance data was collected from a previously constructed database of advanced schistosomiasis cases in the Hubei province from a study conducted by the Hubei Institute of Schistosomiasis Prevention and Control . The information was obtained by a standard sociodemographic and epidemiological questionnaire for patients in Hubei with advanced schistosomiasis . Participants were recruited from schistosomiasis epidemic areas all over the province , primarily along the Yangtze River regions . The treatment methods of advanced schistosomiasis patients vary with different disease conditions . Liver protection and symptomatic treatment was applied for ascites type patients . Splenectomy was needed to be done in splenomegaly patients if there is hypersplenism symptom existed . The praziquantel ( PZD ) treatment can be utilized after six months of stable period in which the general situation of the patient is fine ( e . g . no ascites or hemorrhage symptoms ) . The medical records of the patients with advanced schistosomiasis were reviewed by attending physicians . Criteria of cases inclusion are as follows: To avoid the confounding effect of other diseases on the prediction of advanced schistosomiasis prognosis , the patients with following diseases were excluded from the study . A total of 4136 cases were included in the study which consisted of 2674 men and 1462 women and were divided into two groups: favorable prognosis and poor prognosis . Favorable prognosis referred to cases of recovery and improved disease outcomes while poor prognosis referred to cases of deterioration and death . The presence of the event ( dead or deterioration ) was coded as 1 and the absence of the event ( recovery or improved ) was coded as 0 . The death of advanced schistosomiasis patients was mainly due to schistosomiasis and schistosomiasis-induced complications , such as upper gastrointestinal hemorrhage , hepatorenal syndrome ( HRS ) , hepatic coma and liver cancer . Therefore , the death outcome that appears in this article refers to all-cause death . The deterioration outcome means that the primary symptoms persist ( e . g . no ascites regression sign ) or patients in splenomegaly type have no surgical indications . Data collection included demographical data , hospitalization costs , clinical features , surgical procedures , and outcomes . This study was entirely retrospective which was utilizing records from the hospitals specializing in schitosomiasis of various epidemic counties , Hubei province . In the first step , the continuous explanatory variables were transformed into categorized variables to decrease the effect of extreme values and enhance the computational efficiency of the ANN . The cutoff points of these variables were set as 0 . 5 . The variables included occupation , annual income , body mass index ( BMI ) and so on . The sociodemographic and epidemiological characteristics of the 4136 advanced schistosomiasis cases are presented in Table 1 . The criterion used for the histopathologic diagnosis of advanced schistosomiasis was the national standardized diagnostic criteria for schistosomiasis ( WS261-2006 ) . In the second step , a univariate Cox proportional hazard model was used to improve the computational efficiency and prediction performance of the ANN model by testing the potential relationships between independent variables . Variables with statistically significant differences ( log-rank test , P<0 . 05 ) were reserved to build the ANN model ( Table 1 ) . In total , 16 variables were selected to build the ANN model . Patients were randomly assigned to the training group ( 70% of the total cases ) for the development of the ANN , DT , and LR models . The rest of the patients ( 30% of the total cases ) were assigned to the validation groups for the assessment of model performance . Of the 4136 patients with advanced schistosomiasis , 2896 were assigned to the training group and1240 were assigned to the validation group . As listed in Table 1 , the effects of the input variables did not significantly differ between the training group and the validation group of all three models ( P>0 . 05 ) , indicating the reliability of the data partition . The data mining software package MATLAB ( Matrix Laboratory , Math Works Company , USA , R2014a software ) was used to run ANN and C4 . 5 DT models . SPSS 19 . 0 ( IBM Corp , Armonk , NY , USA ) was used to establish the LR model . For all comparisons , differences were tested with two-tailed tests and P values less than 0 . 05 were considered statistically significant . An ANN is one of the most widely applied models in the medical domain , such as for the interpretation of imaging techniques , prognosis , diagnosis , or diagnostic tests . ANN differs from other conventional statistical models in that ANN usually has more parameters . This study used an ANN model with a standard feed-forward back propagation ( BP ) network structure , including an input layer of 16 neurons , a hidden layer of 20 neurons , and an output layer of 2 neurons , to predict the prognosis of patients with advanced schistosomiasis . Sigmoid transfer functions were applied to the hidden and output layers . Gradient descent was used to calculate the synaptic weights . The initial learning rate was defined as 0 . 07 and the momentum was 0 . 95 . The batch size was defined as 256 and the number of iterations was 200 . Ten-fold cross-validation was employed . Fig 1 shows the structure of the ANN model . As there is currently no accepted theory that predetermines the optimal number of hidden layer neurons , the number of hidden layer neurons was determined by repeated trial and error test until the best sensitivity and specificity was achieved . For the categorical dependent variables , a LR model was conducted to identify the risk factors of various diseases by using patient demographic characteristics and other disease parameters . The LR model formula calculates the probability of a given disease , y ( y = 1 if the selected case suffers from the disease , otherwise , y = 0 ) . If the subject suffers from the disease , the conditional probability is represented as p ( y = 1∣X ) = p ( X ) , and the formula of the LR model is expressed as log [ ( p ( x ) ∣1− p ( x ) ] = β0+β1x1+β2x2+…+βkxk] , where X = ( x1 , x2 , … , xk ) denotes the vector of independent variables . An ‘entry’ approach was used to construct the LR model using the 16 variables . The LR model was built using the training dataset and tested using the validation data . The model-based clinical data interpretation system C4 . 5 algorithm for the prognosis of advanced schistosomiasis is shown in Fig 2 . C4 . 5 was used as the multiclass classification algorithm , which was a development of the DT algorithm ID3 . The algorithm contained the same working principle , but calculated information gain differently . In the ID3 algorithm , the learning process is conducted in reference to the gain calculation , which is the same gain calculation in the feature selection process of the information gain , as shown in Eqs ( 1 ) and ( 2 ) . In the C4 . 5 algorithm , the learning process uses the ID3 normalized gain , as shown in Eqs ( 3 ) and ( 4 ) : Entropy ( S ) =∑tc−pilog2 ( pi ) ( 1 ) Gain ( S , A ) =Entropy ( S ) −∑v∈Values ( A ) SvSEntropy ( Sv ) ( 2 ) GainRation ( S , A ) =Gain ( S , A ) /SplitInfo ( S , A ) ( 3 ) SplitInfo ( S , A ) =∑t=1cSvSlog2 ( SvS ) ( 4 ) The AUC was used to compare the prediction performance of the three data mining models . The classification accuracy referred to the fraction of cases classified correctly . Sensitivity referred to the proportion of positive cases that were classified as positive . Specificity referred to the proportion of negative cases that were classified as negative . The formulas are shown as follows , where TP , FP , TN , FN represent true positives , false positives , true negatives , and false negatives , respectively . The AUC value of ANN can be interpreted Accuracy= ( TP+TN ) / ( TP+FP+TN+FN ) Sensitivity=TP/ ( TP+FN ) Specificity=TN/ ( FP+TN )
For the training and validation group , the ROC curves for the ANN , LR , and DT models are shown in Figs 3 and 4 . In the training group , the AUC value for the prognosis of patients with advanced schistosomiasis was 0 . 927 for the ANN model , 0 . 828 for the LR model , and 0 . 823 for the DT model . The AUC values of the ANN model were superior to those of the DT and LR models . In the validation group , the AUC value for the prognosis of patients with advanced schistosomiasis was 0 . 832 for the ANN model , 0 . 835 for the LR model , and 0 . 815 for the DT model . The AUC values of the ANN , DT , and LR models were approximate . The performance comparison of the three models in the two groups is listed in Table 2 . We evaluate the differences in order to see whether there was significance . AUC value could be shown as the normalized Mann–Whitney U statistics . Concerning the normalization denominator is universal for all models , we could thus show the superiority by the AUC value from nonparametric test perspective . Specifically , given the true label of each sample , the larger AUC value , the lager Mann–Whitney U statistics , the better classified capability of the model . We additionally conduct two pairwise tests for AUC values to substantiate the superiority . For ANN and DT , the result shows the difference is significant . ( Z = 15 . 742 , P = 0 . 000 ) . For ANN and LR , we obtain the similar result as following . ( Z = 15 . 117 , P = 0 . 000 )
Advanced schistosomiasis , resulting from either repeated infection or acute infection without chemotherapy , is the most severe form of schistosomiasis and clinically presents with portal hypertension [23] , periportal liver fibrosis , spleen enlargement , congestion , and other serious conditions [24–26] . Data mining systems aim to extract implicit , previously unknown and potentially valuable relationships and patterns from large amounts of data to provide clear and useful information through advanced processes of selecting , exploring , and modeling [27 , 28] . Recent years have seen a rapid development of data mining technology [29 , 30] . Currently , predictive models are being used in the clinical setting to improve diagnostic and prognostic accuracy and enhance clinical decision-making [28 , 31] . Of these predictive models , LR , ANN , and DT models are among the most widely used models for predicting a patients’ prognosis [14 , 32–34] . However , little research has been conducted on the use of data mining methods to establish predictive models for prognosis of advanced schistosomiasis . Thus , the current study used data from the Hubei Institute of Schistosomiasis Prevention and Control to develop and compare three predictive models in their ability to predict the prognosis of patients with advanced schistosomiasis . One of the most attractive features of ANN is the system’s ability to apply machine learning , also referred to as training . ANNs can continuously adjust parameters , such as connection weights , and store the sample set as a connection weight matrix under circumstance of external environment stimulation , such as the input of the sample set . When the ANN accepts the input again , the system can provide the appropriate output . In the present study , there were many neurons in the model and the sample size had rigorous requirements . Therefore , only the variables that were selected by single factor analysis and closely related to the prognosis of advanced schistosomiasis were used as input variables . A good predictive model can distinguish population at high risk from the one at low risk , which is so called discrimination . Discrimination is generally expressed as the area under the ROC curve , referred to as AUC . The higher the AUC value , the better the model can discriminate between high and low risk groups . Due to the serious adverse prognosis of advanced schistosomiasis patients , the sensitivity of the predictive model should be as high as possible in order to avoid false negatives on condition that the discrimination of the model is fine ( e . g . AUC≥0 . 75 ) . Data from the designated training set was then used to evaluate the ANN model , and the prediction accuracy of the ANN model was 0 . 8660 , which was better than the LR model ( 0 . 7990 , ) and the DT model ( 0 . 8194 ) . The AUC of the ANN , LR , and DT models was 0 . 9267 , 0 . 8276 , and 0 . 8229 , respectively , which indicates that the ANN model had the best prediction performance by Mann–Whitney U test . In comparison to the LR and DT models , the ANN model had the best fitting effect for the relationship between advanced schistosomiasis and pathogenic factors . Schistosomiasis’ pathogenesis of disease is a complicated process influenced by multiple factors; thus , the use of traditional LR models to predict the development of disease is significantly limited by the inability to determine effects of multiple co-linearity between the independent variables . DT models can be easily applied to discrete values , but when there are more attribute values , the effect may be poor [35] . While ANN models can handle more attribute values , they have the potential to over-fit effects and their network training speed can decrease when there are more independent variables [36] . Despite its limitations , the LR model has been widely adopted because it offers other advantages [37 , 38] . LR models have the function of discrimination and prediction and LR models are suitable for qualitative and semi-quantitative indicators [39] . In addition , LR models can use log transformation to convert nonlinear relationships between dependent variables and independent variables into linear relationships , which has less restriction conditions and a relatively low requirement of data types . To build predictive models , LR frameworks can automatically select highly correlated indices to be included as independent variables in the equation , which makes LR models convenient , feasible , and easy to popularize[40 , 41] . It should be noted that once we develop a LR model in medical practice , it always means the LR model for every disease itself rather than for any disease . In comparison to LR models , DT models can not only detect statistically significant risk factors , the model can also intuitively compare the intensity of various risk factors on the prognosis of patients with advanced schistosomiasis [42 , 43] . The DT algorithm can simultaneously handle diverse types of data and missing data values without having to address the parameters in advance . DT models have a fast training speed , high classification efficiency , and ability to handle large sets of complex non-linear data [44–46] . ANN simulates the function and structure of biological neural network to establish non-linear mathematical models with strong fault tolerance , adaptiveness , nonlinear comprehensive reasoning ability , and the powerful ability to solve co-linearity and interactions between variables [47 , 48] . Although complex relationships often exist between output and input factors in the medical field , ANNs have been used in clinical settings to effectively solve this issue and successfully applied to large and complex sample statistics . [49–51] . ANN models can not only realize the objective detection and classification of disease , but they can also improve the efficiency of disease prognosis and differential diagnosis . While the predictive ability of ANNs has many advantages , the model still has several limitations . First , the network changes with the setting of parameters , functions , and initial values . The correctness of these settings lack a theoretical basis , as the settings can only be determined by experience and repeated tests . Second , unlike the LR model , the ANN model does not have a recognized model of input variable access and elimination . Third , as a result of their structure , ANN models do not provide any medical explanation pertaining to each independent variable; thus , the hypothesis test methods , confidence intervals , and other issues require additional research [52 , 53] . The advantages and disadvantages between these models on the implementation of them in the medical practice are noteworthy . A study that used ANN models and generalized additive models ( GAM ) to estimate glomerular filtration rate ( GFR ) in patients with chronic kidney disease found that the advantage of ANN is obvious only when multiple variables added to the model , especially the multicollinearity existed [54] . ANN is difficult to solve the problem of internal authenticity ( repeatability ) within the model due to the single data set source . However , the advantages of the ANN model over LR were also demonstrated: dealing with noise and incomplete input variables , high fault tolerance and good generalizability . LR model still plays an important role in the study of prognosis of disease due to its better interpretability . In a study that used large national samples to find the cause of arthritis pain , the DT model incorporated more than 200 variables with a high accuracy of 85 . 68% [55] . In the era of big data , the DT model facilitates algorithms transforming from hypothesis-driven to data-driven . Like ANN model , the robustness of DT model is better when there are more covariables [56] . Tree models can produce visual classification rules which are closer to people's way of thinking . However , DT model also has its disadvantages such as potentially introducing bias due to division of the tree every time , with the other drawbacks of high variance and instability . The present study constructed three predictive models—the ANN model , the LR model , and the DT model—to predict advanced schistosomiasis prognosis . While each of the predictive models proved effective and had their own advantages , the ANN model outperformed the LR and DT models in terms of AUC and sensitivity . However , to achieve the highest level of prediction accuracy and better assist medical professionals , the three predictive models should be applied after model comparison .
|
Worldwide , approximately 240 million individuals are infected with schistosomiasis , a parasitic neglected tropical disease that continues to be a significant cause of morbidity and mortality , especially in China . Effective tools that can accurately predict the prognosis of patients with advanced schistosomiasis would aid in the treatment and management of the disease . To this end , we constructed and compared the performance of three predictive models—an artificial neural network ( ANN ) model , a logistic regression ( LR ) model and a decision tree ( DT ) model—in their ability to predict the prognosis of patients with advanced schistosomiasis . We found that while all three models proved effective , the ANN model outperformed the LR and DT models in terms of AUC and sensitivity . Yet , to achieve the highest level of prediction accuracy and to better assist medical professionals , we recommend comparing the performance of the three predictive models to select the optimal one , which will be better than select a model at random . The findings of this study not only provide valuable information on the construction of effective predictive models for the prognosis of advanced schistosomiasis , but also offer new methodology for clinically determining patient diagnosis and prognosis .
|
[
"Abstract",
"Introduction",
"Methods",
"Results",
"Discussion"
] |
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2018
|
Comparison of three data mining models for prediction of advanced schistosomiasis prognosis in the Hubei province
|
We have reported that transcription of a hypothetical small open reading frame ( orf60 ) in enteroaggregative E . coli ( EAEC ) strain 042 is impaired after mutation of aggR , which encodes a global virulence activator . We have also reported that the cryptic orf60 locus was linked to protection against EAEC diarrhea in two epidemiologic studies . Here , we report that the orf60 product acts as a negative regulator of aggR itself . The orf60 protein product lacks homology to known repressors , but displays 44–100% similarity to at least fifty previously undescribed small ( <10 kDa ) hypothetical proteins found in many gram negative pathogen genomes . Expression of orf60 homologs from enterotoxigenic E . coli ( ETEC ) repressed the expression of the AraC-transcriptional ETEC regulator CfaD/Rns and its regulon in ETEC strain H10407 . Complementation in trans of EAEC 042orf60 by orf60 homologs from ETEC and the mouse pathogen Citrobacter rodentium resulted in dramatic suppression of aggR . A C . rodentium orf60 homolog mutant showed increased levels of activator RegA and increased colonization of the adult mouse . We propose the name Aar ( AggR-activated regulator ) for the clinically and epidemiologically important orf60 product in EAEC , and postulate the existence of a large family of homologs among pathogenic Enterobacteriaceae and Pasteurellaceae . We propose the name ANR ( AraC Negative Regulators ) for this family .
Enteroaggregative Escherichia coli ( EAEC ) is a diarrheagenic pathotype linked to traveler's diarrhea , foodborne outbreaks and sporadic diarrhea in industrialized and developing countries [1]–[4] . A Shiga toxin-lysogenized EAEC caused a large and highly lethal European outbreak in 2011 , highlighting the potential virulence of this pathotype [4]–[6] . Virulence gene expression in EAEC is activated in coordinate fashion by a regulator called AggR , a member of the AraC/XylS family of bacterial transcription factors [7]–[9]; AggR is most closely related to the CfaD/Rns activator of enterotoxigenic E . coli ( ETEC ) [10] , RegA in C . rodentium [11] and PerA in enteropathogenic E . coli ( EPEC ) [12] , [13] . AggR , Rns/CfaD , RegA and PerA are required for expression of genes mediating the biosynthesis of colonization fimbriae and other virulence-associated factors . We have recently reported that AggR regulates the expression of at least 44 genes , including itself , at the onset of the logarithmic growth phase [14] . Among the most dramatically upregulated genes in the AggR regulon was a very small cryptic open reading frame ( orf; designated variously orf60 or orf61 , but here only orf60 ) lacking homology to any known gene , but located on the pAA2 virulence plasmid nearby to the gene encoding AggR itself [14] . We were struck by the high prevalence and conservation of orf60 among EAEC strains . In an effort to understand the highly mosaic character of the EAEC genome and its relationship to endemic diarrhea in developing countries , we scored the presence of AggR-dependent and AggR-independent putative virulence genes among collections of EAEC strains from children under 5 years of age with diarrhea in Mali [15] and Brazil [16] . In both studies , we were struck by the strong and consistent negative association between the presence of orf60/61 and diarrhea . Given compelling data favoring some important role for cryptic locus orf60/61 in EAEC epidemiology , we undertook a thorough investigation of its role in pathogenesis . We report here that EAEC orf60 encodes a novel protein negative regulator , now formally re-named Aar ( AggR-activated regulator ) . Although expression of the Aar-encoding gene in EAEC is indeed activated by AggR , expression of the gene down-regulates expression of AggR itself . Most surprisingly , we show that Aar is a member of a previouly unrecognized large class of regulators in pathogenic Gram negative bacteria .
To examine the role of orf60 , a 042orf60 mutant was generated , assessed for established EAEC phenotypes and observed by TEM . The orf60 mutant was complemented in trans by expressing the predicted orf downstream of the arabinose promoter in pBAD30 , to yield pOrf60 . Since the orf generated two possible protein products given translational start from an ATG or alternative start codon , the construct included the most upstream ( alternative ) potential start site . Surprisingly , 042orf60 was found to be hyper-fimbriated by negative staining in TEM ( Figure 1 , B and E ) , and readily distinguishable from the parent strain ( Figure 1 , A and D ) , or the 042orf60 mutant complemented in trans with the pOrf60 plasmid ( Figure 1 , C and F ) , both of which showed sparse fimbriae . As predicted from the documented role of AAF in aggregation , larger bacterial aggregates were visualized by TEM in the 042orf60 mutant , when compared to the wild type or complemented strains . The hyper-aggregative phenotype of 042orf60 was also apparent in undisturbed broth cultures ( Fig . S1 in Text S1 , panels A and B ) . We have previously demonstrated that the AAF/II major pilin protein AafA binds to fibronectin [17] . To evaluate fimbrial function in the absence of orf60 , we assessed this phenotype in 042orf60 and complemented constructs . As expected , the hyperfimbriated 042orf60 strain exhibited more abundant binding to fibronectin-coated plates ( ∼200% binding ) compared to the parent strain ( Figure 1 , panel G ) , while overexpression of orf60 in the complemented EAEC strain yielded marked reduction of fibronectin binding . As predicted from these phenotypes , 042orf60 yielded more abundant expression of the major AAF/II fimbrial subunit protein AafA than its wild type parent in immunoblot analysis , and this phenotype was reversed in the complemented construct ( Fig . S1 in Text S1 , panel C ) . We therefore employed qRT-PCR to assess the effect of orf60 on aaf fimbrial gene expression . 042 wild type , 042orf60 and 042orf60 ( pOrf60 ) strains were grown in DMEM high glucose and samples from log-phase cultures were used for qRT-PCR analysis ( Figure 1 , H ) . We observed higher levels of expression for fimbrial genes aafA ( 10- to 25-fold ) , aafB ( 4- to 11-fold ) , aafC ( 4- to 6-fold ) and aafD ( 3- to 8-fold ) in the 042orf60 mutant compared with the parent strain , while frimbrial gene expression in the complemented strain was nearly undetectable . Our data suggested that orf60 may act as a negative feedback regulator of fimbrial gene expression , despite the fact that both the fimbriae and orf60 are under AggR activation . We sought to dissect features of this regulatory system in EAEC using qRT-PCR . Levels of transcription of aggR ( Figure 2 , A ) and the aggR-regulated genes aap ( Figure 2 , B ) and aatPABCD ( Figure 2 , C ) were compared between 042orf60 and the parent strain by qRT-PCR . We observed two-fold higher aggR mRNA levels in 042orf60 compared to the parent strain ( Figure 2 , A ) . Expression of other AggR-regulated genes was similarly affected by orf60 deletion , including aap , aatP , aatA , aatB , aatC , and aatD ( Figure 2 , B and C ) . The greatest effect was observed for the aatC gene , expression of which was 37-fold higher in the orf60 mutant compared with the wild type parent strain ( Figure 2 , C ) . Complementation in trans with the orf60 gene resulted in undetectable levels of aggR and AggR-regulated genes , comparable to the levels seen in EAEC lacking the pAA2 plasmid ( Figure 2A , B and C ) . We examined similarly aggR and orf60 expression in the 042aggR and 042orf60 mutant strains during the middle-late log phase of growth ( 5–8 h ) . aggR expression was consistently high in the absence of orf60 ( Figure 2 , E ) , whereas orf60 levels were drastically reduced in the absence of aggR ( Figure 2 , F ) . These data suggest that the effect of orf60 on fimbrial gene expression was via a negative feedback effect on aggR itself , accompanied by the predicted suppression of other genes downstream in the AggR regulon . We hypothesized that orf60 may represent a delayed negative feedback regulator of aggR . To test this hypothesis , RNA was obtained from strain 042 cultures prepared in DMEM high glucose at various stages of cell growth , spanning the log and early stationary phases ( 0–8 h of growth ) , and analyzed for aggR and orf60 transcripts ( Figure 2 , D ) . As previously reported [18] , we observed a rapid increase in aggR expression in the first 2 h of growth ( early log phase ) , while expression of orf60 was delayed , achieving maximal levels after 4 h of incubation ( middle log phase ) ( Figure 2 , D ) ; at this time point aggR expression was seen to be declining , consistent with activation of orf60 by AggR and repression of aggR by the orf60 product . At 6 h of growth , both aggR and orf60 levels were declining . Interestingly , orf60 gene expression reached its lowest expression level at the end of late log phase ( 8 h ) , while aggR expression was again increasing . Both aggR and orf60 were at low levels by 10 hr of growth ( Figure 2 , D ) . We sought to determine whether orf60 encodes a small regulatory RNA molecule or a regulatory protein . Expression of orf60 from pOrf60 was assessed after mutation of three potential start codons in the open reading frame: predicted codons 1 , 4 and 5 ( illustrated in Figure 3A as M1 , M4 , and M5 ) . Plasmid derivatives ( pOrf60-M1 , pOrf60-M4 , and pOrf60-M5 ) were used to complement the 042orf60 strain . Transcripts for orf60 , aggR and aap ( Figure 3 , B , C and D ) were determined in all 042orf60 ( pOrf60 ) derivatives . In all strains , high levels of transcripts for orf60 were detected by qRT-PCR ( Figure 3 , B ) . Replacement of the ATG only in position 5 with a stop codon lead to abrogation of the orf60-induced phenotypes , manifested as expression of aggR and the AggR-regulated gene aap ( Figure 3 , panels C , D ) . The hyper-aggregative phenotype of 042orf60 was not reversed when the strain was transformed with pOrf60-M5 , indicating requirement of this predicted start codon in orf60 expression ( Fig . S1 in Text S1 , panels A , B ) . Our data suggested that orf60 would be transcribed and translated as a small protein of 7 . 23 kDa . In order to observe and localize the orf60 protein , bacterial samples were fractionated into outer membrane , cytoplasmic/periplasmic fractions , and analyzed by Western immunoblot ( Figure 3 , E ) . Localization of the product at the predicted mass confirmed its existence and localized the product to the cytoplasmic/periplasmic fraction of the bacterium . Using the Bprom algorithm , a strong sigma-70 bacterial promoter region was predicted upstream of the ATG start site; predicted −35 and −10 regions were included in plasmid pOrf60 . To confirm that constitutive expression of orf60 was driven by this predicted promoter , the araC gene and PBAD promoter were removed from pOrf60 plasmid to generate pOrf60-2 ( Fig . S2 in Text S1 , panel A ) . pOrf60-2 plasmid was transformed into 042 and its orf60 mutant , and RNA transcripts for orf60 and aggR were quantitated by qRT-PCR . High transcriptional levels of orf60 were detected by qRT-PCR in strains transformed with pOrf60 and pOrf60-2 ( Fig . S2 in Text S1 , panel C ) . 042 derivatives transformed with pOrf60-2 still retained the inhibitory effect of orf60 ( Fig . S2 in Text S1 , panel D ) . High transcriptional levels of orf60 did not compromise the fitness of the cell , as manifested by growth curves in DMEM medium ( Fig . S3 in Text S1 , Panel A ) . To assure that the effects of orf60 expression in trans were not due to high copy number over-expression artifacts , we cloned the gene into low copy number vector a pACYC177 . This lower copy number construct restored the wild type phenotype ( Fig . S3 in Text S1 , Panels B , C , D ) . Blast analysis of orf60 and its predicted product did not suggest significant relatedness to any known bacterial regulatory protein; however , the analysis did identify nearly 50 hypothetical proteins , present in 7 major genera/species: Escherichia coli , Citrobacter spp . , Haemophilus spp . , Pasteurella spp . , Mannheimia spp . , Pantoea spp . and Aggregatibacter spp . ( Figure 4 ) . Like orf60 , all predicted products of this family of hypothetical proteins exhibited low predicted molecular mass ( 39 to 80 amino acids , 4 . 36–9 . 54 kDa ) , and exhibited 44–100% similarity to orf60 ( Figure 4 ) . Haemophilus orf60 homologs were mainly found in pathogenic strains including H . influenzae , H . paraphrohaemolyticus , H . parainfluenzae , H . aegypticus , and H . pittmaniae subspecies [19] , [20] . The predicted protein masses of orf60 homologs in Haemophilus sp . varied from 7 . 73 to 8 . 65 kDa and exhibited 49 to 56% amino acid similarity to the EAEC orf60 product ( Figure 4 , dark gray boxes ) . orf60 homologs were also found in pathogens Pasteurella multocida and Pasteurella bettyae [21]; these predicted proteins displayed 54% similarity to orf60 with sizes between 6 . 82 to 8 . 67 kDa ( Figure 4 ) . Orf60 homologs with 51 to 55% similarity and masses between 8 . 26 to 9 . 04 kDa were also identified in Mannheimia haemolytica , the agent of bovine respiratory disease complex [22] . Orf60 homologs in Aggregatibacter actinomycetemcomitans and Aggregatibacter aphrophilus exhibit 50 to 55% similarity to EAEC orf60 and their masses range from of 7 . 85 to 8 . 17 kDa . Orf60 homologs are also found in Pantoea spp . , a Gram-negative bacterium associated with infections in neonates [23] . The orf60 homolog in Pantoea is a 7 kDa protein that shows 50% similarity to EAEC orf60 . A phylogenetic subgroup of orf60 homologs was found among pathogenic E . coli genomes , subdivided into two main subfamilies ( SFs ) , SF1 and SF2 ( Figure 4 ) . SF1 comprised the orf60 homologs found in enterohemorrhagic E . coli ( EHEC ) strain ( 12009 , DEC5E , DEC8D ) , enteropathogenic E . coli ( EPEC ) ( E2348/69 ) , Shiga-toxin producing E . coli ( STEC ) ( DEC11C , H . 1 . 8 , EH250 , 99 . 0741 , 1 . 2264 , 2 . 3916 ) , enterotoxigenic E . coli ( ETEC ) ( LT-68 ) , extra-intestinal pathogenic E . coli ( ExPEC ) ( F11 ) , enteroinvasive E . coli ( EIEC ) ( 53638 ) ; homologs were identified among additional E . coli strains designated M605 , EC40967 , DEC6c and 541-15 . Orf60 homologs in the SF1 subfamily share 44 to 58% amino acid identity across the full length of the predicted proteins ( Figure 4 , light gray box ) . SF2 comprised homologs among EAEC ( 55989 ) , ETEC ( H10407 , and 1392/75 ) , and Shiga-toxin producing EAEC ( HUSE41 ) strains; the archetype orf60 from 042 was assigned to this SF , all members of which shared 72–100% amino acid similarity ( Figure 4 ) . Among the most noteworthy predicted proteins was ROD_02851 ( 8 . 9 kDa ) from C . rodentium , sharing 52% similarity to orf60 ( Figure 4 ) . C . rodentium is an enteric pathogen which pursues a pathogenic strategy similar to that of EPEC and STEC , and which harbors both an AggR homolog ( RegA ) and an orf60 homolog . We examined the genetic organization of the orf60 homologs among the diarrheagenic E . coli strains EAEC , ETEC , Shiga-toxin producing EAEC and C . rodentium . Unexpectively , in all the analyzed EAEC and ETEC genome sequences , four highly conserved features were found: a fimbrial operon , a dispersin-like protein , an Aat translocator system for dispersin , and an AraC family transcriptional regulator . Whereas the precise location of the genes varied , all were found to be located close to and in divergent organization up or downstream of AraC activators ( Figure 5 , A–G ) . Most interesting was the case of archetype ETEC strain H10407 [24] . This strain has been described as having two copies of cfaD/rns , which encodes the AraC homolog most closely related to AggR; one of the copies exhibits a frameshift mutation and is therefore considered to be inactive [25] . We found orf60 homologs divergently arranged in close proximity to both cfaD genes ( Figure 5 , E ) . Another ETEC strain , 1392/75 , harbors two orf60 genes , located in the p746 ( p746_052 ) and p1018 ( p1018_093 ) plasmids ( Figure 5 , F , G ) . In contrast to EAEC and ETEC , the orf60 homolog of C . rodentium was located within a predicted phage-encoded region , flanked by flagellar operon genes and the Aat translocator system ( Figure 5 , H ) . Conservation of function would presumably dictate conservation of orf60 protein structure across the family . To test this hypothesis , we assembled an alignment of orf60 family members and applied a variety of prediction algorithms to reveal the presence of conserved predicted secondary structure . PROMALS3D algorithm strongly predicted the presence of three consensus alpha helices at conserved locations in the family ( Fig . S4 ) . Several amino acid residues were highly conserved in identity or character across the family; these included a very highly conserved cysteine at position 60 in the EAEC orf60 protein . We sought to address whether orf60 homologs from other diarrheagenic strains would be able to rescue orf60 function in the 042orf60 mutant . For these experiments we chose orf60 homologs from SF1 ( C . rodentium , ROD_02851 ) and SF2 ( ETEC strain H10407 , p948_0450 and p948_1070 ) , exhibiting similarities of 52 and 80% to orf60 respectively ( Fig . 4 ) . We transformed 042orf60 with pOrf0450 , pOrf1070 , and pOrf02851; strains were grown in DMEM high glucose , then proteins and RNA were analyzed by western blot using anti-AafA antibody and qRT-PCR , respectively . AafA protein expression in 042 was completely abolished when complemented with any of the orf60 homologs ( Fig . 6B ) . Similarly , aggR expression was suppressed in strains complemented with any of the ETEC or C . rodentium orf60 homologs ( Fig . 6A ) . Thus , orf60 homologs from two different subfamilies were capable of complementing orf60 function in 042 . We hypothesized that the orf60 homologs from ETEC acted as regulators of the AggR homolog Rns/CfaD . ETEC H10407 was transformed with pOrf0450 and pOrf1070 , grown and prepared for qRT-PCR analysis as above . In the presence of the orf60 homologs , we observed significant reduction in expression of cfaD itself ( 3- to 8-fold ) , as well as the CfaD-activated fimbrial genes , cfaA ( 2- to 9-fold ) , cfaE ( 2- to 13-fold ) , cfaC ( 4- to 12-fold ) genes , and the gene encoding the dispersin-like protein CexE ( 11- to 24-fold ) ( Fig . 7 , A , B ) . Interestingly , the orf1070 gene repressed cfaD and CfaD-regulated genes more strongly than did orf0450 . We sought to determine if the orf60 homolog of C . rodentium ( ROD_02851 ) is a negative regulator of the AggR homolog RegA ( Fig . 8 ) . C . rodentium was transformed with pOrf02851K , grown and prepared for qRT-PCR analysis as above . In the absence of orf02851 , we observed a significant increase in expression of regA ( ∼10- to 12-fold ) ( Fig . 8 , B ) , as well as the genes regulated by RegA: fimbrial genes kfcC , kfcE and kfcH ( 4- to 11-fold ) ( Fig . 8 , C ) , dispersin ( ∼80-fold ) and the aat system ( 20- to 30-fold ) ( Fig . 8 , D ) . Complementation in trans down-regulated the expression of regA and RegA-regulated genes ( Fig . 8 , B , C , D ) . Of note , mutations in the Kfc pilus genes were found to demonstrate early loss of colonization by C . rodentium [11] . To examine potential effects of orf60-homolog orf02851 on virulence , groups of five mice were inoculated with the wild-type C . rodentium strain and the orf02851 mutant . Although both strains were recovered at high levels in stools collected from days 1 to 15 ( Figure 9A ) , orf02851 mutant showed sustained high levels of bacteria ( 107 to 1010 ) for more than 11 days ( day 3 to 15 ) ( Figure 9 , A ) , whereas the wild-type strain exhibited a significant decrease in bacterial shedding levels after day 12 ( Fig . 9 , A ) . Only two mice out of five were shedding the wild type strain by day 16 and 17 ( Table S3 in Text S2 ) , while high levels of bacteria were detected in feces of mice inoculated with the orf02851 mutant ( at levels of 107 to 108 per gram of stool ) ( Table S3 in Text S2 ) . Consistent with levels of shedding in the stools , we observed higher levels of challenge strain colonization in the colonic lumen in mice fed the wild type strain compared with those fed the orf02851 mutant ( Fig . 9C ) . Mice inoculated with orf02851 strain also showed greater weight loss compared to mice inoculated with wild-type ( Fig . 9B ) . Transmission electron microscopic examination of colonic tissues revealed more intense cytoplasmic vacuolization in animals infected with the mutant strain compared with wild type , accompanied by greater amounts of luminal debris ( Fig . 10 ) .
Many microorganisms utilize members of large families of regulators , presumably tailoring them to their pathogenetic idiosyncrasies . The large AraC/XylS family of gram-negative transcriptional activators is defined by a 100-amino-acid region of sequence similarity that contains two helix-turn-helix ( HTH ) DNA binding motifs [7] , [9]; a number of family members are involved in carbon metabolism , responses to environmental stress , and many serve as virulence gene regulators [7] , [9] . Several virulence-related AraC-family activators , including AggR of EAEC , have been shown to exercise autoactivation , presumably in order to assure very rapid activation of their regulons upon entry into an environment conducive to pathogenic lifestyles . Interestingly , however , for few autoactivators has a very simple engineering question been plausibly addressed: how does an autoactivator check runaway positive feedback ? Unrestrained activation could be maladaptive in terms of optimal bacterial metabolism , or could conceivably render the bacterium more virulent than is fitting for optimal persistence in the host population . For these reasons , mutations in negative feedback regulators of autoactivators could engender increased or decreased virulence . We suggest here the term Aar ( AggR-activated regulator ) to describe the orf60 gene product , and propose the term AraC-family negative regulators ( ANR ) to describe its family . The precise contribution of Aar in pathogenesis remains unknown . It could act by simply preventing excessive action of its activator partner , and/or could assure finer levels of on-demand gene expression at precise times or places in the setting of pathogenesis . Alternatively , Aar could act directly or indirectly as a virulence suppressor , perhaps to modulate virulence as a result of selection towards clinical attenuation . Our finding of increased pathogenicity in aar-negative strains in Mali and Brazil would support this latter hypothesis [15] , [16] . Although the Aar-homolog mutation in C . rodentium yielded a predicted effect ( enhanced intestinal colonization ) , it is unclear whether all Aar homologs act as virulence modulators . The mechanism by which orf60 checks aggR expression is not apparent from our analysis . Alignment of the orf60 family revealed conserved motifs: strongly predicted alpha helical structure with several highly conserved residues ( Figure S4 ) . Alpha-helical dominance is found in several DNA binding proteins [26] , suggesting that this function could be provided by orf60 . Alternatively , orf60 could bind AggR , preventing its interaction with the DNA upstream of its activated promoters . A third possibility entails action of orf60 via an intermediate regulator . These three , and other possible hypotheses are under investigation . The existence of antivirulence genes is attracting increased attention . Early work on this area suggested the loss of basic metabolic genes whose activities interfered with virulence functions ( e . g . cadA of Shigella spp . ) [27] . Some pathogens express protein effectors that act to suppress virulence , often by diminishing the inflammatory response ( e . g . Pic from Shigella flexneri ) [28] . However , to our knowledge , Aar represents the first example of a dedicated pathogen-specific attenuator of virulence genes in gram-negative bacteria . Additional investigations are required to understand the role of Aar and its homologs in the setting of disease .
Bacterial strains used in this study are shown in table S1 in Text S2 . Strains EAEC 042 , 042aggR , and 042aggR ( pBADaggR ) were previously described [18] , [29] , [30] . Bacterial cultures were routinely propagated in Luria Broth ( LB ) and Dulbecco's modified Eagle's medium with 0 . 4% glucose ( DMEM high glucose ) ( Gibco , Grand Island , NY ) as previously described [14] . Mutagenesis of orf60 in 042 and C . rodentium strain ROD_02851 was accomplished by using lambda red technology [31] . The locus ( 46 , 236–46 , 438 , GenBank FN554767 . 1 ) in 042 and ( 319 , 732–319 , 967 , GenBank NC_013716 . 1 ) in C . rodentium were replaced with the kanamycin ( km ) resistance marker as previously reported [31] . 042orf60 and C . rodentium orf02851 strains were identified by PCR using specific primers for orf60 , orf02851 and a km resistance marker ( Table S2 in Text S2 ) . We isolated a spontaneous pAA2 plasmid-cured derivative of strain 042 for use as a negative control in several assays . For the complementation of 042orf60 , plasmids pOrf60 , pOrf0450 , pOrf1070 and pOrf2851 were generated in this study ( Table S1 in Text S2 ) . Briefly , a 328-kb fragment encompassing the orf60 gene and its predicted promoter ( see Fig . S2 in Text S1 ) was amplified by PCR ( spanning nucleotides 46 , 141–46 , 433 in GenBank accession FN554767 . 1 ) , and cloned into the EcoRI and XbaI sites of pBAD30; the resulting plasmid was designated pOrf60 . pOrf60-2 was generated by removing araC and the PBAD promoter from the plasmid vector backbone ( Fig . S2 in Text S1 ) . The orf60 gene with native promoter was generated by PCR ( pACYC primers ) ( Table S2 in Text S2 ) and cloned into the HindIII/SmaI site of vector pACYC177 ( GenBank X06402 ) ( Figure . S3 in Text S1 ) . To express orf60 alleles from other bacteria , the EAEC orf60 gene was deleted by reverse PCR of pOrf60 so as to preserve the original EAEC orf60 translational start codon; the respective heterologous allele was fused downstream to assure transcription and translation at levels similar to EAEC . orf60 homologs from ETEC ( p948_0450 , genomic region 43 , 990–44 , 184 and p948_1070 , genomic region 88 , 912–89 , 109 , GenBank NC_017724 . 1 ) [32] and C . rodentium ( ROD_02851 , genomic region c319966–319733 , GenBank NC_013716 . 1 ) [33] were employed to generate plasmids pOrf0450 , pOrf1070 , and pOrf2851 respectively . For the complementation of C . rodentium orf02851 , the pOrf2851K plasmid was generated by inserting an encoding kmr marker into pOrf2851 backbone . Stop codons ( TAG ) were introduced in the three hypothetical alternative or canonical start codons for orf60 ( ( TTG-position 1 ) , 46 , 234–46 , 236; ( TTG-position 4 ) , 46 , 243–46 , 248 and ( ATG-position 5 ) , 46 , 246–46 , 248 , ( GenBank FN554767 . 1 ) ) by using the QuikChange II XL Site-Directed Mutagenesis Kit ( Agilent Technologies , CA USA ) . As a template for the mutagenesis reaction , 50 ng of pOrf60 plasmid was mixed with 125 ng of the corresponding primers ( L1F-L1R; L4F-L4R and M5F-M5R ) ( Table S2 in Text S2 ) and 2 . 5 U/µl of Pfu Turbo DNA polymerase . Samples were treated for 1 cycle/3 minutes at 95°C followed by 18 cycles of 95°C/30 seconds , 55°C/1 minute , 68°C/8 minutes . Samples were digested with DpnI for 2 h at 37°C and transformed into XL10-Gold Ultracompetent Cells ( Agilent Technologies , CA USA ) . Plasmid derivatives were designated pOrf60-M1 , pOrf60-M4 , and pOrf60-M5 respectively . All constructs were verified by nucleotide sequencing at the University of Virginia DNA Science Core . Overnight bacterial cultures of EAEC were diluted 1∶100 into 13 ml of DMEM high glucose ( aggR-inducing conditions ) , and incubated at 37°C without shaking for the times indicated . For ETEC and C . rodentium , bacterial cultures were diluted 1∶100 in 13 ml of LB or DMEM-LB broth respectively . Extraction of RNA , cDNA synthesis and qRT-PCR assays were performed as previously described [14] . Primers for EAEC were previously published [14] . Primers for ETEC and C . rodentium genes are reported in Table S2 in Text S2 . Reactions were run in experimental duplicate using two independent cDNA preparations . Expression levels for each queried gene were normalized to the constitutively expressed cat gene in EAEC 042 , rpoA in ETEC H10407 and rpoD in C . rodentium as previously described [14] , [34] , [35] . Strains were grown in LB overnight with shaking at 37°C , then diluted 1∶100 in 5 . 0 ml of DMEM-high glucose , and incubated with shaking to reach OD600 of 0 . 8 . Samples were prepared for negative staining with 2% uranyl acetate as previously described [14] . Colonic sections of mice infected with C . rodentium derivatives were analyzed by TEM . Briefly , groups of five C57BL/6 mice were inoculated with 1010 CFU of C . rodentium derivatives . Mice were euthanized at day 9 post-infection and descending colonic tissue was dissected and prepared for TEM analysis . The TEM samples were viewed on a Jeol JEM1230 Transmission Electron Microscope ( 80 kV ) at the Advanced Microscopy Laboratory at the University of Virginia ( AML-UVA ) . For detection of EAEC Aggregative Adherence Fimbriae II ( AAF/II ) , strains were grown in 13 ml of DMEM high glucose to reach an OD600 of 0 . 8 . Bacteria were pelleted , resuspended in 100 µl of 0 . 5 mM Tris , 75 mM NaCl and heated for 30 min at 65°C . The major pilin subunit of AAF/II ( AafA ) was analyzed in the supernatant by SDS-PAGE and Western blot analysis . For detection of orf60 protein , outer membrane ( OM ) and cytoplasmic/periplasmic ( C/P ) fractions of E . coli 042orf60 and 042orf60 ( pOrf60 ) were prepared as described [36] . Protein samples were separated in acrylamide gels and transferred to Immobilon-P membranes ( BioRad , Hercules CA , USA ) by using standard protocols . The membranes were incubated overnight with anti-AafA or anti-orf60 antibodies respectively . The next day , the membranes were washed twice in PBS-0 . 1% tween , and incubated for 1 h with a horseradish peroxidase-conjugated goat anti-rabbit IgG antibody . Membranes were developed by using TMB Membrane peroxidase substrate ( KPL , Gaithersburg , MD , USA ) following the manufacter's specifications . Fibronectin-binding was assessed as previously reported [17] . The autoaggregation assay was performed as previously described ( 13 ) . Hypothetical proteins were analyzed by using Clustalw algorithms ( http://www . genome . jp/tools/clustalw/ ) . Protein mass , secondary structure and similarity was determined in predicted proteins by using bioinformatic tools ( http://www . bioinformatics . org/sms/prot_mw . html , http://www . ch . embnet . org/software/LALIGN_form . html and http://prodata . swmed . edu/promals3d/promals3d . php . −35 and −10 regions of the Porf60 promoter were predicted by using Bprom algorithm ( http://linux1 . softberry . com/cgi-bin/programs/gfindb/bprom . pl ) . Statistical analysis of the data for fibronectin binding , fecal shedding and gene expression was performed by using the GraphPad Prism 6 ( GraphPad Software , Inc . , CA , USA ) . The statistical significance of the differences in the sample means was calculated by using ANOVA with post hoc Tukey's correction . Results were considered significant at P<0 . 05 . All animal work has been conducted according to relevant national and international guidelines . Four to five week old male C57BL/6 mice were inoculated with 200 µl of a bacterial suspension containing 1010 CFU in PBS using a feeding needle . The mice were weighed daily and fecal pellets were collected aseptically from each mouse . The number of viable bacteria per gram of feces was determined by plating serial dilutions of the samples onto media containing appropriate antibiotics . For bacterial colonization , groups of 8–10 mice were inoculated with containing 1010 CFU in 200 µl PBS . Mice were euthanized at day 9 post-infection and bacteria in the large intestinal lumen was quantified as described above . Animal experiments were performed in accordance with the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health and with the permission of the American Association for the Assessment and Accreditation of Laboratory Animal Care . The protocol was reviewed and approved by the Institutional Animal Care and Use Committee of the University of Virginia ( Protocol No . 3894 ) . Presented are database accession numbers for genes identified by BLAST search and presented in Fig . 4 . Numbers are listed in order of similarity to orf60 from strain 042: gi|387604910 , YP_006099179 . 1; gi|218511215 , |YP_002415673 . 1; gi|386283102 , ZP_10060736 . 1; gi|387610422 , YP_006203859 . 1; gi|387610470 , YP_006203907 . 1; gi|299836136 , YP_003717705 . 1; gi|417835927 , ZP_12482356 . 1; gi|298206490 , YP_003717592 . 1; gi|419923404 , ZP_14441355 . 1; gi|417147810 , ZP_11988310 . 1; gi|215487703 , YP_002330134 . 1; gi|283784065 , YP_003363930 . 1; gi|417264971 , ZP_12052353 . 1; gi|419153984 , ZP_13698552 . 1; gi|417251191 , ZP_12042956 . 1; gi|417259639 , ZP_12047171 . 1; gi|191174000 , ZP_03035517 . 1; gi|419137699 , ZP_13682492 . 1; gi|417150722 , ZP_11990461 . 1; gi|331648301 , ZP_08349390 . 1; gi|417166561 , ZP_11999917 . 1; gi|260845240 , YP_003223018 . 1; gi|419216701 , ZP_13759700 . 1; gi|417624551 , ZP_12274849 . 1; gi|188493508 , ZP_03000778 . 1; gi|419301338 , ZP_13843337 . 1; gi|415811870 , ZP_11504183 . 1; gi|417615862 , ZP_12266306 . 1; gi|270315363 , gb|EFA27649 . 1; gi|338217140 , gb|EGP03044 . 1; gi|341952232 , gb|EGT78764 . 1; gi|341956103 , gb|EGT82542 . 1; gi|347813358 , gb|EGY30032 . 1; gi|348653724 , gb|EGY69408 . 1; gi|359755683 , gb|EHK89847 . 1; gi|386908035 , gb|EIJ72734 . 1; gi|145634275 , ZP_01789986 . 1; gi|145635267 , ZP_01790971 . 1; gi|145635897 , ZP_01791585 . 1; gi|229844281 , ZP_04464421 . 1; gi|261492133 , ZP_05988704 . 1; gi|261493480 , ZP_05990003 . 1; gi|261495320 , ZP_05991771 . 1; gi|329122764 , ZP_08251338 . 1; gi|329124231 , ZP_08252775 . 1; gi|343518941 , ZP_08755927 . 1; gi|359299044 , ZP_09184883 . 1; gi|386389116 , ZP_10073947 . 1; gi|387770888 , ZP_10127061 . 1; gi|398801995 , ZP_10561225 . 1
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We report here the identification and characterization of a new family of negative regulators in Gram-negative bacteria , including many pathotypes of diarrheagenic Enterobacteriaceae and members of the Pasteurellaceae . Members of this regulator family in enteroaggregative ( EAEC ) and enterotoxigenic E . coli ( ETEC ) and in Citrobacter rodentium downregulate the expression of positive regulator partners AggR , CfaD/Rns and RegA , respectively , all members of the AraC/XylS family of regulators . Accordingly , we propose the name ANR ( AraC Negative Regulators ) for this family . ANR members orf60 ( termed Aar ) , orf02851 ( Rnr ) , orf0450 and orf01070 ( Cnr ) from EAEC , C . rodentium and ETEC respectively were characterized in this study . Deletion of ANR homologs upregulated the expression of AggR and RegA in EAEC strain 042 and C . rodentium respectively; overexpression of orf60 , orf02851 , orf0450 and orf01070 in EAEC strain 042 down-regulated AggR . C . rodentium harboring a null mutation in orf02851 exhibited a significant increase in expression of the regA and RegA-regulated fimbriae . The orf02851 mutant showed higher levels of C . rodentium in feces and colonic contents , and greater weight loss compared to mice inoculated with the wild-type .
|
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"bacteriology",
"escherichia",
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2014
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A Large Family of Antivirulence Regulators Modulates the Effects of Transcriptional Activators in Gram-negative Pathogenic Bacteria
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In some tropical countries , such as Brazil , schistosomiasis control programs have led to a significant reduction in the prevalence and parasite burden of endemic populations . In this setting , the Kato-Katz technique , as the standard diagnostic method for the diagnosis of Schistosoma mansoni infections , which involves the analysis of two slides from one fecal sample , loses its sensitivity . As a result , a significant number of infected individuals are not detected . The objective of this study was to perform extensive parasitological testing of up to three fecal samples and include a rapid urine test ( POC-CCA ) in a moderate prevalence area in Northern Minas Gerais , Brazil , and evaluate the performance of each test separately and in combination . A total of 254 individuals were examined with variants of the standard Kato-Katz technique ( up to18 Kato-Katz slides prepared from three fecal samples ) , a modified Helmintex ( 30 g of feces ) , the saline gradient ( 500 mg of feces ) , and the POC-CCA methods . We established a reference standard taking into consideration all the positive results in any of the parasitological exams . Evaluation of the parasite burden by two Kato-Katz slides confirmed that most of the individuals harbored a light infection . When additional slides and different parasitological methods were included , the estimated prevalence rose 2 . 3 times , from 20 . 4% to 45 . 9% . The best sensitivity was obtained with the Helmintex method ( 84% ) . All parasitological methods readily detected a high or moderate intensity of infection; however , all lost their high sensitivity in the case of low or very low intensity infections . The overall sensitivity of POC-CCA ( 64 . 9% ) was similar to the six Kato-Katz slides from three fecal samples . However , POC-CCA showed low concordance ( κ = 0 . 34 ) when compared with the reference standard . The recommended Kato-Katz method largely underestimated the prevalence of S . mansoni infection . Because the best performance was achieved with a modified Helmintex method , this technique might serve as a more precise reference standard . An extended number of Kato-Katz slides in combination with other parasitological methods or with POC-CCA was able to detect more than 80% of egg-positive individuals; however , the rapid urine test ( POC-CCA ) produced a considerable percentage of false positive results .
Recent estimates of helminth infections indicate the existence of more than one billion infected individuals in underdeveloped areas of Africa , Asia , and in Central and South America [1] . Among the different trematode species infecting humans , schistosome species are the parasites with the highest impact on public health , affecting more than 240 million individuals and with 700–800 million people living at risk of infection [2–4] . In sub-Saharan Africa , approximately 280 , 000 deaths per annum have been attributed to schistosome infections and their clinical complications [5] . In Brazil , the only schistosome species transmitted among the human population is Schistosoma mansoni and estimates vary between 1 . 5 and 6 million infected individuals [1 , 6 , 7 , 8 , 9] . Since the implementation of the National Schistosomiasis Control Program ( NSCP ) in the 1970s and decades of consequent chemotherapeutic interventions , the Brazilian health authorities reported significant improvements in terms of transmission , prevalence , and parasite load in the country’s endemic regions , especially in the states of Minas Gerais and Bahia [10] . In this new epidemiological scenario , most of the infected individuals in endemic areas harbor low parasite loads and are very unlikely to be detected with the commonly used parasitological methods [11 , 12] . The Kato-Katz method ( KK ) [13] is recommended by the World Health Organization ( WHO ) as the standard method for the detection of S . mansoni infection [14–16] . It is very efficient in individuals with high to medium parasite loads , e . g . more than 100 eggs per gram of feces , but shows reduced sensitivity in individuals with low parasite loads . As a consequence , the real prevalence in an endemic setting may be significantly underestimated and that has led to shortcomings in the control of schistosomiasis in these areas [17–20] . An important result of the NSCP was a significant reduction in the number of severe clinical cases and deaths due to S . mansoni infection [21 , 22] . However , the failure to correctly identify all or most of the individuals with low parasite burden by the standard parasitological approach ( 1 or 2 KK slides ) has contributed to the continuation of S . mansoni infection , with accompanying contamination of the environment , especially the water bodies , and hence , allow reinfection in endemic areas . Therefore , if new WHO guidelines about the elimination of schistosome infections in the world are sought to be achieved [16] , new and more sensitive methods , apart from the standard KK test , will have to be applied . Due to the reduced performance of the KK method for the diagnosis of S . mansoni infection in areas with low endemicity , new parasitological methods have been developed such as saline gradient [23] and Helmintex [24] . Even immunological methods have been re-evaluated in order to improve detection of S . mansoni infection in endemic populations [25–27] . As an alternative to enhance the specificity of immunological methods for the diagnosis of schistosome infections , some assays focus on the detection of parasite-secreted antigens in serum or urine samples of infected individuals [28] . Indeed , circulating cathodic antigens ( CCA ) of S . mansoni are released into the circulation by juvenile and adult schistosomes and the levels of these antigens correlate with the worm burden , thus indicating active infection [29–31] . Based on these initial studies , a rapid antigen test , the Point-of-Care-CCA rapid test ( POC-CCA ) was developed and is commercially available . It detects the circulating antigen in urine samples and has a higher sensibility than the standard KK method when it was evaluated in schistosomiasis endemic areas in Africa [32–35] . However , most of these studies were restricted to Africa and they only compared the POC-CCA reactivity in urine samples with parasitological results obtained with the standard KK method and using this method as the reference standard [36] . Since the KK method is not sensitive enough to identify individuals with low parasite burden and serve as a ‘gold standard’ , the real efficiency of the POC-CCA to detect S . mansoni infection in endemic populations remains to be validated in relation to more sensitive parasitological , molecular , and serological methods . In the present study , we performed a combination of alternative parasitological methods to detect more precisely intestinal schistosomiasis in an endemic area in Brazil . The thorough parasitological investigation allowed us to implement a new reference standard to detect active S . mansoni infection and to evaluate each of the parasitological methods for its performance and accuracy . Moreover , we analyzed the potential of POC-CCA rapid urine test as an alternative for time-consuming parasitological exams in detecting individuals with low parasite burden commonly found in endemic areas subjected to long-term chemotherapeutic interventions .
The present study was approved by the Ethics Committee of the Research Center René Rachou—FIOCRUZ and all project details have been registered on the Brazilian Platform for Research with Human Subjects ( Plataforma Brasil ) under the following number: CAAE#21824513 . 9 . 0000 . 5091 . Before any research activities , the local health authorities were contacted and agreed to collaborate with the researchers from the different institutions . All enrolled participants were required to sign an informed consent form . Parents or legal guardians signed the informed consent when minors were involved . When the parasitological results were positive , the relevant individuals were informed and received free oral treatment at the local health clinic . Schistosomiasis: praziquantel ( 40 mg/kg for adults and 60 mg/kg for children ) ; intestinal helminths: albendazole ( 400 mg ) ; protozoan parasites: metronidazole ( 250 mg/2x/ 5 days ) . The study was conducted in a rural area of the district of Brejo do Amparo , Municipality of Januária ( S1 Fig Supplemental Information ) , located in the northern part of Minas Gerais State , Brazil , approximately 600 km from the capital Belo Horizonte . The community is located along the margins of the Tocantins brook and consists of roughly 270 individuals in total . In local meetings and house-to-house visits , the project was explained to all interested inhabitants , and stool exams were offered . A family-based socio-economic questionnaire was applied to gather information on household construction , water supply , sanitation , and other socio-economical aspects . Also , an individual questionnaire was used to record demographic and occupational information and to indicate previous clinical conditions that might be relevant for the research . Based on past interventions carried out by the local health authorities responsible for schistosomiasis control , a prevalence of S . mansoni infection between 15–20% was expected in this area . According to these authorities , no schistosomiasis control interventions had been performed in the localities during the last two years before the beginning of the present study . Participants were asked to provide a urine sample and three fecal samples , which were collected on consecutive days . Fecal samples were brought to the field laboratory in Januária to be processed by the different parasitological methods . The flow diagram in Fig 1 shows the total number of samples analyzed by each parasitological test and the results obtained with the rapid urine test ( POC-CCA ) . At least 50 grams of feces were collected with the first fecal sample using a 500 ml plastic container , which is sufficient for a complete fecal evacuation . The fecal samples collected in the following days were small and , therefore , 80 ml plastic cups were used . Variants of the standard KK technique [13] were perfomed by preparing 14 slides with the first fecal sample and two slides for the second , and third samples . Slides were examined under the microscope ( 100x ) for the presence of S . mansoni eggs and other intestinal helminths . The exams were conducted by experienced microscopists at the Centro de Pesquisas René Rachou and the Universidade Federal de Minas Gerais . At least 15% of all slides had their reading confirmed by a second microscopist , after random selection . The intensity of infection was calculated by determining the mean number of S . mansoni eggs found in each slide and multiplying the mean obtained by 24 to determine the number of eggs per gram of feces ( EPG ) . According to the World Health Organization [14] , the intensity of S . mansoni infection can be categorized as light ( 1–99 EPG ) , moderate ( 100–399 EPG ) , or heavy ( ≥400 EPG ) . The spontaneous sedimentation method [37] was used to evaluate the presence of protozoan parasites in fecal samples . Next , a subsample was taken from the first fecal sample and processed following the saline gradient technique and a modified Helmintex method . For the saline gradient method [23] , a suspension of 500 mg of feces was subjected to a slow flow of a 3% saline solution during one hour . Subsequently , the supernatant was removed and the sediment was placed onto microscope slides to search for S . mansoni eggs . The modified Helmintex method was performed as described by Favero and colleagues [38] . Briefly , 30 grams of feces from the first fecal sample were suspended in 70% ethanol , treated with detergent ( Tween-20 ) , subjected to repetitive filtration and sedimentation steps , the addition of a solution with magnetic particles , and the separation of S . mansoni eggs using a magnetic field . Finally , the free suspension was discarded and the attached particles , which formed the final sediment , were mixed with 3% ninhydrin solution and transferred onto microscope slides to search for S . mansoni eggs [38] . As mentioned above , each participant was also asked to provide a urine sample to perform the rapid urine test ( POC-CCA , Rapid Medical Diagnostics , Pretoria , South Africa ) and detect the circulating cathodic antigen of S . mansoni . To this end , first-morning urine samples were collected , transferred to the field laboratory in Januária , aliquoted in 10–15 ml samples , and stored at -20°C until further testing . The test followed the manufacturers’ guidelines , and was read 20 minutes after addition of the urine sample and buffer solution . Test results were scored as negative if the circulating cathodic antigen band was absent . Positive results were scored as trace ( very light band ) , weak ( + ) , medium ( ++ ) and strong ( +++ ) depending on the intensity of the circulating cathodic antigen band [28 , 39] . Cases with trace results for the circulating cathodic antigen of S . mansoni were considered as positive . The tests were scored independently by two investigators . In case of conflicting results , a third investigator was consulted . Analyses were performed using Open Epi , version 3 . 03 and GraphPad Prism , version 5 . 0 . In order to evaluate the performance of the different diagnostic tests , a “Reference Standard” was established , which included all positive results ( visible eggs ) from any of the parasitological methods used ( 18 KK slides , saline gradient , and Helmintex ) . Normal distribution of the data was verified by the Shapiro-Wilk test . For non-parametric data and categorical variables , the Chi-square test was used . To compare the means for continuous variables , the Manny-Whitney U-test and Kruskal-Wallis test were used , with a p-value ≤ 0 . 05 considered significant . The overall prevalence of S . mansoni infection in the endemic area was calculated by the number of egg-positive individuals found in any of the parasitological exams , as defined by the “Reference Standard” , divided by the total number of participants . To compare the performance and accuracy of each method , we calculated the sensitivity , specificity , positive ( PPV ) and negative predictive values ( NPV ) , and concordance ( kappa index ) . To evaluate the degree of concordance between the different methods , the kappa index ( κ ) , which varies from 0 to 1 . 0 , followed the following categorization: no agreement if κ<0 . 01; bad if 0 . 01≤κ≤0 . 20; weak if 0 . 21≤κ≤ 0 . 40; moderate if 0 . 41≤κ≤0 . 60; good if 0 . 61≤κ≤0 . 80 , and excellent agreement if κ>0 . 81 [40] . The relationship between the intensity of infection , as determined by the mean EPG value of two slides from the first fecal sample and the semi-quantitative intensity of POC-CCA results was examined by the Spearman’s rank correlation test .
As shown in Table 1 , the parasitological study included 257 individuals , of which 122 were male ( 47 . 5% ) and 135 female ( 52 . 5% ) . Age of the participants ranged from 2–88 years , with a mean age of 34 . 9 years ( SD ±22 . 6 ) and a median age of 32 years ( interquartile range 15–51 years ) . The number of individuals was equally distributed throughout the different age groups . The study population was of low income and educational level: 90% of adult individuals earned minimum Brazilian wages , and almost 80% had only elementary education or less . The primary drinking water source is the local brook ( 60% of the residences ) and the domestic sewage receives no treatment . The initial fecal analyses performed with the saline gradient and the standard KK ( two slides ) methods revealed that 85 individuals were positive for protozoan cysts and 81 individuals eliminated helminth eggs in the fecal samples ( Table 2 ) . The most prevalent helminthic infections were intestinal schistosomiasis ( 20 . 4% ) and hookworm ( 9 . 8% ) . The mean number of S . mansoni eggs in infected individuals was 210 ± 645 . 8 EPG . Among these 48 infected individuals , most ( 66 . 7%; n = 32 ) had a low parasite load of less than 100 EPG , 25% ( n = 12 ) had a moderate infection , and 8 . 3% were heavily infected ( Fig 2A ) . There was no statistically significant association between the prevalence and the intensity of schistosomiasis with gender . Also , the intensity of S . mansoni infection was similar among individuals of different age groups ( Fig 2B ) . To evaluate the sensitivity of the technique recommended by the WHO ( two KK slides from one fecal sample ) and other parasitological tests to identify S . mansoni infection , we performed thorough parasitological examinations using three fecal samples . Moreover , urine samples collected from the participating individuals were tested for the circulating cathodic schistosome antigen using the rapid urine test ( POC-CCA ) , as described above . The inclusion of additional parasitological methods for schistosome diagnosis resulted in the detection of a much higher number of infected individuals within the study population ( Table 3 ) . The apparent prevalence rose from 20 . 4 to 29 . 9% , when the number of KK slides was increased from two to 14 slides , or to 38 . 3% , when we used two slides prepared from each of the three fecal samples . Other parasitological methods that used a higher amount of fecal matter , such as the saline gradient and Helmintex , also detected a higher number of S . mansoni-infected individuals ( Table 3 ) . Overall , and taking into consideration the results of all the parasitological methods ( reference standard ) , the prevalence of intestinal schistosomiasis reached 45 . 9% , which represents a 2 . 3 times increase in relation to the WHO’s recommended standard KK procedure . The reference standard was used to evaluate the efficacy of each of the diagnostic methods tested . For the fecal techniques , the best performance was obtained with the modified Helmintex method , which identified schistosome eggs in feces of 88 individuals ( 40 . 4% of prevalence ) . This parasitological method showed a high sensitivity ( 86 . 6% ) and the highest degree of concordance in relation to the reference standard ( kappa = 0 . 84 ) ( Table 3 ) . The analysis also demonstrated that the sensitivity of the KK method increased from 41 . 4% with two slides from one fecal sample to up to 66 . 7% with six slides from three fecal samples . In comparison , if only one fecal sample was processed , the sensitivity remained around 60% , even when the number of examined slides was increased to 12 or 14 ( Table 3 and Fig 3 ) . The improved performance of the KK method due to an increased number of examined slides ( 14 slides ) or increased sampling effort ( three fecal samples ) is shown in Fig 3 . Fig 4 shows the prevalence of S . mansoni infection for the different age groups and as a function of the parasitological methods , e . g . the standard KK method ( 2 slides from one fecal sample ) versus the reference standard ( 18 Kato-Katz slides , saline gradient , and Helmintex ) . Using the reference standard , we found that children and young adults ( 11–20 years of age ) had the highest prevalence ( 55% ) for S . mansoni infection . In contrast , the prevalence was reduced to less than 50% in the other age groups , being further reduced in the elderly ( older than 60 years of age ) . Importantly , the prevalence found in each age group , considering the combination of all parasitological exams ( reference standard ) , was 1 . 7 to 4 . 7 times higher than the prevalence obtained with the recommended two KK slides from one fecal sample ( Fig 4 ) . The parasite load in S . mansoni infected individuals was determined by counting the eggs found in two KK slides from one fecal sample and converting the counts in eggs per gram of feces ( EPG ) , according to standard procedures recommended by the WHO [14] . We assigned an EPG value of 1 for the individuals who were not detected by two KK slides , but who were found positive when additional slides were analysed or when other fecal exams were used . Thus , we classified 102 individuals with a light parasite load ( EPG: 1–99 ) , 12 individuals with a moderate parasite load ( EPG: 100–399 ) , and four individuals with a heavy parasite load ( EPG: 400 or more ) . Therefore , most of the infected individuals within the studied population had a light parasitic infection . Next , we analyzed the performance of the parasitological methods in relation to the parasite load , with the individuals with a light infection being arbitrarily divided into three subgroups ( Table 4 ) . All the diagnostic methods readily detected individuals with heavy to moderate infections . On the other hand , the diagnostic methods decreased their sensitivity to detect individuals with a low parasite load , especially in fecal samples with less than 12 EPG . In this case , the best performance of the KK method ( SPL1-3 K1-K2 ) reached a sensitivity of only 40% . In the group with a very low parasite load , the saline gradient and the rapid urine test had sensitivities of 33 . 9 and 50 . 8% , respectively . The Helmintex method showed the highest sensitivity for the group with very low parasite load ( 84 . 1% ) . The POC-CCA identified 108 out of a total of 228 individuals as infected , which resulted in a prevalence of 47 . 4% and a sensitivity of 64 . 9% , when compared with the reference standard ( 18 Kato-Katz slides , saline gradient , and Helmintex ) . The sensitivity of the POC-CCA was superior to the saline gradient and comparable to the results obtained with six KK slides from three fecal samples . However , the kappa index of the urine test was considerably lower than that obtained with the other parasitological tests ( Table 5 ) . The performance of the POC-CCA is illustrated in Fig 5 . The visual scores ranged from negative to trace , weak ( + ) , moderate ( ++ ) , and strongly positive ( +++ ) , with trace results considered a positive reaction for S . mansoni infection , as recommended by the manufacturer ( Fig 5A ) . Comparing the POC-CCA result with the other parasitological analyses , we observed that , of the 139 negative individuals in the parasitological tests , only 116 participants provided urine samples for the POC-CCA test . Of these individuals , 81 ( 70% ) were also found not reactive ( negative ) in the urine test . However , 33 urine samples ( 28% ) from the individuals found negative by the other parasitological tests showed a trace reaction and another two samples ( 1 . 7% ) of parasitologically negative individuals had a weak positive result ( + ) ( Fig 5B ) . Among these 35 individuals , only four ( 11 . 4% ) individuals had a hookworm infection and eight ( 22 . 9% ) individuals presented with protozoan cysts in their feces . From 118 individuals found positive for S . mansoni eggs in any of the parasitological exams ( reference standard ) , 112 participants provided urine samples . Out of these 112 samples , 73 ( 65% ) were tested positive for the circulating cathodic antigen of S . mansoni and were in agreement with the results of the other parasitological exams . The results were classified as trace , weak ( + ) , medium ( ++ ) , or strongly positive ( +++ ) in 43 ( 38% ) , 17 ( 15% ) , 10 ( 9% ) , and three ( 3% ) of the examined urine samples , respectively ( Fig 5B ) . In contrast , 39 urine samples ( 35% ) from egg-positive individuals were not reactive in the urine test and , therefore , were misclassified as uninfected ( false negatives ) . Interestingly , the mean EPG value from these missclassified individuals was considered as very low ( mean EPG: 4 . 3; minimum: 1 EPG , maximum: 36 EPG ) . Out of the 73 samples that were positive according to the reference standard and in the POC-CCA , 59 ( 81% ) , 10 ( 14% ) , and four ( 5% ) individuals were considered to have a light , moderate or high parasite load , respectively . A significantly positive correlation was found between the scores of the POC-CCA and intensity of infection , as determined by individual EPG values ( R = 0 . 537; p = 0 . 0001 ) . The agreement between POC-CCA and the reference standard , as the sum of all parasitological exams , showed a low concordance ( κ = 0 . 34 ) , which was even lower when trace results in the urine test were considered as a negative result ( κ = 0 . 25 ) ( see also Table 5 ) . Since the KK method is the recommended technique for the diagnosis of intestinal schistosomiasis [14] , we compared the combination of more KK slides and fecal samples with the modified Helmintex method , saline gradient , and the rapid urine test ( POC-CCA ) . The combination of two KK slides from one fecal sample ( 1SPL K1-K2 ) with Helmintex or of six slides from three fecal samples ( SPL1-3 K1-K2 ) with POC-CCA resulted in the highest prevalence rates ( 45 . 4% and 60 . 3% ) and highest sensitivity rates ( 90 . 0% and 88 . 3% ) ( Table 6 ) . Looking for easily applicable diagnostic methods with improved sensitivity for epidemiological studies , we found that the combination of the KK method with the POC-CCA test produced better results when the number of slides and fecal samples was increased ( Table 6 ) .
Human schistosomiasis is still considered a parasitic infection with global health impact as it affects about 250 million people in 78 countries and more than 700 million individuals are estimated to live at risk of infection [3 , 4 , 16] . In the Americas , the only schistosome species is S . mansoni and recent estimates indicated about 1 . 8 million infected individuals and approximately 25 million people living at risk of infection , with most of the cases occurring in Brazil [9] . In Brazil , transmission of schistosomiasis occurs in 19 states with a larger presence in the northeastern states as well as Minas Gerais , and Espírito Santo [41] . Recent data released by the Brazilian Ministry of Health in 2012 indicated a positivity rate of 4 . 5% of examined individuals residing in the endemic areas covered by the National Program for Schistosomiasis Control [42] . The large-scale parasitological screening , individual diagnosis , and ongoing treatment with praziquantel promoted by the NPSC led to a considerable reduction of infection rates , severe clinical cases , and transmission of S . mansoni in endemic areas [21 , 42] . For field-based diagnosis , the recommended tool for the detection of intestinal schistosomiasis is the KK thick-smear method [13] , which detects schistosome eggs in two KK slides from one fecal sample [14] . However , it has been shown , in different endemic settings , that this technique is not sensitive enough to detect schistosomiasis in individuals with low parasite burden [17 , 25 , 43–47] , being even less sensitive when only one KK slide was examined , as usually occurs during the interventions promoted by the NPSC [12 , 19 , 20] . Thus , the Brazilian Ministry of Health recommends the examination of a higher number of KK slides in areas where the parasite burden is supposed to be low [42] . In the present study , we tested the sensitivity of an increasing number of KK slides using up to three fecal samples and compared its performance with other parasitological methods in an area endemic for intestinal schistosomiasis . By performing thorough parasitological exams , we aimed to get close to the ‘real’ picture of S . mansoni infections in this endemic region , which is located within the area of action of the NSPC , but had not suffered any intervention in the two years before the beginning of the present study . The diagnostic effort presented herein allowed us to evaluate different parasitological methods in the light of a strong reference standard , uniquely defined in this study . Most of the population from the rural area studied herein had no adequate water supply and sanitation . While waterborne protozoan infections were common , other intestinal helminth infections were less frequent . S . mansoni infection was initially estimated to be 20 . 4% , after examination of two KK slides from one fecal sample , which led the area to be classified as with moderate risk of infection [48] . The classification of infected individuals according to their parasite load [14] confirmed that two thirds of the initially diagnosed individuals harbored a light S . mansoni infection and less than 10% had a heavy infection . After performing additional KK slides and other parasitological methods , the prevalence rose to 45 . 9% , which represented a 2 . 3 times increase when compared with the initial exams and indicated nearly half of the examined population as infected . As revealed by previous studies in areas of low transmission of S . mansoni [12 , 19 , 20 , 25] , the prevalence of infection for this parasite in the area studied herein was largely underestimated when only the standard KK method was used . The prevalence profile for intestinal schistosomiasis in different age groups revealed herein matched that from other studies [4 , 49 , 50] . However , if the standard method of two KK slides was compared with our reference standard ( 18 KK slides + saline gradient + Helmintex ) , we identified up to 4 . 7 times higher prevalences in the different age groups . This is in line with results published previously [19 , 20] , showing that an increase in the number of examined KK slides considerably augmented the number of egg-positive individuals . However , and this goes beyond the already existing data on the evaluation and performance of multiple KK slides , we showed that even using the superior version of the KK technique , which involves analyzing two slides from three different fecal samples , we still missed more than one third of the infected population . Besides the KK technique , the other parasitological tests composing our reference standard included a saline gradient using 500 mg of fecal matter from the first fecal sample [23] and performed modified Helmintex method [38] , which used up to 30 grams of feces . Using these methods , a considerable number of additional egg-positive individuals were detected , with the Helmintex method presenting the best performance and a sensitivity of over 80% . Initially , the Helmintex method was described of being 30 times more sensitive than the standard KK method [24] , which is mainly due to the high amount of examined fecal matter , the successive sieving and concentration processes and the separation and distinction of eggs by paramagnetic beads and additional staining methods in the modified version [38] . A study investigating a low transmission area in the northeast of Brazil using the Helmintex method showed similar results to ours published [51] . However , it has to be emphasized that , in the present setting , none of the parasitological methods tested herein was able to detect eggs in every positive sample . In this context it is interesting to note , that in seeding experiments with 30 grams of feces , the recovery of schistosome eggs in fecal samples processed by the Helmintex method was about 27% , only [38] . Further , it was not the aim of the study to evaluate and compare the different methods in terms of applicability in field surveys , as well as operational , personnel , and logistics and other factors that influence their implementation , as stated by others [19 , 52–54] . An interesting alternative to the time consuming and labor intensive parasitological methods are rapid immunochromatographic tests for circulating antigens . Therefore , we included the commercialized rapid urine test ( POC-CCA ) [28] in our study and evaluated it in comparison with our parasitological reference standard The POC-CCA has shown promising results for the detection of intestinal schistosomiasis in various settings in Africa and Asia [32–34 , 55 , 56] . When the S . mansoni egg-positive individuals tested herein were classified according to their parasite load , the parasitological tests and the POC-CCA readily detected the individuals with heavy or moderate infections . In contrast , all tests ( parasitological and the POC-CCA ) showed reduced sensitivities when individuals with a low ( 99–12 EPG ) or very low ( less than 12 EPG ) parasite load had to be detected . Especially in the case of very low parasite load , the KK technique , at its best , only detected 40% of the infected individuals . In the case of the individuals with very low parasite load , the POC-CCA and the Helmintex methods showed the best performance with sensitivities of more than 50 and 84% , respectively . The rapid urine test ( POC-CCA ) has been successfully tested in different regions of Africa and Asia [32 , 34 , 56–58] and there are initiatives which favor this test for screening and mapping of intestinal schistosomiasis and improve transmission control and the elimination of schistosomiasis [59 , 60] . However , the epidemiological situation of intestinal schistosomiasis in most areas in Brazil is different from that found in many endemic settings in other tropical countries . This is probably because the country has a national program for schistosomiasis control since the 1970s with regular intervals of diagnosis and treatment rounds in endemic populations . Data from the Brazilian Ministry of Health [42] and risk mapping of schistosomiasis in the country [61–63] indicated a considerable decrease in infection rates and high prevalence risk areas with ongoing interventions [42 , 63] . However , these claims might be overly optimistic since they are based on data from one KK slide from one fecal sample . In any case , according to the government-published data , as a result of the NPSC interventions , the parasite burden , significant morbidity , and mortality rates decreased during the last two decades [42] . We evaluated the performance of POC-CCA and compared it with the reference standard to detect S . mansoni infection in individuals of a community where NPSC’s interventions including varying rounds of treatment had been promoted . The POC-CCA showed a sensitivity of approximately 65% , which is superior to that obtained with the saline gradient method , comparable with the results obtained with KK variant using six KK slides from three fecal samples , and inferior to the sensitivity found with Helmintex , when the criteria of evaluation were used as indicated by the manufacturer that is , if ‘trace’ was considered a positive result . A similar result for the sensitivity of POC-CCA and comparison with the performance of multiple KK smears was obtained in an endemic area in Africa [64] . In our study , the main shortcoming of the rapid urine test ( POC-CCA ) was a low concordance with the reference standard , since we found 30 and 35% of false positive and false negative results , respectively . This low concordance for the rapid urine test was not observed in other studies where parasitological efforts for detection of schistosome eggs in feces were far less rigorous [35 , 65] . Also , the discrepancy might be partially explained by the discontinuous distribution of eggs in the fecal matter , intermittent egg excretion , a small number of female worms , or by occult infections with just one sex or aging worms . This is somewhat expected in elderly individuals since they rarely visit contaminated water streams and are , therefore , less prone to reinfection [32 , 43 , 46 , 66 , 67] . If ‘trace’ was not considered as positive , then the specificity increased to more than 98% , but the sensitivity dropped to less than 27% , which we consider insufficient for a screening method . In a recent study , the performance of POC-CCA was compared with that of a KK test with two slides of one fecal sample , as recommended by WHO , and without further extensive parasitological testing [65] . Even in that experimental setting , without a strong reference standard , the rapid urine test had a considerable percentage of false positive results , and that occurred even for individuals from an area considered as non-endemic for schistosomiasis . Additionally , 14% were classified as negative by the urine test , but these were proven to be positive during parasitological exams [65] . Previous studies have reported cross-reactivity between schistosomes and other intestinal helminths or other clinical conditions that can lead to a false positive POC-CCA result [68–70] . However , we were not able to correlate any intestinal protozoan or helminth infection with a ‘trace’ or positive POC-CCA result . In order to improve the performance of POC-CCA test and elucidate the situation of individuals who were tested as ‘trace’ , prior concentration of urine by lyophilization significantly improved the concordance of the test in individuals with low parasite burden [70] . Also , recent investigations on the specificity and sensitivity of methods for the detection of circulating anodic antigen ( CAA ) from schistosomes seem to be even more promising [71–74] . To reach a maximum sensitivity and specificity and indicate alternatives for schistosomiasis control programs , we tried to combine the standard KK method and different modifications of this technique with the other parasitological methods or the POC-CCA . The best KK variant tested herein ( six slides prepared from three fecal samples ) achieved a sensitivity of 82 , 88 , and 94% when combined with the saline gradient , POC-CCA or Helmintex methods , respectively . Whether any of these scenarios is applicable to large-scale national control programs has to be carefully evaluated , considering logistic and economic aspects [54] . In any case , maybe a first parasitological test has to be combined with a second more specific test for schistosomiasis in order to join efforts against soil-transmitted helminthiasis and schistosomiasis [54 , 59 , 75] . Further , we believe that in areas of low endemicity or low intensity infections , serology or molecular biology , as proposed elsewhere [11 , 25 , 76–78] , might be valuable alternatives to be included as additional diagnostic procedures . We are currently investigating the performance of molecular biological methods and serology in the parasitologically well-defined population studied herein . In conclusion , we showed that in endemic areas of intestinal schistosomiasis with low-intensity infections , the actual prevalence can be underestimated by up to 4 . 7 times when measured by the recommended standard procedure . The rigorous parasitological testing of three fecal samples allowed us to evaluate parasitological and immunochromatographic methods for diagnosis of infection with S . mansoni . The KK technique , even at its best was able to detect only two-thirds of the infected individuals . The best sensitivity rate ( over 80% ) was achieved with the Helmintex method . However , in its present form , Helmintex is not applicable for large-scale screening due to the required sample size and the time-consuming sieving and sedimentation processes [38] , but might be an adequate reference standard or gold standard for the evaluation of newly developed , field-based diagnostic tools . In addition , the performance of the POC-CCA was in the range of the best KK variant ( six slides from three fecal samples ) , but a high number of individuals were not correctly diagnosed ( false positive or false negative ) . Furthermore , studies are underway , in order to re-evaluate the use of standard serological methods and PCR-based detection of parasite DNA with our well-defined biological samples . We believe that a combination of methods has to be implemented since the schistosomiasis control programs in different regions of the world are moving from morbidity control towards transmission control and elimination .
|
Human infection with the flatworm Schistosoma mansoni continues to be a public health problem in many tropical countries , including Brazil . The parasitological method recommended by the World Health Organization for the detection of intestinal schistosomiasis , the Kato-Katz method ( KK ) , underestimates the prevalence of the infection in endemic areas with reduced parasite burden . When extensive and supplementary parasitological exams were performed , the prevalence of schistosomiasis in the examined population increased 2 . 3 times . Additional KK slides and other parasitological methods , such as saline gradient and Helmintex , allowed us to establish a strong reference standard that was used to assess the parasitological tests and the rapid urine test for the detection of the circulating cathodic antigen of S . mansoni ( POC-CCA ) . All tests readily detected the presence of the flatworm in individuals with medium to high parasite loads . The Helmintex method showed the best performance as it detected almost 84% of all infected individuals . A variant of the standard KK method , involving six fecal smears from three stool samples , detected two-thirds of all infections , thus having a performance comparable to that found with the POC-CCA . A combination of this variant KK method with the POC-CCA may be a field-applicable alternative to improve the diagnosis of S . mansoni infections in individuals with low parasite loads in endemic areas .
|
[
"Abstract",
"Introduction",
"Materials",
"and",
"methods",
"Results",
"Discussion"
] |
[
"schistosoma",
"invertebrates",
"schistosoma",
"mansoni",
"medicine",
"and",
"health",
"sciences",
"body",
"fluids",
"helminths",
"tropical",
"diseases",
"parasitic",
"diseases",
"animals",
"parasitology",
"urine",
"neglected",
"tropical",
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"intestinal",
"diseases",
"protozoan",
"infections",
"intestinal",
"schistosomiasis",
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"schistosomiasis",
"eukaryota",
"anatomy",
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"life",
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] |
2018
|
Evaluation of diagnostic methods for the detection of intestinal schistosomiasis in endemic areas with low parasite loads: Saline gradient, Helmintex, Kato-Katz and rapid urine test
|
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